TensorFlow のオブジェクト検出データを TFRecords で視覚化する

コンテンツ概要 データのバッチを視覚化する 電車と評価 Load Logs in Tensorboard 訓練されたモデルの保存と輸出 トレーニングモデルからの推論 テストデータの視覚化 輸入保存モデル 予測の視覚化 データのバッチを視覚化します。 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']) Create Category Index Dictionary to map the labels to corresponding label names. カテゴリーインデックス辞書を作成してラベルをマップします。 tf_ex_decoder = TfExampleDecoder(include_mask=True) TFRecords の結果を視覚化するためのヘルパー機能 利用 から 画像にボックスを描く。 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() 列車データの視覚化 Bounding Box Detection には、3つのコンポーネントがあります。 検出されたオブジェクトのクラスラベル 予測された真実の境界線と地上の真実の境界線の間に一致する割合。 セグメントマスク 注:すべてが100%である理由は、私たちが基本的な真理を視覚化しているからです。 すべてが100%である理由は、私たちが基本的な真理を視覚化しているからです。 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) 電車と評価 COCOチャレンジの伝統に従って、MAP(Mean Average Precision)に基づいてオブジェクト検出の精度を評価します。 検出タスクの評価メトリックがどのように行われているかについての詳細な説明のために。 ここ :は、予測された境界ボックスと地上真実境界ボックスの合併の領域で分かれる交差点の領域として定義されます。 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} Load Logs in Tensorboard %load_ext tensorboard %tensorboard --logdir "./trained_model" 訓練されたモデルの保存と輸出 THE Object Returned by データセットローダーによって、同じ平均値と変数統計を使用してデータを正常化することを期待します。 このエクスポート機能は、これらの詳細を処理しますので、 写真を撮り、正しい結果を得る。 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 トレーニングモデルからの推論 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 テストデータの視覚化 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) 輸入保存モデル 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_417522) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_415776) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_419385) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417171) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417396) with ops with unsaved custom gradients. Will likely fail if a gradient is requested. WARNING:absl:Importing a function (__inference_internal_grad_fn_417279) 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_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. 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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. 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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 予測の視覚化 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() 最初はTensorFlowのウェブサイトに掲載され、この記事はここに新しいタイトルの下に表示され、CC BY 4.0でライセンスを受けています。 最初はTensorFlowのウェブサイトに掲載され、この記事はここに新しいタイトルの下に表示され、CC BY 4.0でライセンスを受けています。 TensorFlowについて TensorFlowについて