77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# Lint as: python2, python3
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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Utilities for helping test ops."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from six.moves import range
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def ConvertBetweenDataFormats(x, data_format_src, data_format_dst):
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"""Converts 4D tensor between data formats."""
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valid_data_formats = ["NHWC", "NCHW", "HWNC", "HWCN"]
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if data_format_src not in valid_data_formats:
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raise ValueError("data_format_src must be of %s, got %s." %
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(valid_data_formats, data_format_src))
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if data_format_dst not in valid_data_formats:
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raise ValueError("data_format_dst must be of %s, got %s." %
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(valid_data_formats, data_format_dst))
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if len(x.shape) != 4:
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raise ValueError("x must be 4D, got shape %s." % x.shape)
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if data_format_src == data_format_dst:
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return x
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dim_map = {d: i for i, d in enumerate(data_format_src)}
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transpose_dims = [dim_map[d] for d in data_format_dst]
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return np.transpose(x, transpose_dims)
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def PermuteDimsBetweenDataFormats(dims, data_format_src, data_format_dst):
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"""Get new shape for converting between data formats."""
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valid_data_formats = ["NHWC", "NCHW", "HWNC", "HWCN"]
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if data_format_src not in valid_data_formats:
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raise ValueError("data_format_src must be of %s, got %s." %
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(valid_data_formats, data_format_src))
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if data_format_dst not in valid_data_formats:
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raise ValueError("data_format_dst must be of %s, got %s." %
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(valid_data_formats, data_format_dst))
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if len(dims) != 4:
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raise ValueError("dims must be of length 4, got %s." % dims)
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if data_format_src == data_format_dst:
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return dims
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dim_map = {d: i for i, d in enumerate(data_format_src)}
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permuted_dims = [dims[dim_map[d]] for d in data_format_dst]
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return permuted_dims
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_JIT_WARMUP_ITERATIONS = 10
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def RunWithWarmup(sess, op_to_run, feed_dict, options=None, run_metadata=None):
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"""Runs a graph a few times to ensure that its clusters are compiled."""
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for _ in range(0, _JIT_WARMUP_ITERATIONS):
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sess.run(op_to_run, feed_dict, options=options)
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return sess.run(
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op_to_run, feed_dict, options=options, run_metadata=run_metadata)
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