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133 lines
5.5 KiB
133 lines
5.5 KiB
# Copyright (c) 2020 PaddlePaddle 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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from __future__ import print_function
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import paddle
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import unittest
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import numpy as np
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class TestProdOp(unittest.TestCase):
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def setUp(self):
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self.input = np.random.random(size=(10, 10, 5)).astype(np.float32)
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def run_imperative(self):
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input = paddle.to_tensor(self.input)
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dy_result = paddle.prod(input)
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expected_result = np.prod(self.input)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=1)
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expected_result = np.prod(self.input, axis=1)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=-1)
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expected_result = np.prod(self.input, axis=-1)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=[0, 1])
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expected_result = np.prod(self.input, axis=(0, 1))
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=1, keepdim=True)
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expected_result = np.prod(self.input, axis=1, keepdims=True)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=1, dtype='int64')
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expected_result = np.prod(self.input, axis=1, dtype=np.int64)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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dy_result = paddle.prod(input, axis=1, keepdim=True, dtype='int64')
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expected_result = np.prod(
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self.input, axis=1, keepdims=True, dtype=np.int64)
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self.assertTrue(np.allclose(dy_result.numpy(), expected_result))
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def run_static(self, use_gpu=False):
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input = paddle.fluid.data(name='input', shape=[10, 10, 5], dtype='float32')
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result0 = paddle.prod(input)
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result1 = paddle.prod(input, axis=1)
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result2 = paddle.prod(input, axis=-1)
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result3 = paddle.prod(input, axis=[0, 1])
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result4 = paddle.prod(input, axis=1, keepdim=True)
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result5 = paddle.prod(input, axis=1, dtype='int64')
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result6 = paddle.prod(input, axis=1, keepdim=True, dtype='int64')
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place = paddle.CUDAPlace(0) if use_gpu else paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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static_result = exe.run(feed={"input": self.input},
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fetch_list=[
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result0, result1, result2, result3, result4,
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result5, result6
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])
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expected_result = np.prod(self.input)
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self.assertTrue(np.allclose(static_result[0], expected_result))
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expected_result = np.prod(self.input, axis=1)
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self.assertTrue(np.allclose(static_result[1], expected_result))
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expected_result = np.prod(self.input, axis=-1)
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self.assertTrue(np.allclose(static_result[2], expected_result))
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expected_result = np.prod(self.input, axis=(0, 1))
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self.assertTrue(np.allclose(static_result[3], expected_result))
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expected_result = np.prod(self.input, axis=1, keepdims=True)
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self.assertTrue(np.allclose(static_result[4], expected_result))
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expected_result = np.prod(self.input, axis=1, dtype=np.int64)
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self.assertTrue(np.allclose(static_result[5], expected_result))
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expected_result = np.prod(
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self.input, axis=1, keepdims=True, dtype=np.int64)
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self.assertTrue(np.allclose(static_result[6], expected_result))
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def test_cpu(self):
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paddle.disable_static(place=paddle.CPUPlace())
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self.run_imperative()
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paddle.enable_static()
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with paddle.static.program_guard(paddle.static.Program()):
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self.run_static()
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def test_gpu(self):
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if not paddle.fluid.core.is_compiled_with_cuda():
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return
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paddle.disable_static(place=paddle.CUDAPlace(0))
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self.run_imperative()
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paddle.enable_static()
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with paddle.static.program_guard(paddle.static.Program()):
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self.run_static(use_gpu=True)
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class TestProdOpError(unittest.TestCase):
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def test_error(self):
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with paddle.static.program_guard(paddle.static.Program(),
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paddle.static.Program()):
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x = paddle.fluid.data(name='x', shape=[2, 2, 4], dtype='float32')
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bool_x = paddle.fluid.data(name='bool_x', shape=[2, 2, 4], dtype='bool')
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# The argument x shoule be a Tensor
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self.assertRaises(TypeError, paddle.prod, [1])
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# The data type of x should be float32, float64, int32, int64
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self.assertRaises(TypeError, paddle.prod, bool_x)
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# The argument axis's type shoule be int ,list or tuple
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self.assertRaises(TypeError, paddle.prod, x, 1.5)
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# The argument dtype of prod_op should be float32, float64, int32 or int64.
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self.assertRaises(TypeError, paddle.prod, x, 'bool')
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if __name__ == "__main__":
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unittest.main()
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