wehub-resource-sync
70 lines
2.5 KiB
Python
70 lines
2.5 KiB
Python
# Copyright (c) 2022 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 is_custom_device
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import paddle
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from paddle.base import core
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class TestTensorCopyFrom(unittest.TestCase):
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def test_main(self):
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if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
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place = paddle.CPUPlace()
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np_value = np.random.random(size=[10, 30]).astype('float32')
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tensor = paddle.to_tensor(np_value, place=place)
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tensor._uva()
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self.assertTrue(tensor.place.is_gpu_place())
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class TestUVATensorFromNumpy(unittest.TestCase):
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def test_uva_tensor_creation(self):
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if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
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dtype_list = [
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"int32",
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"int64",
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"float32",
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"float64",
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"float16",
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"int8",
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"int16",
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"bool",
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]
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for dtype in dtype_list:
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data = np.random.randint(10, size=[4, 5]).astype(dtype)
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tensor = core.eager.to_uva_tensor(data, 0)
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tensor2 = core.eager.to_uva_tensor(data)
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self.assertTrue(tensor.place.is_gpu_place())
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self.assertTrue(tensor2.place.is_gpu_place())
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np.testing.assert_allclose(tensor.numpy(), data, rtol=1e-05)
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np.testing.assert_allclose(tensor2.numpy(), data, rtol=1e-05)
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def test_uva_tensor_correctness(self):
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if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
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a = np.arange(0, 100, dtype="int32")
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a = a.reshape([10, 10])
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slice_a = a[:, 5]
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tensor1 = paddle.to_tensor(slice_a)
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tensor2 = core.eager.to_uva_tensor(slice_a)
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np.testing.assert_allclose(
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tensor1.numpy(), tensor2.numpy(), rtol=1e-05
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)
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if __name__ == "__main__":
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unittest.main()
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