# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np from dygraph_to_static_utils import ( Dy2StTestBase, enable_to_static_guard, test_ast_only, ) import paddle def tensor_clone(x): x = paddle.to_tensor(x) y = x.clone() return y class TestTensorClone(Dy2StTestBase): def _run(self): x = paddle.ones([1, 2, 3]) return paddle.jit.to_static(tensor_clone)(x).numpy() def test_tensor_clone(self): with enable_to_static_guard(False): dygraph_res = self._run() static_res = self._run() np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-05) def tensor_numpy(x): x = paddle.to_tensor(x) x.clear_gradient() return x class TestTensorDygraphOnlyMethodError(Dy2StTestBase): def _run(self): x = paddle.zeros([2, 2]) y = paddle.jit.to_static(tensor_numpy)(x) return y.numpy() @test_ast_only def test_to_static_numpy_report_error(self): with enable_to_static_guard(False): dygraph_res = self._run() with self.assertRaises(AssertionError): static_res = self._run() def tensor_item(x): x = paddle.to_tensor(x) y = x.clone() return y.item() class TestTensorItem(Dy2StTestBase): def _run(self): x = paddle.ones([1]) return paddle.jit.to_static(tensor_item)(x) def test_tensor_clone(self): with enable_to_static_guard(False): dygraph_res = self._run() static_res = self._run() np.testing.assert_allclose(dygraph_res, static_res) def tensor_size(x): x = paddle.to_tensor(x) x = paddle.reshape(x, paddle.shape(x)) # dynamic shape y = x.size return y class TestTensorSize(Dy2StTestBase): def _run(self, to_static): x = paddle.ones([1, 2, 3]) if not to_static: return tensor_size(x) ret = paddle.jit.to_static(tensor_size)(x) if hasattr(ret, 'numpy'): ret = ret.numpy() return ret def test_tensor_size(self): dygraph_res = self._run(to_static=False) static_res = self._run(to_static=True) np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5) def true_div(x, y): z = x / y return z class TestTrueDiv(Dy2StTestBase): def _run(self): x = paddle.to_tensor([3], dtype='int64') y = paddle.to_tensor([4], dtype='int64') return paddle.jit.to_static(true_div)(x, y).numpy() def test_true_div(self): with enable_to_static_guard(False): dygraph_res = self._run() static_res = self._run() np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5) def tensor_stride_no_dim(x): x = paddle.to_tensor(x) return x.stride() def tensor_stride_with_dim(x): x = paddle.to_tensor(x) return x.stride(0) def tensor_stride_negative_dim(x): x = paddle.to_tensor(x) return x.stride(-1) class TestTensorStride(Dy2StTestBase): def _assert_dy2st_equal(self, fn): x = paddle.ones([2, 3, 4]) dygraph_res = fn(x) static_res = paddle.jit.to_static(fn)(x) np.testing.assert_allclose(dygraph_res, static_res, rtol=1e-5) def test_tensor_stride_no_dim(self): self._assert_dy2st_equal(tensor_stride_no_dim) def test_tensor_stride_with_dim(self): self._assert_dy2st_equal(tensor_stride_with_dim) def test_tensor_stride_negative_dim(self): self._assert_dy2st_equal(tensor_stride_negative_dim) if __name__ == '__main__': unittest.main()