tf.contrib.quantize.experimental_create_eval_graph

Rewrites an eval input_graph in place for simulated quantization.

Variables added by the rewrite get added to the global variables collection.

This function has additional experimental options not (yet) available to create_eval_graph. The resulting behavior may be undefined.

The graph has fake quantization ops inserted to simulate the error introduced by quantization. Since the graph is transformed in place, the expected behavior of previously held references to nodes and tensors may change.

Args
input_graph The tf.Graph to be transformed, if None then defaults to the default graph.
weight_bits Number of bits to use for quantizing weights.
activation_bits Number of bits to use for quantizing activations.
symmetric If true, use symmetric quantization limits instead of training the minimum and maximum of each quantization range separately.
quant_delay Number of steps after which weights and activations are quantized during eval.
scope The scope to be transformed. If it's not None, only the ops which are in this scope will be transformed.
Raises
ValueError If elements contains an element that isn't a tf.Tensor or tf.Operation.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/quantize/experimental_create_eval_graph