Wizualizacja danych wykrywania obiektów w TensorFlow za pomocą TFRecords

Przegląd zawartości Wizualizuj baterię danych Pociąg i ocena Ładowanie w tenorboardzie Oszczędzanie i eksportowanie przeszkolonego modelu Inferencja z wyszkolonego modelu Wizualizacja danych testowych Importowanie modelu oszczędnościowego Wizualizacja prognoz Wizualizuj baterię danych. for images, labels in task.build_inputs(exp_config.task.train_data).take(1): print() print(f'images.shape: {str(images.shape):16} images.dtype: {images.dtype!r}') print(f'labels.keys: {labels.keys()}') WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/tensorflow/python/util/deprecation.py:660: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with dtype is deprecated and will be removed in a future version. Instructions for updating: Use fn_output_signature instead WARNING: All log messages before absl::InitializeLog() is called are written to STDERR W0000 00:00:1701347149.948159 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -56 } dim { size: -42 } dim { size: -43 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -3 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -3 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -3 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } images.shape: (8, 256, 256, 3) images.dtype: tf.float32 labels.keys: dict_keys(['anchor_boxes', 'image_info', 'rpn_score_targets', 'rpn_box_targets', 'gt_boxes', 'gt_classes', 'gt_outer_boxes', 'gt_masks']) Utwórz Słownik indeksowania kategorii, aby skopiować etykiety do odpowiednich nazw etykiet tf_ex_decoder = TfExampleDecoder(include_mask=True) Funkcja pomocnicza do wizualizacji wyników z TFRecords Użyj od Aby narysować pudełka na obrazku. visualize_boxes_and_labels_on_image_array visualization_utils def show_batch(raw_records): plt.figure(figsize=(20, 20)) use_normalized_coordinates=True min_score_thresh = 0.30 for i, serialized_example in enumerate(raw_records): plt.subplot(1, 3, i + 1) decoded_tensors = tf_ex_decoder.decode(serialized_example) image = decoded_tensors['image'].numpy().astype('uint8') scores = np.ones(shape=(len(decoded_tensors['groundtruth_boxes']))) # print(decoded_tensors['groundtruth_instance_masks'].numpy().shape) # print(decoded_tensors.keys()) visualization_utils.visualize_boxes_and_labels_on_image_array( image, decoded_tensors['groundtruth_boxes'].numpy(), decoded_tensors['groundtruth_classes'].numpy().astype('int'), scores, category_index=category_index, use_normalized_coordinates=use_normalized_coordinates, min_score_thresh=min_score_thresh, instance_masks=decoded_tensors['groundtruth_instance_masks'].numpy().astype('uint8'), line_thickness=4) plt.imshow(image) plt.axis("off") plt.title(f"Image-{i+1}") plt.show() Wizualizacja danych pociągów Detekcja skrzynki granicznej ma trzy elementy Etykieta klasy wykrytego obiektu. Odsetek dopasowania między polami graniczącymi prawdą przewidywaną i gruntową. Maska segmentacyjna Uwaga: Powodem, dla którego wszystko jest w 100%, jest to, że wizualizujemy podstawową prawdę Powodem, dla którego wszystko jest w 100%, jest to, że wizualizujemy podstawową prawdę. Note: buffer_size = 100 num_of_examples = 3 train_tfrecords = tf.io.gfile.glob(exp_config.task.train_data.input_path) raw_records = tf.data.TFRecordDataset(train_tfrecords).shuffle(buffer_size=buffer_size).take(num_of_examples) show_batch(raw_records) Pociąg i ocena Stosujemy tradycję COCO, aby ocenić dokładność wykrywania obiektów na podstawie mAP (średnia dokładność średnia). Aby uzyskać szczegółowe wyjaśnienie, w jaki sposób wykonuje się metryki oceny dla zadania wykrywania. tutaj : jest zdefiniowana jako obszar skrzyżowania podzielony przez obszar zjednoczenia przewidywanego pola granicznego i pola granicznego ziemi. IoU model, eval_logs = tfm.core.train_lib.run_experiment( distribution_strategy=distribution_strategy, task=task, mode='train_and_eval', params=exp_config, model_dir=model_dir, run_post_eval=True) INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). INFO:tensorflow:Reduce to /job:localhost/replica:0/task:0/device:CPU:0 then broadcast to ('/job:localhost/replica:0/task:0/device:CPU:0',). WARNING:tensorflow:`tf.keras.layers.experimental.SyncBatchNormalization` endpoint is deprecated and will be removed in a future release. Please use `tf.keras.layers.BatchNormalization` with parameter `synchronized` set to True. /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/engine/functional.py:642: UserWarning: Input dict contained keys ['6'] which did not match any model input. They will be ignored by the model. inputs = self._flatten_to_reference_inputs(inputs) WARNING:tensorflow:`tf.keras.layers.experimental.SyncBatchNormalization` endpoint is deprecated and will be removed in a future release. Please use `tf.keras.layers.BatchNormalization` with parameter `synchronized` set to True. /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/initializers/initializers.py:120: UserWarning: The initializer VarianceScaling is unseeded and being called multiple times, which will return identical values each time (even if the initializer is unseeded). Please update your code to provide a seed to the initializer, or avoid using the same initializer instance more than once. warnings.warn( loading annotations into memory... Done (t=0.01s) creating index... index created! restoring or initializing model... INFO:tensorflow:Customized initialization is done through the passed `init_fn`. INFO:tensorflow:Customized initialization is done through the passed `init_fn`. train | step: 0 | training until step 200... W0000 00:00:1701347174.666189 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -56 } dim { size: -42 } dim { size: -43 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -3 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -3 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -3 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 101 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 101 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 101 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 INFO:tensorflow:Collective all_reduce tensors: 101 all_reduces, num_devices = 4, group_size = 4, implementation = CommunicationImplementation.NCCL, num_packs = 1 train | step: 200 | steps/sec: 1.3 | output: {'frcnn_box_loss': 0.31850263, 'frcnn_cls_loss': 0.05660701, 'learning_rate': 0.06828698, 'mask_loss': 0.5251324, 'model_loss': 1.0341916, 'rpn_box_loss': 0.0608424, 'rpn_score_loss': 0.073107146, 'total_loss': 1.3348999, 'training_loss': 1.3348999} saved checkpoint to ./trained_model/ckpt-200. eval | step: 200 | running 200 steps of evaluation... W0000 00:00:1701347326.414129 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.55s). Accumulating evaluation results... DONE (t=0.37s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.003 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.004 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.010 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.009 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.027 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.007 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.096 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.77s). Accumulating evaluation results... DONE (t=0.36s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.002 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.013 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.010 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.008 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.024 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.021 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.099 eval | step: 200 | steps/sec: 2.5 | eval time: 80.1 sec | output: {'AP': 0.0034739533, 'AP50': 0.01818383, 'AP75': 0.000105925246, 'APl': 0.009990587, 'APm': 0.0038059496, 'APs': 0.00014011688, 'ARl': 0.096254684, 'ARm': 0.060511984, 'ARmax1': 0.008508347, 'ARmax10': 0.026843267, 'ARmax100': 0.04902959, 'ARs': 0.0065315315, 'mask_AP': 0.0021072333, 'mask_AP50': 0.012642865, 'mask_AP75': 1.1583788e-05, 'mask_APl': 0.010214079, 'mask_APm': 0.001238946, 'mask_APs': 5.1088673e-06, 'mask_ARl': 0.09868914, 'mask_ARm': 0.021187363, 'mask_ARmax1': 0.008023694, 'mask_ARmax10': 0.02381474, 'mask_ARmax100': 0.035661805, 'mask_ARs': 0.0015765766, 'steps_per_second': 2.49587810524514, 'validation_loss': 0.0} train | step: 200 | training until step 400... train | step: 400 | steps/sec: 1.7 | output: {'frcnn_box_loss': 0.3148728, 'frcnn_cls_loss': 0.04683144, 'learning_rate': 0.06331559, 'mask_loss': 0.41505823, 'model_loss': 0.8509541, 'rpn_box_loss': 0.054795396, 'rpn_score_loss': 0.019396221, 'total_loss': 1.1508584, 'training_loss': 1.1508584} saved checkpoint to ./trained_model/ckpt-400. eval | step: 400 | running 200 steps of evaluation... W0000 00:00:1701347440.748884 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=0.96s). Accumulating evaluation results... DONE (t=0.31s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.109 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.104 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.074 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.077 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.005 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.201 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.08s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.026 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.086 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.003 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.076 