wehub-resource-sync
161 lines
4.1 KiB
Python
161 lines
4.1 KiB
Python
# Copyright (c) 2021 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 dygraph_to_static_utils import (
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Dy2StTestBase,
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enable_to_static_guard,
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test_ast_only,
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)
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import paddle
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def tensor_clone(x):
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x = paddle.to_tensor(x)
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y = x.clone()
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return y
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class TestTensorClone(Dy2StTestBase):
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def _run(self):
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x = paddle.ones([1, 2, 3])
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return paddle.jit.to_static(tensor_clone)(x).numpy()
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def test_tensor_clone(self):
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with enable_to_static_guard(False):
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dygraph_res = self._run()
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static_res = self._run()
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np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-05)
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def tensor_numpy(x):
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x = paddle.to_tensor(x)
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x.clear_gradient()
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return x
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class TestTensorDygraphOnlyMethodError(Dy2StTestBase):
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def _run(self):
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x = paddle.zeros([2, 2])
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y = paddle.jit.to_static(tensor_numpy)(x)
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return y.numpy()
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@test_ast_only
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def test_to_static_numpy_report_error(self):
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with enable_to_static_guard(False):
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dygraph_res = self._run()
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with self.assertRaises(AssertionError):
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static_res = self._run()
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def tensor_item(x):
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x = paddle.to_tensor(x)
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y = x.clone()
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return y.item()
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class TestTensorItem(Dy2StTestBase):
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def _run(self):
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x = paddle.ones([1])
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return paddle.jit.to_static(tensor_item)(x)
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def test_tensor_clone(self):
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with enable_to_static_guard(False):
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dygraph_res = self._run()
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static_res = self._run()
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np.testing.assert_allclose(dygraph_res, static_res)
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def tensor_size(x):
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x = paddle.to_tensor(x)
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x = paddle.reshape(x, paddle.shape(x)) # dynamic shape
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y = x.size
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return y
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class TestTensorSize(Dy2StTestBase):
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def _run(self, to_static):
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x = paddle.ones([1, 2, 3])
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if not to_static:
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return tensor_size(x)
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ret = paddle.jit.to_static(tensor_size)(x)
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if hasattr(ret, 'numpy'):
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ret = ret.numpy()
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return ret
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def test_tensor_size(self):
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dygraph_res = self._run(to_static=False)
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static_res = self._run(to_static=True)
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np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5)
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def true_div(x, y):
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z = x / y
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return z
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class TestTrueDiv(Dy2StTestBase):
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def _run(self):
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x = paddle.to_tensor([3], dtype='int64')
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y = paddle.to_tensor([4], dtype='int64')
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return paddle.jit.to_static(true_div)(x, y).numpy()
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def test_true_div(self):
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with enable_to_static_guard(False):
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dygraph_res = self._run()
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static_res = self._run()
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np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5)
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def tensor_stride_no_dim(x):
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x = paddle.to_tensor(x)
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return x.stride()
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def tensor_stride_with_dim(x):
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x = paddle.to_tensor(x)
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return x.stride(0)
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def tensor_stride_negative_dim(x):
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x = paddle.to_tensor(x)
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return x.stride(-1)
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class TestTensorStride(Dy2StTestBase):
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def _assert_dy2st_equal(self, fn):
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x = paddle.ones([2, 3, 4])
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dygraph_res = fn(x)
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static_res = paddle.jit.to_static(fn)(x)
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np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5)
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def test_tensor_stride_no_dim(self):
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self._assert_dy2st_equal(tensor_stride_no_dim)
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def test_tensor_stride_with_dim(self):
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self._assert_dy2st_equal(tensor_stride_with_dim)
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def test_tensor_stride_negative_dim(self):
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self._assert_dy2st_equal(tensor_stride_negative_dim)
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if __name__ == '__main__':
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unittest.main()
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