የ Tensor Slicing እና Data Insertion በ TensorFlow ጋር ቀላል

አጠቃላይ ግምገማ አግኙን የ Tensor Slices አጠቃቀም ውሂብ በ Tensors ውስጥ ይመዝገቡ ተጨማሪ ያንብቡ እና Ressources የ ML መተግበሪያዎች እንደ ንጥረ-የተግበሪያዎች እና የ NLP እንደ መተግበሪያዎች ላይ በመተግበሪያዎች ላይ ይሰራሉ ጊዜ, አንዳንድ ጊዜ tensors ን ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች ንጥረ-የተግበሪያዎች በ NLP መተግበሪያዎች ውስጥ, የ Tensor Slicing በመጠቀም የጽሑፍ ማሸጊያ መተግበር ይችላሉ. ለምሳሌ, እርስዎ የጽሑፍ ማሸጊያ ለሁሉም የጽሑፍ ውስጥ የጽሑፍ ማሸጊያ ለማግኘት የጽሑፍ ማሸጊያ ለመምረጥ የጽሑፍ ማሸጊያ ውሂብ ለመምረጥ እና ከዚያም የጽሑፍ ማሸጊያ በጽሑፍ የጽሑፍ ማሸጊያ መተግበሪያዎችን ለመምረጥ ይችላሉ. በዚህ መመሪያ ውስጥ, የ TensorFlow APIs እንዴት እንደሚጠቀሙ እንደሚቻል ያገኛሉ: አንድ Tensor ከ መቁረጥ በ Tensor ውስጥ ልዩ ትዕዛዞች ላይ ውሂብ መውሰድ ይህ መመሪያ የ tensor indexing ን ያውቃል. እና ይህን መመሪያ ጋር መጀመር በፊት. አግኙን በ TensorFlow NumPy አግኙን import tensorflow as tf import numpy as np 2024-08-15 02:59:22.387959: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2024-08-15 02:59:22.409014: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2024-08-15 02:59:22.415391: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered የ Tensor Slices አጠቃቀም በ NumPy-like tensor slicing ይጠቀሙ . tf.slice t1 = tf.constant([0, 1, 2, 3, 4, 5, 6, 7]) print(tf.slice(t1, begin=[1], size=[3])) tf.Tensor([1 2 3], shape=(3,), dtype=int32) WARNING: All log messages before absl::InitializeLog() is called are written to STDERR I0000 00:00:1723690765.029742 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.033507 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.037154 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.040869 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.052765 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.056359 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.059719 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.063138 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.066532 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.070040 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.073650 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690765.077235 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.300773 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.302797 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.304766 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.306851 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.308843 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.310723 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.312589 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.314574 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.316423 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.318291 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.320168 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.322150 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.360968 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.362946 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.364849 