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.051 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.052 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.024 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.153 eval | step: 400 | steps/sec: 4.5 | eval time: 44.7 sec | output: {'AP': 0.037587434, 'AP50': 0.1090748, 'AP75': 0.018366594, 'APl': 0.10382032, 'APm': 0.022636896, 'APs': 0.0011642236, 'ARl': 0.20149812, 'ARm': 0.054738563, 'ARmax1': 0.04948842, 'ARmax10': 0.07442111, 'ARmax100': 0.07727517, 'ARs': 0.0054054055, 'mask_AP': 0.025703182, 'mask_AP50': 0.08565975, 'mask_AP75': 0.0030623602, 'mask_APl': 0.07599234, 'mask_APm': 0.012238867, 'mask_APs': 9.593982e-07, 'mask_ARl': 0.15299626, 'mask_ARm': 0.02369281, 'mask_ARmax1': 0.0364028, 'mask_ARmax10': 0.050511576, 'mask_ARmax100': 0.051857837, 'mask_ARs': 0.00022522523, 'steps_per_second': 4.477373324644756, 'validation_loss': 0.0} train | step: 400 | training until step 600... train | step: 600 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.27767265, 'frcnn_cls_loss': 0.049189795, 'learning_rate': 0.055572484, 'mask_loss': 0.39033934, 'model_loss': 0.7880812, 'rpn_box_loss': 0.051621474, 'rpn_score_loss': 0.019257905, 'total_loss': 1.0869627, 'training_loss': 1.0869627} saved checkpoint to ./trained_model/ckpt-600. eval | step: 600 | running 200 steps of evaluation... W0000 00:00:1701347519.556857 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.53s). Accumulating evaluation results... DONE (t=0.34s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.058 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.147 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.161 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.094 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.108 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.099 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.244 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.71s). Accumulating evaluation results... DONE (t=0.33s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.099 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.005 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.010 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.098 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.041 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.052 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.054 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.001 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.155 eval | step: 600 | steps/sec: 4.2 | eval time: 47.9 sec | output: {'AP': 0.057559177, 'AP50': 0.14743358, 'AP75': 0.034844287, 'APl': 0.1611763, 'APm': 0.035119582, 'APs': 0.0034293495, 'ARl': 0.24419476, 'ARm': 0.09869281, 'ARmax1': 0.0665136, 'ARmax10': 0.0941388, 'ARmax100': 0.10835528, 'ARs': 0.026576577, 'mask_AP': 0.028755136, 'mask_AP50': 0.0986329, 'mask_AP75': 0.00467551, 'mask_APl': 0.09832131, 'mask_APm': 0.010138089, 'mask_APs': 1.7697794e-06, 'mask_ARl': 0.15505618, 'mask_ARm': 0.030337691, 'mask_ARmax1': 0.040624514, 'mask_ARmax10': 0.052256178, 'mask_ARmax100': 0.05403324, 'mask_ARs': 0.0009009009, 'steps_per_second': 4.171504081290655, 'validation_loss': 0.0} train | step: 600 | training until step 800... train | step: 800 | steps/sec: 2.4 | output: {'frcnn_box_loss': 0.28230885, 'frcnn_cls_loss': 0.043198194, 'learning_rate': 0.045815594, 'mask_loss': 0.38323456, 'model_loss': 0.77104104, 'rpn_box_loss': 0.046326794, 'rpn_score_loss': 0.015972756, 'total_loss': 1.0689586, 'training_loss': 1.0689586} saved checkpoint to ./trained_model/ckpt-800. eval | step: 800 | running 200 steps of evaluation... W0000 00:00:1701347601.529665 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.01s). Accumulating evaluation results... DONE (t=0.32s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.063 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.147 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.046 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.004 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.177 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.097 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.103 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.015 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.256 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.14s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.045 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.124 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.136 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.053 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.001 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.192 eval | step: 800 | steps/sec: 4.4 | eval time: 45.0 sec | output: {'AP': 0.063469686, 'AP50': 0.1473477, 'AP75': 0.045820855, 'APl': 0.17694354, 'APm': 0.03674903, 'APs': 0.003920865, 'ARl': 0.25561798, 'ARm': 0.07761438, 'ARmax1': 0.07167474, 'ARmax10': 0.09676898, 'ARmax100': 0.10253096, 'ARs': 0.014639639, 'mask_AP': 0.04488069, 'mask_AP50': 0.12370826, 'mask_AP75': 0.0165427, 'mask_APl': 0.1360923, 'mask_APm': 0.017513687, 'mask_APs': 5.2146588e-05, 'mask_ARl': 0.19232209, 'mask_ARm': 0.029575163, 'mask_ARmax1': 0.053419493, 'mask_ARmax10': 0.064243406, 'mask_ARmax100': 0.06532041, 'mask_ARs': 0.0011261262, 'steps_per_second': 4.4475057268487275, 'validation_loss': 0.0} train | step: 800 | training until step 1000... train | step: 1000 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.26871693, 'frcnn_cls_loss': 0.04368285, 'learning_rate': 0.034999996, 'mask_loss': 0.38002, 'model_loss': 0.7526051, 'rpn_box_loss': 0.044981632, 'rpn_score_loss': 0.015203744, 'total_loss': 1.0497146, 'training_loss': 1.0497146} saved checkpoint to ./trained_model/ckpt-1000. eval | step: 1000 | running 200 steps of evaluation... W0000 00:00:1701347680.528202 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=0.98s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.078 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.165 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.065 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.010 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.083 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.107 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.110 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.088 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.267 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.05s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.046 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.129 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.143 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.001 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.190 eval | step: 1000 | steps/sec: 4.4 | eval time: 45.9 sec | output: {'AP': 0.078015566, 'AP50': 0.16489986, 'AP75': 0.06506885, 'APl': 0.20505275, 'APm': 0.0508199, 'APs': 0.009842132, 'ARl': 0.26666668, 'ARm': 0.0875817, 'ARmax1': 0.08303716, 'ARmax10': 0.10705439, 'ARmax100': 0.11001615, 'ARs': 0.018693693, 'mask_AP': 0.045874245, 'mask_AP50': 0.12868273, 'mask_AP75': 0.016570596, 'mask_APl': 0.14324915, 'mask_APm': 0.017211707, 'mask_APs': 9.338933e-05, 'mask_ARl': 0.18988764, 'mask_ARm': 0.030392157, 'mask_ARmax1': 0.0547119, 'mask_ARmax10': 0.0638126, 'mask_ARmax100': 0.06483576, 'mask_ARs': 0.0009009009, 'steps_per_second': 4.3583434846159985, 'validation_loss': 0.0} train | step: 1000 | training until step 1200... train | step: 1200 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.24772172, 'frcnn_cls_loss': 0.0436343, 'learning_rate': 0.024184398, 'mask_loss': 0.36858365, 'model_loss': 0.72140527, 'rpn_box_loss': 0.045137476, 'rpn_score_loss': 0.016328312, 'total_loss': 1.0178626, 'training_loss': 1.0178626} saved checkpoint to ./trained_model/ckpt-1200. eval | step: 1200 | running 200 steps of evaluation... W0000 00:00:1701347760.342535 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.15s). Accumulating evaluation results... DONE (t=0.31s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.084 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.176 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.069 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.010 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.056 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.219 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.090 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.114 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.124 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.110 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.277 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.28s). Accumulating evaluation results... DONE (t=0.31s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.024 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.016 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.153 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.037 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.196 eval | step: 1200 | steps/sec: 4.3 | eval time: 46.4 sec | output: {'AP': 0.08426202, 'AP50': 0.17574485, 'AP75': 0.06948364, 'APl': 0.21902785, 'APm': 0.0561062, 'APs': 0.010037346, 'ARl': 0.27734083, 'ARm': 0.10996732, 'ARmax1': 0.0897382, 'ARmax10': 0.114347786, 'ARmax100': 0.12382544, 'ARs': 0.03536036, 'mask_AP': 0.04775647, 'mask_AP50': 0.12510313, 'mask_AP75': 0.023735445, 'mask_APl': 0.15327115, 'mask_APm': 0.015975025, 'mask_APs': 9.356999e-05, 'mask_ARl': 0.19606742, 'mask_ARm': 0.036764707, 'mask_ARmax1': 0.05893583, 