forked from mindspore-Ecosystem/mindspore
84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
# Copyright 2021-2022 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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import pytest
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import numpy as np
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from mindspore.ops import composite as C
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from mindspore.ops import functional as F
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from mindspore import Parameter
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from mindspore import Tensor
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from mindspore import context
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import mindspore.common.dtype as mstype
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import mindspore.nn as nn
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class Net(nn.Cell):
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def construct(self, x, y):
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while x < y:
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x = x * x + 1
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return x
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class GradNet(nn.Cell):
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def __init__(self, net):
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super().__init__()
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self.net = net
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self.grad_op = C.GradOperation(get_all=True)
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def construct(self, x, y):
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gradient_function = self.grad_op(self.net)
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return gradient_function(x, y)
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@pytest.mark.level1
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_while_grad():
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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x = Tensor([2.0], dtype=mstype.float32)
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y = Tensor([2.0], dtype=mstype.float32)
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GradNet(Net())(x, y)
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class WhileSpecTwiceNet(nn.Cell):
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def __init__(self):
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super().__init__()
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self.w = Parameter(Tensor([(- 3)], mstype.float32), name='w')
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self.b = Parameter(Tensor([(- 2)], mstype.float32), name='b')
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def construct(self, x, y):
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x = self.b
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while y > x:
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x = y + 2
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return y
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_while_header_spec_twice():
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"""
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Feature: FuncGraph Cloner.
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Description: While header will be specialized to 2 graphs, because common call header is RefTensor but body call
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header is Tensor.Related issue:I5HVPJ.
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Expectation: No error raised.
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"""
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x = Tensor(np.array([3], np.float32))
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y = Tensor(np.array([1], np.float32))
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net = WhileSpecTwiceNet()
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grad_net = F.grad(net, grad_position=(0, 1))
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fgrad = grad_net(x, y)
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print('ms backward: ', fgrad)
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