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