'mask_ARmax10': 0.06712107, 'mask_ARmax100': 0.068467334, 'mask_ARs': 0.0018018018, 'steps_per_second': 4.310460102047628, 'validation_loss': 0.0} train | step: 1200 | training until step 1400... train | step: 1400 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.23599713, 'frcnn_cls_loss': 0.041378804, 'learning_rate': 0.014427517, 'mask_loss': 0.35429612, 'model_loss': 0.68914723, 'rpn_box_loss': 0.042537488, 'rpn_score_loss': 0.014937655, 'total_loss': 0.98513216, 'training_loss': 0.98513216} saved checkpoint to ./trained_model/ckpt-1400. eval | step: 1400 | running 200 steps of evaluation... W0000 00:00:1701347840.710868 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.00s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.088 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.075 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.059 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.226 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.091 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.115 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.122 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.103 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.282 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.09s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.133 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.019 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.156 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.071 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.203 eval | step: 1400 | steps/sec: 4.5 | eval time: 44.5 sec | output: {'AP': 0.087541394, 'AP50': 0.1765836, 'AP75': 0.074927665, 'APl': 0.22625497, 'APm': 0.05886792, 'APs': 0.011434166, 'ARl': 0.28220972, 'ARm': 0.10310458, 'ARmax1': 0.09084545, 'ARmax10': 0.11534733, 'ARmax100': 0.12186322, 'ARs': 0.029279279, 'mask_AP': 0.050579414, 'mask_AP50': 0.13304058, 'mask_AP75': 0.027463775, 'mask_APl': 0.15557747, 'mask_APm': 0.018948099, 'mask_APs': 0.00015400951, 'mask_ARl': 0.20262173, 'mask_ARm': 0.036111113, 'mask_ARmax1': 0.05988153, 'mask_ARmax10': 0.070113085, 'mask_ARmax100': 0.07059774, 'mask_ARs': 0.0018018018, 'steps_per_second': 4.490972982132935, 'validation_loss': 0.0} train | step: 1400 | training until step 1600... train | step: 1600 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.2448898, 'frcnn_cls_loss': 0.040846318, 'learning_rate': 0.006684403, 'mask_loss': 0.3572018, 'model_loss': 0.69579756, 'rpn_box_loss': 0.038723875, 'rpn_score_loss': 0.014135833, 'total_loss': 0.99148893, 'training_loss': 0.99148893} saved checkpoint to ./trained_model/ckpt-1600. eval | step: 1600 | running 200 steps of evaluation... W0000 00:00:1701347919.382529 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.00s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.089 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.014 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.057 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.093 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.118 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.124 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.099 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.288 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.08s). Accumulating evaluation results... DONE (t=0.28s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.054 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.136 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.021 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.168 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.074 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.075 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.041 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.212 eval | step: 1600 | steps/sec: 4.4 | eval time: 45.6 sec | output: {'AP': 0.08937628, 'AP50': 0.17525133, 'AP75': 0.0808516, 'APl': 0.2315524, 'APm': 0.057085045, 'APs': 0.014369107, 'ARl': 0.28820226, 'ARm': 0.09918301, 'ARmax1': 0.09332256, 'ARmax10': 0.11814755, 'ARmax100': 0.12353258, 'ARs': 0.03400901, 'mask_AP': 0.053880908, 'mask_AP50': 0.1363149, 'mask_AP75': 0.03003062, 'mask_APl': 0.16768122, 'mask_APm': 0.021485755, 'mask_APs': 0.0002800922, 'mask_ARl': 0.21161048, 'mask_ARm': 0.040849674, 'mask_ARmax1': 0.063327946, 'mask_ARmax10': 0.07399031, 'mask_ARmax100': 0.07495961, 'mask_ARs': 0.0027027028, 'steps_per_second': 4.384812711815325, 'validation_loss': 0.0} train | step: 1600 | training until step 1800... train | step: 1800 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.23585029, 'frcnn_cls_loss': 0.039750163, 'learning_rate': 0.0017130232, 'mask_loss': 0.35994247, 'model_loss': 0.6895491, 'rpn_box_loss': 0.040137492, 'rpn_score_loss': 0.013868618, 'total_loss': 0.9850925, 'training_loss': 0.9850925} saved checkpoint to ./trained_model/ckpt-1800. eval | step: 1800 | running 200 steps of evaluation... W0000 00:00:1701347999.044772 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.04s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.089 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.085 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.058 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.230 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.092 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.117 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.123 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.102 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.282 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.12s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.133 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.025 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.019 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.159 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.200 eval | step: 1800 | steps/sec: 4.5 | eval time: 44.7 sec | output: {'AP': 0.08882947, 'AP50': 0.1769001, 'AP75': 0.084709905, 'APl': 0.23017395, 'APm': 0.05795139, 'APs': 0.012462094, 'ARl': 0.282397, 'ARm': 0.10163399, 'ARmax1': 0.09213786, 'ARmax10': 0.11690899, 'ARmax100': 0.122886375, 'ARs': 0.03445946, 'mask_AP': 0.050573327, 'mask_AP50': 0.13258772, 'mask_AP75': 0.025201378, 'mask_APl': 0.15921223, 'mask_APm': 0.019294621, 'mask_APs': 0.00025428535, 'mask_ARl': 0.20018727, 'mask_ARm': 0.03627451, 'mask_ARmax1': 0.06015078, 'mask_ARmax10': 0.06919763, 'mask_ARmax100': 0.07022078, 'mask_ARs': 0.002927928, 'steps_per_second': 4.474347551876668, 'validation_loss': 0.0} train | step: 1800 | training until step 2000... train | step: 2000 | steps/sec: 2.5 | output: {'frcnn_box_loss': 0.22732982, 'frcnn_cls_loss': 0.04367072, 'learning_rate': 0.0, 'mask_loss': 0.35671493, 'model_loss': 0.68381965, 'rpn_box_loss': 0.040140744, 'rpn_score_loss': 0.01596347, 'total_loss': 0.9793183, 'training_loss': 0.9793183} saved checkpoint to ./trained_model/ckpt-2000. eval | step: 2000 | running 200 steps of evaluation... W0000 00:00:1701348077.624909 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.05s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.091 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.178 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.086 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.013 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.062 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.093 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.119 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.125 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.103 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.286 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.12s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.053 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.136 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.164 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.040 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.207 eval | step: 2000 | steps/sec: 4.4 | eval time: 45.7 sec | output: {'AP': 0.09090912, 'AP50': 0.17810935, 'AP75': 0.08558971, 'APl': 0.23334582, 'APm': 0.0617902, 'APs': 0.013224964, 'ARl': 0.2863296, 'ARm': 0.10294118, 'ARmax1': 0.09337641, 'ARmax10': 0.11895531, 'ARmax100': 0.124663435, 'ARs': 0.035135135, 'mask_AP': 0.053071458, 'mask_AP50': 0.13569556, 'mask_AP75': 0.028363172, 'mask_APl': 0.16439752, 'mask_APm': 0.022396944, 'mask_APs': 0.00038678324, 'mask_ARl': 0.20692883, 'mask_ARm': 0.039542485, 'mask_ARmax1': 0.062250942, 'mask_ARmax10': 0.0724825, 'mask_ARmax100': 0.073236406, 'mask_ARs': 0.002927928, 'steps_per_second': 4.3735250426509005, 'validation_loss': 0.0} eval | step: 2000 | running 200 steps of evaluation... W0000 00:00:1701348123.440153 8938 op_level_cost_estimator.cc:699] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -5 } dim { size: -6 } dim { size: -7 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } value { dtype: DT_INT32 tensor_shape { dim { size: 2 } } int_val: 112 } } device { type: "CPU" vendor: "GenuineIntel" model: "111" frequency: 2199 num_cores: 32 environment { key: "cpu_instruction_set" value: "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 32768 l2_cache_size: 262144 l3_cache_size: 57671680 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 112 } dim { size: 112 } dim { size: 1 } } } creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=1.01s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.091 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.178 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.086 