forked from huawei/mindspore2022
83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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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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# ============================================================================
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"""test jvp in graph mode"""
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import numpy as np
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import pytest
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import mindspore.nn as nn
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import mindspore.context as context
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from mindspore import Tensor
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from mindspore.nn.grad import Vjp
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context.set_context(mode=context.GRAPH_MODE)
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class SingleInputNet(nn.Cell):
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def construct(self, x):
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return x**3
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class MultipleInputsOutputNet(nn.Cell):
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def construct(self, x, y):
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return 2*x, y**3
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def test_vjp_single_input_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = SingleInputNet()
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Vjp(net)(x, v)
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def test_vjp_multiple_inputs_default_v_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = MultipleInputsOutputNet()
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Vjp(net)(x, y, (v, v))
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def test_vjp_wrong_input_v_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = SingleInputNet()
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with pytest.raises(TypeError):
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Vjp(net)(x, (v, v))
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def test_vjp_wrong_input_v_2_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = SingleInputNet()
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with pytest.raises(TypeError):
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Vjp(net)(x, (v,))
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def test_vjp_wrong_input_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = SingleInputNet()
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with pytest.raises(TypeError):
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Vjp(net)(x, y, v)
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def test_vjp_wrong_input_2_graph():
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x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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net = MultipleInputsOutputNet()
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with pytest.raises(TypeError):
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Vjp(net)((x, y), (v, v))
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