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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.
# ==============================================================================
"""Functional tests for ExtractVolumePatches 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 ExtractVolumePatches(test.TestCase):
"""Functional tests for ExtractVolumePatches op."""
def _VerifyValues(self, image, ksizes, strides, padding, patches):
"""Tests input-output pairs for the ExtractVolumePatches op.
Args:
image: Input tensor with shape:
[batch, in_planes, in_rows, in_cols, depth].
ksizes: Patch size specified as: [ksize_planes, ksize_rows, ksize_cols].
strides: Output strides, specified as:
[stride_planes, stride_rows, stride_cols].
padding: Padding type.
patches: Expected output.
Note:
rates are not supported as of now.
"""
ksizes = [1] + ksizes + [1]
strides = [1] + strides + [1]
with self.test_session(use_gpu=True):
out_tensor = array_ops.extract_volume_patches(
constant_op.constant(image),
ksizes=ksizes,
strides=strides,
padding=padding,
name="im2col_3d")
self.assertAllClose(patches, out_tensor.eval())
# pylint: disable=bad-whitespace
def testKsize1x1x1Stride1x1x1(self):
"""Verifies that for 1x1x1 kernel the output equals the input."""
image = np.arange(2 * 3 * 4 * 5 * 6).reshape([2, 3, 4, 5, 6]) + 1
patches = image
for padding in ["VALID", "SAME"]:
self._VerifyValues(
image,
ksizes=[1, 1, 1],
strides=[1, 1, 1],
padding=padding,
patches=patches)
def testKsize1x1x1Stride2x3x4(self):
"""Test for 1x1x1 kernel and strides."""
image = np.arange(6 * 2 * 4 * 5 * 3).reshape([6, 2, 4, 5, 3]) + 1
patches = image[:, ::2, ::3, ::4, :]
for padding in ["VALID", "SAME"]:
self._VerifyValues(
image,
ksizes=[1, 1, 1],
strides=[2, 3, 4],
padding=padding,
patches=patches)
def testKsize1x1x2Stride2x2x3(self):
"""Test for 1x1x2 kernel and strides."""
image = np.arange(45).reshape([1, 3, 3, 5, 1]) + 1
patches = np.array([[[[[ 1, 2],
[ 4, 5]],
[[11, 12],
[14, 15]]],
[[[31, 32],
[34, 35]],
[[41, 42],
[44, 45]]]]])
for padding in ["VALID", "SAME"]:
self._VerifyValues(
image,
ksizes=[1, 1, 2],
strides=[2, 2, 3],
padding=padding,
patches=patches)
def testKsize2x2x2Stride1x1x1Valid(self):
"""Test for 2x2x2 kernel with VALID padding."""
image = np.arange(8).reshape([1, 2, 2, 2, 1]) + 1
patches = np.array([[[[[1, 2, 3, 4, 5, 6, 7, 8]]]]])
self._VerifyValues(
image,
ksizes=[2, 2, 2],
strides=[1, 1, 1],
padding="VALID",
patches=patches)
def testKsize2x2x2Stride1x1x1Same(self):
"""Test for 2x2x2 kernel with SAME padding."""
image = np.arange(8).reshape([1, 2, 2, 2, 1]) + 1
patches = np.array([[[[[1, 2, 3, 4, 5, 6, 7, 8],
[2, 0, 4, 0, 6, 0, 8, 0]],
[[3, 4, 0, 0, 7, 8, 0, 0],
[4, 0, 0, 0, 8, 0, 0, 0]]],
[[[5, 6, 7, 8, 0, 0, 0, 0],
[6, 0, 8, 0, 0, 0, 0, 0]],
[[7, 8, 0, 0, 0, 0, 0, 0],
[8, 0, 0, 0, 0, 0, 0, 0]]]]])
self._VerifyValues(
image,
ksizes=[2, 2, 2],
strides=[1, 1, 1],
padding="SAME",
patches=patches)
if __name__ == "__main__":
test.main()
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