| # 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.""" |
| |
| 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.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() |