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.013 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.062 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.093 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.119 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.125 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.103 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.286 Running per image evaluation... Evaluate annotation type *segm* DONE (t=1.10s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.053 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.136 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.164 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.040 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.207 eval | step: 2000 | steps/sec: 4.4 | eval time: 45.8 sec | output: {'AP': 0.09090912, 'AP50': 0.17810935, 'AP75': 0.08558971, 'APl': 0.23334582, 'APm': 0.0617902, 'APs': 0.013224964, 'ARl': 0.2863296, 'ARm': 0.10294118, 'ARmax1': 0.09337641, 'ARmax10': 0.11895531, 'ARmax100': 0.124663435, 'ARs': 0.035135135, 'mask_AP': 0.053071458, 'mask_AP50': 0.13569556, 'mask_AP75': 0.028363172, 'mask_APl': 0.16439752, 'mask_APm': 0.022396944, 'mask_APs': 0.00038678324, 'mask_ARl': 0.20692883, 'mask_ARm': 0.039542485, 'mask_ARmax1': 0.062250942, 'mask_ARmax10': 0.0724825, 'mask_ARmax100': 0.073236406, 'mask_ARs': 0.002927928, 'steps_per_second': 4.370002598316903, 'validation_loss': 0.0} Ładowanie w tenorboardzie %load_ext tensorboard %tensorboard --logdir "./trained_model" Oszczędzanie i eksportowanie przeszkolonego modelu o Obiekt zwrócony przez oczekuje, że dane zostaną znormalizowane przez ładowarkę zbiorów danych przy użyciu tych samych statystyk średnich i różnicowych w Ta funkcja eksportu obsługuje te szczegóły, dzięki czemu można Zdjęcia i uzyskanie właściwych wyników. keras.Model train_lib.run_experiment preprocess_ops.normalize_image(image, offset=MEAN_RGB, scale=STDDEV_RGB) tf.uint8 export_saved_model_lib.export_inference_graph( input_type='image_tensor', batch_size=1, input_image_size=[HEIGHT, WIDTH], params=exp_config, checkpoint_path=tf.train.latest_checkpoint(model_dir), export_dir=export_dir) /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/engine/functional.py:642: UserWarning: Input dict contained keys ['6'] which did not match any model input. They will be ignored by the model. inputs = self._flatten_to_reference_inputs(inputs) WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. WARNING:tensorflow:Skipping full serialization of Keras layer , because it is not built. INFO:tensorflow:Assets written to: ./exported_model/assets INFO:tensorflow:Assets written to: ./exported_model/assets Inferencja z wyszkolonego modelu def load_image_into_numpy_array(path): """Load an image from file into a numpy array. Puts image into numpy array to feed into tensorflow graph. Note that by convention we put it into a numpy array with shape (height, width, channels), where channels=3 for RGB. Args: path: the file path to the image Returns: uint8 numpy array with shape (img_height, img_width, 3) """ image = None if(path.startswith('http')): response = urlopen(path) image_data = response.read() image_data = BytesIO(image_data) image = Image.open(image_data) else: image_data = tf.io.gfile.GFile(path, 'rb').read() image = Image.open(BytesIO(image_data)) (im_width, im_height) = image.size return np.array(image.getdata()).reshape( (1, im_height, im_width, 3)).astype(np.uint8) def build_inputs_for_object_detection(image, input_image_size): """Builds Object Detection model inputs for serving.""" image, _ = resize_and_crop_image( image, input_image_size, padded_size=input_image_size, aug_scale_min=1.0, aug_scale_max=1.0) return image Wizualizacja danych testowych num_of_examples = 3 test_tfrecords = tf.io.gfile.glob('./lvis_tfrecords/val*') test_ds = tf.data.TFRecordDataset(test_tfrecords).take(num_of_examples) show_batch(test_ds) Importowanie modelu oszczędnościowego imported = tf.saved_model.load(export_dir) model_fn = imported.signatures['serving_default'] WARNING:absl:Importing a function (__inference_internal_grad_fn_419718) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416667) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415362) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414651) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416415) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416739) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418449) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418179) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417081) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418368) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419556) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419097) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414750) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419124) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417927) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418674) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416847) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418899) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415020) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414399) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418197) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418476) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416775) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415272) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416685) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. 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WARNING:absl:Importing a function (__inference_internal_grad_fn_416343) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413760) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417324) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415344) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416235) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417846) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415308) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415902) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414291) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418773) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416280) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415092) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417567) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413679) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418962) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413661) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415200) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414786) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416010) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413985) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417954) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414354) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416703) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414516) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419349) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416091) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417297) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419646) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415830) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414435) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415263) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419493) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418620) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419439) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417261) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417873) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. 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WARNING:absl:Importing a function (__inference_internal_grad_fn_413787) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416568) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417108) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415326) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419358) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417945) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414156) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414462) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418008) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415452) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419070) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418107) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417243) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416046) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416559) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413580) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414300) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419673) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414255) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415758) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413967) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414795) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414687) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416307) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416469) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414741) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418422) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414192) