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- # Copyright 2018 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.
- # ==============================================================================
- """Functions for quantized training and evaluation."""
-
- import tensorflow as tf
-
-
- def build(graph_rewriter_config, is_training):
- """Returns a function that modifies default graph based on options.
-
- Args:
- graph_rewriter_config: graph_rewriter_pb2.GraphRewriter proto.
- is_training: whether in training of eval mode.
- """
- def graph_rewrite_fn():
- """Function to quantize weights and activation of the default graph."""
- if (graph_rewriter_config.quantization.weight_bits != 8 or
- graph_rewriter_config.quantization.activation_bits != 8):
- raise ValueError('Only 8bit quantization is supported')
-
- # Quantize the graph by inserting quantize ops for weights and activations
- if is_training:
- tf.contrib.quantize.create_training_graph(
- input_graph=tf.get_default_graph(),
- quant_delay=graph_rewriter_config.quantization.delay)
- else:
- tf.contrib.quantize.create_eval_graph(input_graph=tf.get_default_graph())
-
- tf.contrib.layers.summarize_collection('quant_vars')
- return graph_rewrite_fn
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