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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.
# ==============================================================================
"""Utilities for helping test ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
def ConvertBetweenDataFormats(x, data_format_src, data_format_dst):
"""Converts 4D tensor between data formats."""
valid_data_formats = ["NHWC", "NCHW", "HWNC", "HWCN"]
if data_format_src not in valid_data_formats:
raise ValueError("data_format_src must be of %s, got %s." %
(valid_data_formats, data_format_src))
if data_format_dst not in valid_data_formats:
raise ValueError("data_format_dst must be of %s, got %s." %
(valid_data_formats, data_format_dst))
if len(x.shape) != 4:
raise ValueError("x must be 4D, got shape %s." % x.shape)
if data_format_src == data_format_dst:
return x
dim_map = {d: i for i, d in enumerate(data_format_src)}
transpose_dims = [dim_map[d] for d in data_format_dst]
return np.transpose(x, transpose_dims)
def PermuteDimsBetweenDataFormats(dims, data_format_src, data_format_dst):
"""Get new shape for converting between data formats."""
valid_data_formats = ["NHWC", "NCHW", "HWNC", "HWCN"]
if data_format_src not in valid_data_formats:
raise ValueError("data_format_src must be of %s, got %s." %
(valid_data_formats, data_format_src))
if data_format_dst not in valid_data_formats:
raise ValueError("data_format_dst must be of %s, got %s." %
(valid_data_formats, data_format_dst))
if len(dims) != 4:
raise ValueError("dims must be of length 4, got %s." % dims)
if data_format_src == data_format_dst:
return dims
dim_map = {d: i for i, d in enumerate(data_format_src)}
permuted_dims = [dims[dim_map[d]] for d in data_format_dst]
return permuted_dims
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