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415938) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414030) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415560) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415038) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415380) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418548) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414228) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416928) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418872) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417423) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417711) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413850) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416748) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418494) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419052) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417837) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417180) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419565) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416640) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417675) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416919) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417342) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414723) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414408) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416226) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415056) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414597) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415983) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418485) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415686) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416649) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415173) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418719) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414876) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417918) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416028) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415866) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414660) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415893) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418305) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419214) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413589) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418062) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419232) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417693) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419421) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418350) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417549) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415884) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414111) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417756) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415821) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418881) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413625) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413859) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417405) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417072) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417639) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419511) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415209) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418278) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416631) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418683) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414084) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416451) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418935) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418566) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413634) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419277) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417000) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416460) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416397) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418224) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415929) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415992) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417513) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415677) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415137) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417864) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419007) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413877) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414867) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417666) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415515) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416262) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417684) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414804) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419196) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419268) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419295) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416163) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416802) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418026) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414453) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419250) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415488) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415416) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417486) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415920) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418242) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418647) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415182) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415587) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413643) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413454) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415425) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419655) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419520) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414903) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418359) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415083) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413733) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419403) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417468) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418377) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414129) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417090) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418845) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415839) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415164) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416271) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415524) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414381) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417144) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416658) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414849) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419583) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417036) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419151) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418791) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419241) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417216) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413940) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416055) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414489) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414093) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414102) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417900) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415947) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414219) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417045) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414012) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415875) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418116) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414939) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413544) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419457) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418611) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414993) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419547) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414696) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413688) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417333) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414615) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417702) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419034) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418584) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415731) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416001) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418170) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418953) