# Copyright 2021 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Keras-based transformer block layer.""" import functools import tensorflow as tf class TfFunctionIfEagerDecorator(object): """Helper decorator function to optionally apply the @tf.function annotation.""" def __init__(self, **kwargs): self.func_kwargs = kwargs def __call__(self, func): @functools.wraps(func) def wrapped_func(*args): # TODO(b/150147476, b/150024785): Fix tf.function in TF1 crash. if not hasattr(tf.compat.v1, 'executing_eagerly_outside_functions' ) or tf.compat.v1.executing_eagerly_outside_functions(): return tf.function(func=func, **self.func_kwargs)(*args) return func(*args) # Cache the created function in self._call_impl. if not hasattr(self, '_call_impl'): self._call_impl = wrapped_func return self._call_impl def tf_function_if_eager(**kwargs): """Applies the @tf.function decorator only if running in eager mode.""" return TfFunctionIfEagerDecorator(**kwargs) def filter_kwargs(kwargs): """In place removes unused options in kwargs. This function removes the construction signatures: e.g. number_attention_heads... in TransformerEncoderBlock. This is needed, otherwise base_layer.py in Keras will complain. Args: kwargs: keyword arguments to be filtered. """ # This is the union of signatures of TransformerEncoderBlock and # ReZeroTransformer. Every Transformer # block that uses compatible signature with TransformerEncoderBlock should # call this function before base constructor super().__init__(**kwargs). denylist = [ 'num_attention_heads', 'intermediate_size', 'intermediate_activation', 'inner_dim', 'inner_activation', 'output_range', 'kernel_initializer', 'bias_initializer', 'kernel_regularizer', 'bias_regularizer', 'activity_regularizer', 'kernel_constraint', 'bias_constraint', 'use_bias', 'norm_first', 'norm_epsilon', 'output_dropout', 'attention_dropout', 'inner_dropout', 'attention_initializer', 'attention_axes', 'share_rezero' ] for unused_key in denylist: kwargs.pop(unused_key, None)