wehub-resource-sync
98 lines
3.4 KiB
Python
98 lines
3.4 KiB
Python
# Copyright (c) 2025 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 utils import static_guard
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import paddle
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class TestPirTensor(unittest.TestCase):
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def test_element_size(self):
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with static_guard():
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x = paddle.to_tensor(1, dtype="bool")
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self.assertEqual(x.itemsize, 1)
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x = paddle.to_tensor(1, dtype="float16")
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self.assertEqual(x.itemsize, 2)
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x = paddle.to_tensor(1, dtype="float32")
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self.assertEqual(x.itemsize, 4)
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x = paddle.to_tensor(1, dtype="float64")
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self.assertEqual(x.itemsize, 8)
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x = paddle.to_tensor(1, dtype="int8")
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self.assertEqual(x.itemsize, 1)
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x = paddle.to_tensor(1, dtype="int16")
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self.assertEqual(x.itemsize, 2)
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x = paddle.to_tensor(1, dtype="int32")
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self.assertEqual(x.itemsize, 4)
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x = paddle.to_tensor(1, dtype="int64")
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self.assertEqual(x.itemsize, 8)
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x = paddle.to_tensor(1, dtype="uint8")
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self.assertEqual(x.itemsize, 1)
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x = paddle.to_tensor(1, dtype="complex64")
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self.assertEqual(x.itemsize, 8)
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x = paddle.to_tensor(1, dtype="complex128")
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self.assertEqual(x.itemsize, 16)
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class TestPirTensorNelement(unittest.TestCase):
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def test_nelement(self):
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paddle.enable_static()
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.base.program_guard(main, startup):
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x = paddle.assign(np.random.rand(2, 8, 4).astype("float32"))
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exe = paddle.base.Executor(paddle.CPUPlace())
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fetches = exe.run(main, fetch_list=[x.nelement()])
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self.assertEqual(fetches[0], np.prod((2, 8, 4)))
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class TestPirTensorNbytes(unittest.TestCase):
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def test_nbytes(self):
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paddle.enable_static()
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.base.program_guard(main, startup):
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x = paddle.assign(np.random.rand(2, 8, 4).astype("float32"))
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exe = paddle.base.Executor(paddle.CPUPlace())
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fetches = exe.run(main, fetch_list=[x.nbytes])
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self.assertEqual(fetches[0], 2 * 8 * 4 * 4)
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def test_sparse_coo_error(self):
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paddle.enable_static()
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.base.program_guard(main, startup):
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indices = paddle.assign([[0, 1, 2], [1, 0, 2]])
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values = paddle.assign([1.0, 2.0, 3.0])
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x = paddle.sparse.sparse_coo_tensor(indices, values, [3, 3])
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exe = paddle.base.Executor(paddle.CPUPlace())
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with self.assertRaises(RuntimeError):
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fetches = exe.run(main, fetch_list=[x.nbytes])
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if __name__ == '__main__':
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unittest.main()
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