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413841) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413706) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414588) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418593) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418665) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419205) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416523) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415767) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417414) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414759) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415398) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416433) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413607) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418971) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417603) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413562) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417558) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416829) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413535) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415245) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418125) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419367) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419412) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419259) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414336) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416478) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416325) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413652) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413517) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418854) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417459) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416550) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415281) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413814) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419691) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416208) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414543) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414039) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414165) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415911) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417999) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414309) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415722) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414975) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414948) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419628) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415299) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415011) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416424) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416532) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417855) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416154) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416064) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415749) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415542) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417378) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419133) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414966) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417225) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419106) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419016) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414570) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414840) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418656) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415353) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415434) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415128) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413481) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418386) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414858) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415065) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419286) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419142) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418728) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416910) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413445) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418458) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417315) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416406) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417936) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419700) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414057) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417621) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416883) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416856) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414003) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413958) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418251) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416199) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414120) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417432) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417810) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416352) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416361) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417018) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415074) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414579) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416784) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414327) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416811) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415668) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413715) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416145) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414624) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416964) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416676) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416082) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418746) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414561) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414066) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419736) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419727) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419376) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414534) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419169) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415002) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419025) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418332) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418233) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416370) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416793) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414669) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413526) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415110) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416613) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414831) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413571) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419187) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413778) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417198) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418926) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414021) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415254) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418629) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419331) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419637) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418143) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417747) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415803) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416172) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417387) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414525) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416901) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419619) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418269) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417720) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414237) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415389) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416109) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415974) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415335) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418989) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419160) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416127) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417909) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417774) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414363) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419313) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414210) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414345) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418800) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417819) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418890) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415659) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413616) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418692) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416541) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417972) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415857) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417630) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415704) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414642) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415569) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416982) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414714) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413751) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413904) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416298) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416991) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418755) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414282) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417540) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415506) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418944) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418530) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418260) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418287) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419178) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415578) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417009) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413868) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415155) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418467) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415218) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415236) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418053) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419061) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414732) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414930) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419529) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415119) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413886) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414633) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416892) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416037) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416487) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414417) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414201) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417207) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415596) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414912) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415794) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416244) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416766) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419322) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418431) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413796) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418521) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414606) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415461) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417234) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415695) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417963) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415632) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414984) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417792) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415407) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414075) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416388) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413508) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419745) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418206) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414822) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414768) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417585) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419448) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419340) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417135) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418215) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417126) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414507) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416874) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418098) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413769) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413931) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414471) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419115) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414813) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414246) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417531) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413436) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417369) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416721) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416379) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417504) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418512) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415533) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414921) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417477) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414498) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418836) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419043) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415227) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415317) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416217) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413553) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418827) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413913) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413922) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419592) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417783) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416973) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418395) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417648) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415290) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418557) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414894) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415614) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413823) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417594) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419538) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415623) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417612) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414138) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419475) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417360) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415650) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418908) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418071) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416622) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416190) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418035) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416712) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418503) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418152) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416586) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419610) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417162) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419682) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418413) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413895) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414777) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418080) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413670) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418980) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416838) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416595) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415497) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413490) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417099) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418764) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417063) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415812) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416730) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415605) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417306) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416334) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414678) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415101) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413472) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415371) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414048) