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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.
# ==============================================================================
"""Tests for xla.reduce_window."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.compiler.tests import xla_test
from tensorflow.compiler.tf2xla.python import xla
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import function
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import googletest
class ReduceWindowTest(xla_test.XLATestCase):
"""Test cases for xla.reduce_window."""
def _reduce_window(self, operand, init, reducer, **kwargs):
with self.cached_session():
placeholder = array_ops.placeholder(operand.dtype)
with self.test_scope():
output = xla.reduce_window(placeholder, init, reducer, **kwargs)
return output.eval(feed_dict={placeholder: operand})
def testReduceWindow(self):
# TODO(b/77644762): float16 and float64 ReduceWindow are unimplemented.
for dtype in set(self.numeric_types).intersection(
set([dtypes.bfloat16.as_numpy_dtype, np.float32])):
@function.Defun(dtype, dtype)
def sum_reducer(x, y):
return x + y
@function.Defun(dtype, dtype)
def mul_reducer(x, y):
return x * y
self.assertAllClose(
np.array([3, 5, 7, 9, 11, 13], dtype=dtype),
self._reduce_window(
np.array([1, 2, 3, 4, 5, 6, 7], dtype=dtype),
0.0,
sum_reducer,
window_dimensions=[2]))
self.assertAllClose(
np.array([3, 7, 11], dtype=dtype),
self._reduce_window(
np.array([1, 2, 3, 4, 5, 6, 7], dtype=dtype),
0.0,
sum_reducer,
window_dimensions=[2],
window_strides=[2]))
self.assertAllClose(
np.array([1, 4, 7], dtype=dtype),
self._reduce_window(
np.array([1, 2, 3, 4, 5, 6, 7], dtype=dtype),
0.0,
sum_reducer,
window_dimensions=[1],
window_strides=[3]))
self.assertAllClose(
np.array([[24, 36, 24], [96, 0, 0]], dtype=dtype),
self._reduce_window(
np.array([[1, 2, 3, 4], [4, 3, 2, 1], [2, 4, 0, 1]], dtype=dtype),
1.0,
mul_reducer,
window_dimensions=[2, 2],
window_strides=[1, 1]))
self.assertAllClose(
np.array([[0, 0, 0], [5, 10, 5], [2, 4, 1], [0, 0, 0]], dtype=dtype),
self._reduce_window(
np.array([[1, 2, 3, 4], [4, 3, 2, 1], [2, 4, 0, 1]], dtype=dtype),
0.0,
sum_reducer,
window_dimensions=[2, 2],
window_strides=[2, 2],
padding=[[2, 3], [1, 2]]))
if __name__ == '__main__':
googletest.main()
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