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.366867 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.368710 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.370591 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.372447 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.374435 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.376302 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.378677 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.380966 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00:00:1723690766.383365 169903 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 የፓይቶኒክ ስቴትስ ይጠቀሙ ይችላሉ. የ tensor ስኬቶች በ start-stop አካባቢ ላይ ተመሳሳይ ሁኔታዎች ላይ ይሰጣሉ. print(t1[1:4]) tf.Tensor([1 2 3], shape=(3,), dtype=int32) print(t1[-3:]) tf.Tensor([5 6 7], shape=(3,), dtype=int32) ለ 2 ዲሜትር tensors,እርስዎ እንደ ነገር መጠቀም ይችላሉ: t2 = tf.constant([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19]]) print(t2[:-1, 1:3]) tf.Tensor( [[ 1 2] [ 6 7] [11 12]], shape=(3, 2), dtype=int32) መጠቀም ይችላሉ በተጨማሪም ከፍተኛ መጠኖች ላይ. tf.slice t3 = tf.constant([[[1, 3, 5, 7], [9, 11, 13, 15]], [[17, 19, 21, 23], [25, 27, 29, 31]] ]) print(tf.slice(t3, begin=[1, 1, 0], size=[1, 1, 2])) tf.Tensor([[[25 27]]], shape=(1, 1, 2), dtype=int32) በተጨማሪም መጠቀም ይችላሉ በ "Tensor Dimensions" ላይ በ "Tensor Dimensions" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "Tensors" ላይ በ "T tf.strided_slice አጠቃቀም በ Tensor ውስጥ አንድ አጠቃቀም አጠቃቀም አጠቃቀም. tf.gather print(tf.gather(t1, indices=[0, 3, 6])) # This is similar to doing t1[::3] tf.Tensor([0 3 6], shape=(3,), dtype=int32) እያንዳንዱ ምድቦች በተመሳሳይ መጠን ሊያስፈልግም. tf.gather alphabet = tf.constant(list('abcdefghijklmnopqrstuvwxyz')) print(tf.gather(alphabet, indices=[2, 0, 19, 18])) tf.Tensor([b'c' b'a' b't' b's'], shape=(4,), dtype=string) ከብዙ አዝማሚያዎች ከ tensor መውሰድ, መጠቀም ይህ ቀለም ወይም ቀለሞች ብቻ ከታሪክስ ክፍሎች ለመጨመር የሚፈልጉት ጊዜ ተስማሚ ነው. tf.gather_nd t4 = tf.constant([[0, 5], [1, 6], [2, 7], [3, 8], [4, 9]]) print(tf.gather_nd(t4, indices=[[2], [3], [0]])) tf.Tensor( [[2 7] [3 8] [0 5]], shape=(3, 2), dtype=int32) t5 = np.reshape(np.arange(18), [2, 3, 3]) print(tf.gather_nd(t5, indices=[[0, 0, 0], [1, 2, 1]])) tf.Tensor([ 0 16], shape=(2,), dtype=int64) # Return a list of two matrices print(tf.gather_nd(t5, indices=[[[0, 0], [0, 2]], [[1, 0], [1, 2]]])) tf.Tensor( [[[ 0 1 2] [ 6 7 8]] [[ 9 10 11] [15 16 17]]], shape=(2, 2, 3), dtype=int64) # Return one matrix print(tf.gather_nd(t5, indices=[[0, 0], [0, 2], [1, 0], [1, 2]])) tf.Tensor( [[ 0 1 2] [ 6 7 8] [ 9 10 11] [15 16 17]], shape=(4, 3), dtype=int64) ውሂብ በ Tensors ውስጥ ይመዝገቡ አጠቃቀም በ Tensor ውስጥ የተወሰነ ክፍሎች / ኢንዱስትሪዎች ላይ ውሂብ መውሰድ ይችላሉ. በ Tensor ውስጥ እርስዎ ውሂብ መውሰድ የሚፈልጉት ውሂብ 0-initialized ነው. tf.scatter_nd t6 = tf.constant([10]) indices = tf.constant([[1], [3], [5], [7], [9]]) data = tf.constant([2, 4, 6, 8, 10]) print(tf.scatter_nd(indices=indices, updates=data, shape=t6)) tf.Tensor([ 0 2 0 4 0 6 0 8 0 10], shape=(10,), dtype=int32) እንደ ዘዴዎች ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት ከባድ ስሜት እና የ SPARSE TENSOR OPS አጠቃቀም አጠቃቀም. tf.scatter_nd tf.gather_nd tf.scatter_nd አንድ ምሳሌ ይመልከቱ, በዚያ ሁለት ዘዴዎች በመጠቀም አንድ አነስተኛ tensor ለመፍጠር. # Gather values from one tensor by specifying indices new_indices = tf.constant([[0, 2], [2, 1], [3, 3]]) t7 = tf.gather_nd(t2, indices=new_indices) # Add these values into a new tensor t8 = tf.scatter_nd(indices=new_indices, updates=t7, shape=tf.constant([4, 5])) print(t8) tf.Tensor( [[ 0 0 2 0 0] [ 0 0 0 0 0] [ 0 11 0 0 0] [ 0 0 0 18 0]], shape=(4, 5), dtype=int32) ይህ ተመሳሳይ ነው: t9 = tf.SparseTensor(indices=[[0, 2], [2, 1], [3, 3]], values=[2, 11, 18], dense_shape=[4, 5]) print(t9) SparseTensor(indices=tf.Tensor( [[0 2] [2 1] [3 3]], shape=(3, 2), dtype=int64), values=tf.Tensor([ 2 11 18], shape=(3,), dtype=int32), dense_shape=tf.Tensor([4 5], shape=(2,), dtype=int64)) # Convert the sparse tensor into a dense tensor t10 = tf.sparse.to_dense(t9) print(t10) tf.Tensor( [[ 0 0 2 0 0] [ 0 0 0 0 0] [ 0 11 0 0 0] [ 0 0 0 18 0]], shape=(4, 5), dtype=int32) ከባድ ውሂብ ከባድ ውሂብ ከባድ ውሂብ ከባድ ውሂብ ከባድ ውሂብ ከባድ ውሂብ ውሂብ . tf.tensor_scatter_nd_add t11 = tf.constant([[2, 7, 0], [9, 0, 1], [0, 3, 8]]) # Convert the tensor into a magic square by inserting numbers at appropriate indices t12 = tf.tensor_scatter_nd_add(t11, indices=[[0, 2], [1, 1], [2, 0]], updates=[6, 5, 4]) print(t12) tf.Tensor( [[2 7 6] [9 5 1] [4 3 8]], shape=(3, 3), dtype=int32) በተጨማሪም ጥቅም ላይ የ Tensor እና የ Pre-Existing Values አጠቃቀም. tf.tensor_scatter_nd_sub # Convert the tensor into an identity matrix t13 = tf.tensor_scatter_nd_sub(t11, indices=[[0, 0], [0, 1], [1, 0], [1, 1], [1, 2], [2, 1], [2, 2]], updates=[1, 7, 9, -1, 1, 3, 7]) print(t13) tf.Tensor( [[1 0 0] [0 1 0] [0 0 1]], shape=(3, 3), dtype=int32) አጠቃቀም አንድ ንጥረ መለያ ወደ ሌላ ንጥረ መለያ መጠቀም. tf.tensor_scatter_nd_min t14 = tf.constant([[-2, -7, 0], [-9, 0, 1], [0, -3, -8]]) t15 = tf.tensor_scatter_nd_min(t14, indices=[[0, 2], [1, 1], [2, 0]], updates=[-6, -5, -4]) print(t15) tf.Tensor( [[-2 -7 -6] [-9 -5 1] [-4 -3 -8]], shape=(3, 3), dtype=int32) በተጨማሪም ጥቅም ላይ ከሁሉም ክፍሎች ከሁሉም ክፍሎች ከሁሉም ክፍሎች ወደ አንድ ክፍሎች ወደ አንድ ክፍሎች ወደ አንድ ክፍሎች. tf.tensor_scatter_nd_max t16 = tf.tensor_scatter_nd_max(t14, indices=[[0, 2], [1, 1], [2, 0]], updates=[6, 5, 4]) print(t16) tf.Tensor( [[-2 -7 6] [-9 5 1] [ 4 -3 -8]], shape=(3, 3), dtype=int32) ተጨማሪ ያንብቡ እና Ressources በዚህ መመሪያ ውስጥ, በ TensorFlow ጋር ይገኛል የ tensor slicing ops እንዴት እንደሚጠቀሙ እና በ tensors ውስጥ ንጥሎች ላይ ይበልጥ ቁጥጥር እንደሚቻል ያውቃሉ. በ TensorFlow NumPy እንደ tf.experimental.numpy.take_along_axis እና tf.experimental.numpy.take ላይ ይገኛል. በተጨማሪም Tensor መመሪያ እና Variable መመሪያ ይመልከቱ. በመጀመሪያ በ TensorFlow ድር ጣቢያ ላይ የተለጠፈው, ይህ ጽሑፍ እዚህ አንድ አዲስ ምልክት ውስጥ ይመልከቱ እና በ CC BY 4.0. ኮድ ናሙናዎች በ Apache 2.0 License መሠረት ይሰጣል. በመጀመሪያ በ TensorFlow ድር ጣቢያ ላይ የተለጠፈው, ይህ ጽሑፍ እዚህ አንድ አዲስ ምልክት ውስጥ ይመልከቱ እና በ CC BY 4.0. ኮድ ናሙናዎች በ Apache 2.0 License መሠረት ይሰጣል. የ TensorFlow የ TensorFlow