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419664) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416955) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416757) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418314) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417657) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415191) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417495) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418917) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418539) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418161) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418863) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414183) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416505) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418737) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417738) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418134) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415551) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414390) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414264) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417288) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415740) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419502) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418323) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418296) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416577) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415443) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413463) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418638) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415029) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418701) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417441) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417252) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417189) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416136) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414480) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418017) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417576) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418782) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418404) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413832) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416253) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416937) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415713) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415785) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418440) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419574) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417891) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416946) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413598) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414174) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418089) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419394) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417765) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418809) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414426) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413994) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418341) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416442) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418818) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418602) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417981) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417054) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413697) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414705) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417729) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416604) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419466) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418575) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419223) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413742) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418998) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416496) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415965) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_418710) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415848) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419709) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415956) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417351) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415047) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416865) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414273) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_416820) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415641) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417027) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414318) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_414444) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_413724) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415470) with ops with unsaved cust Wizualizacja prognoz def reframe_image_corners_relative_to_boxes(boxes): """Reframe the image corners ([0, 0, 1, 1]) to be relative to boxes. The local coordinate frame of each box is assumed to be relative to its own for corners. Args: boxes: A float tensor of [num_boxes, 4] of (ymin, xmin, ymax, xmax) coordinates in relative coordinate space of each bounding box. Returns: reframed_boxes: Reframes boxes with same shape as input. """ ymin, xmin, ymax, xmax = (boxes[:, 0], boxes[:, 1], boxes[:, 2], boxes[:, 3]) height = tf.maximum(ymax - ymin, 1e-4) width = tf.maximum(xmax - xmin, 1e-4) ymin_out = (0 - ymin) / height xmin_out = (0 - xmin) / width ymax_out = (1 - ymin) / height xmax_out = (1 - xmin) / width return tf.stack([ymin_out, xmin_out, ymax_out, xmax_out], axis=1) def reframe_box_masks_to_image_masks(box_masks, boxes, image_height, image_width, resize_method='bilinear'): """Transforms the box masks back to full image masks. Embeds masks in bounding boxes of larger masks whose shapes correspond to image shape. Args: box_masks: A tensor of size [num_masks, mask_height, mask_width]. boxes: A tf.float32 tensor of size [num_masks, 4] containing the box corners. Row i contains [ymin, xmin, ymax, xmax] of the box corresponding to mask i. Note that the box corners are in normalized coordinates. image_height: Image height. The output mask will have the same height as the image height. image_width: Image width. The output mask will have the same width as the image width. resize_method: The resize method, either 'bilinear' or 'nearest'. Note that 'bilinear' is only respected if box_masks is a float. Returns: A tensor of size [num_masks, image_height, image_width] with the same dtype as `box_masks`. """ resize_method = 'nearest' if box_masks.dtype == tf.uint8 else resize_method # TODO(rathodv): Make this a public function. def reframe_box_masks_to_image_masks_default(): """The default function when there are more than 0 box masks.""" num_boxes = tf.shape(box_masks)[0] box_masks_expanded = tf.expand_dims(box_masks, axis=3) resized_crops = tf.image.crop_and_resize( image=box_masks_expanded, boxes=reframe_image_corners_relative_to_boxes(boxes), box_indices=tf.range(num_boxes), crop_size=[image_height, image_width], method=resize_method, extrapolation_value=0) return tf.cast(resized_crops, box_masks.dtype) image_masks = tf.cond( tf.shape(box_masks)[0] > 0, reframe_box_masks_to_image_masks_default, lambda: tf.zeros([0, image_height, image_width, 1], box_masks.dtype)) return tf.squeeze(image_masks, axis=3) input_image_size = (HEIGHT, WIDTH) plt.figure(figsize=(20, 20)) min_score_thresh = 0.40 # Change minimum score for threshold to see all bounding boxes confidences for i, serialized_example in enumerate(test_ds): plt.subplot(1, 3, i+1) decoded_tensors = tf_ex_decoder.decode(serialized_example) image = build_inputs_for_object_detection(decoded_tensors['image'], input_image_size) image = tf.expand_dims(image, axis=0) image = tf.cast(image, dtype = tf.uint8) image_np = image[0].numpy() result = model_fn(image) # Visualize detection and masks if 'detection_masks' in result: # we need to convert np.arrays to tensors detection_masks = tf.convert_to_tensor(result['detection_masks'][0]) detection_boxes = tf.convert_to_tensor(result['detection_boxes'][0]) detection_masks_reframed = reframe_box_masks_to_image_masks( detection_masks, detection_boxes/256.0, image_np.shape[0], image_np.shape[1]) detection_masks_reframed = tf.cast( detection_masks_reframed > min_score_thresh, np.uint8) result['detection_masks_reframed'] = detection_masks_reframed.numpy() visualization_utils.visualize_boxes_and_labels_on_image_array( image_np, result['detection_boxes'][0].numpy(), (result['detection_classes'][0] + 0).numpy().astype(int), result['detection_scores'][0].numpy(), category_index=category_index, use_normalized_coordinates=False, max_boxes_to_draw=200, min_score_thresh=min_score_thresh, instance_masks=result.get('detection_masks_reframed', None), line_thickness=4) plt.imshow(image_np) plt.axis("off") plt.show() Pierwotnie opublikowany na stronie internetowej TensorFlow, ten artykuł pojawia się tutaj pod nowym tytułem i jest licencjonowany pod CC BY 4.0. Pierwotnie opublikowany na stronie internetowej TensorFlow, ten artykuł pojawia się tutaj pod nowym tytułem i jest licencjonowany pod CC BY 4.0. TensorFlow TensorFlow