TensorFlow 2.10上线：Windows上扩展GPU支持，TF-DF 1.0发布

import tensorflow as tfembedding = tf.keras.layers.Embedding( input_dim=10, output_dim=3, mask_zero=True) # Infer a correct padding mask.# Instantiate a Keras multi-head attention (MHA) layer,# a layer normalization layer, and an `Add` layer object.mha = tf.keras.layers.MultiHeadAttention(key_dim=4, num_heads=1)layernorm = tf.keras.layers.LayerNormalization()add = tf.keras.layers.Add()# Test input.x = tf.constant([[1, 2, 3, 4, 5, 0, 0, 0, 0], [1, 2, 1, 0, 0, 0, 0, 0, 0]])# The embedding layer sets the mask.x = embedding(x)# The MHA layer uses and propagates the mask.a = mha(query=x, key=x, value=x, use_causal_mask=True)x = add([x, a]) # The `Add` layer propagates the mask.x = layernorm(x)# The mask made it through all layers.print(x._keras_mask)

> tf.Tensor(> [[ True True True True True False False False False]> [ True True True False False False False False False]], shape=(2, > 9), dtype=bool)