wehub-resource-sync
88 lines
3.3 KiB
Python
Executable File
88 lines
3.3 KiB
Python
Executable File
# 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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import unittest
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import numpy as np
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from op_test import get_device_place, is_custom_device
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import paddle
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from paddle import base
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class TestIncrement(unittest.TestCase):
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def test_api(self):
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paddle.enable_static()
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with base.program_guard(base.Program(), base.Program()):
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input = paddle.tensor.fill_constant(
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shape=[1], dtype='int64', value=5
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)
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expected_result = np.array([8], dtype='int64')
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output = paddle.tensor.math.increment(input, value=3)
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exe = base.Executor(base.CPUPlace())
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result = exe.run(fetch_list=[output])
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self.assertEqual((result == expected_result).all(), True)
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with base.dygraph.guard():
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input = paddle.ones(shape=[1], dtype='int64')
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expected_result = np.array([2], dtype='int64')
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output = paddle.tensor.math.increment(input, value=1)
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self.assertEqual((output.numpy() == expected_result).all(), True)
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def test_no_inplace_increment(self):
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with (
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paddle.pir_utils.IrGuard(),
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base.program_guard(base.Program(), base.Program()),
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):
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x = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=1)
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x.stop_gradient = False
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input = paddle._pir_ops.increment(x, 1.0)
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input = paddle._pir_ops.increment(input, 1.0)
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input = paddle._pir_ops.increment(input, 1.0)
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out = paddle._pir_ops.increment(input, 1.0)
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dx = paddle.base.gradients(out, x)
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exe = base.Executor(base.CPUPlace())
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result = exe.run(fetch_list=[out, dx])
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self.assertEqual(result[0], 5.0)
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self.assertEqual(result[1], 1.0)
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class TestInplaceApiWithDataTransform(unittest.TestCase):
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def test_increment(self):
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if base.core.is_compiled_with_cuda() or is_custom_device():
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paddle.enable_static()
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with paddle.base.device_guard("gpu:0"):
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x = paddle.tensor.fill_constant([1], "float32", 0)
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with paddle.base.device_guard("cpu"):
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x = paddle.increment(x)
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exe = paddle.static.Executor(get_device_place())
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(a,) = exe.run(paddle.static.default_main_program(), fetch_list=[x])
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paddle.disable_static()
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self.assertEqual(a[0], 1)
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class TestIncrement_ZeroSize(unittest.TestCase):
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def test_api(self):
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with base.dygraph.guard():
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input = paddle.randn(shape=[0]).astype('int64')
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expected_result = np.random.random([0]).astype('int64')
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output = paddle.tensor.math.increment(input, value=1)
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self.assertEqual((output.numpy() == expected_result).all(), True)
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if __name__ == "__main__":
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unittest.main()
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