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# Copyright 2015 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.
# ==============================================================================
"""Functional tests for ExtractImagePatches op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class ExtractImagePatches(test.TestCase):
"""Functional tests for ExtractImagePatches op."""
def _VerifyValues(self, image, ksizes, strides, rates, padding, patches):
"""Tests input-output pairs for the ExtractImagePatches op.
Args:
image: Input tensor with shape: [batch, in_rows, in_cols, depth].
ksizes: Patch size specified as: [ksize_rows, ksize_cols].
strides: Output strides, specified as [stride_rows, stride_cols].
rates: Atrous rates, specified as [rate_rows, rate_cols].
padding: Padding type.
patches: Expected output.
"""
ksizes = [1] + ksizes + [1]
strides = [1] + strides + [1]
rates = [1] + rates + [1]
with self.test_session(use_gpu=True):
out_tensor = array_ops.extract_image_patches(
constant_op.constant(image),
ksizes=ksizes,
strides=strides,
rates=rates,
padding=padding,
name="im2col")
self.assertAllClose(patches, out_tensor.eval())
def testKsize1x1Stride1x1Rate1x1(self):
"""Verifies that for 1x1 kernel the output equals the input."""
# [2, 3, 4, 5]
image = np.reshape(range(120), [2, 3, 4, 5])
# [2, 3, 4, 5]
patches = np.reshape(range(120), [2, 3, 4, 5])
for padding in ["VALID", "SAME"]:
self._VerifyValues(
image,
ksizes=[1, 1],
strides=[1, 1],
rates=[1, 1],
padding=padding,
patches=patches)
def testKsize1x1Stride2x3Rate1x1(self):
"""Test for 1x1 kernel and strides."""
# [2, 4, 5, 3]
image = np.reshape(range(120), [2, 4, 5, 3])
# [2, 2, 2, 3]
patches = image[:, ::2, ::3, :]
for padding in ["VALID", "SAME"]:
self._VerifyValues(
image,
ksizes=[1, 1],
strides=[2, 3],
rates=[1, 1],
padding=padding,
patches=patches)
def testKsize2x2Stride1x1Rate1x1Valid(self):
"""Test for 2x2 kernel with VALID padding."""
# [1, 2, 2, 1]
image = [[[[1], [2]], [[3], [4]]]]
# [1, 1, 1, 4]
patches = [[[[1, 2, 3, 4]]]]
self._VerifyValues(
image,
ksizes=[2, 2],
strides=[1, 1],
rates=[1, 1],
padding="VALID",
patches=patches)
def testKsize2x2Stride1x1Rate1x1Same(self):
"""Test for 2x2 kernel with SAME padding."""
# [1, 2, 2, 1]
image = [[[[1], [2]], [[3], [4]]]]
# [1, 2, 2, 4]
patches = [[[[1, 2, 3, 4], [2, 0, 4, 0]], [[3, 4, 0, 0], [4, 0, 0, 0]]]]
self._VerifyValues(
image,
ksizes=[2, 2],
strides=[1, 1],
rates=[1, 1],
padding="SAME",
patches=patches)
def testKsize2x2Stride1x1Rate2x2Valid(self):
"""Test for 2x2 kernel with 2x2 dilation."""
# [1, 2, 2, 1]
image = np.arange(16).reshape(1, 4, 4, 1).astype(np.float32)
# [1, 2, 2, 4]
patches = [[[[0, 2, 8, 10], [1, 3, 9, 11]],
[[4, 6, 12, 14], [5, 7, 13, 15]]]]
self._VerifyValues(
image,
ksizes=[2, 2],
strides=[1, 1],
rates=[2, 2],
padding="VALID",
patches=patches)
if __name__ == "__main__":
test.main()
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