forked from mindspore-Ecosystem/mindspore
128 lines
4.0 KiB
Python
128 lines
4.0 KiB
Python
# Copyright 2020 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 functools
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import numpy as np
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore import dtype as mstype
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from tests.ut.python.ut_filter import non_graph_engine
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from tests.mindspore_test_framework.mindspore_test import mindspore_test
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from tests.mindspore_test_framework.pipeline.forward.compile_forward \
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import pipeline_for_compile_forward_ge_graph_for_case_by_case_config
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context.set_context(mode=context.GRAPH_MODE)
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class TupleGraphNet(nn.Cell):
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def __init__(self):
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super(TupleGraphNet, self).__init__()
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self.conv1 = nn.Conv2d(3, 1, 3, pad_mode='same')
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self.conv2 = nn.Conv2d(3, 1, 7, pad_mode='same')
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self.conv3 = nn.Conv2d(3, 3, 3, pad_mode='same')
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self.layers = (self.conv1, self.conv2, self.conv3)
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def construct(self, x):
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return self.layers[0](x)
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class NestTupleGraphNet(nn.Cell):
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def __init__(self):
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super(NestTupleGraphNet, self).__init__()
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self.conv1 = nn.Conv2d(3, 1, 3, pad_mode='same')
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self.conv2 = nn.Conv2d(3, 1, 7, pad_mode='same')
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self.conv3 = nn.Conv2d(3, 3, 3, pad_mode='same')
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self.layers = ((self.conv1, self.conv2),
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(self.conv2, self.conv1, self.conv3))
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def construct(self, x):
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return self.layers[0][1](x)
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class InTupleNet(nn.Cell):
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def __init__(self):
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super(InTupleNet, self).__init__()
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self.tuple_ = (1, 2, 3, 4, 5, "ok")
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def construct(self, x):
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ret = x
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if 2 in self.tuple_:
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ret = x + x
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if "ok" in self.tuple_:
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ret = x - x
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return ret
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class TensorInTuple(nn.Cell):
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def __init__(self):
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super(TensorInTuple, self).__init__()
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self.t1 = Tensor(1, mstype.float32)
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self.t2 = Tensor(2, mstype.float32)
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self.tuple_ = (self.t1, self.t2)
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def construct(self, x):
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ret = x
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if self.t1 in self.tuple_:
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ret = x + x
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return ret
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class TensorNotInTuple(nn.Cell):
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def __init__(self):
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super(TensorNotInTuple, self).__init__()
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self.t1 = Tensor(1, mstype.float32)
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self.t2 = Tensor(2, mstype.float32)
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self.tuple_ = (self.t1, self.t2)
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def construct(self, x):
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ret = x
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if self.t1 not in self.tuple_:
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ret = x + x
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return ret
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test_case_ops = [
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('TupleGraph', {
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'block': TupleGraphNet(),
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'desc_inputs': [Tensor(np.ones((3, 3, 24, 24)), mstype.float32)]}),
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('NestTupleGraph', {
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'block': NestTupleGraphNet(),
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'desc_inputs': [Tensor(np.ones((3, 3, 24, 24)), mstype.float32)]}),
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('InTuple', {
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'block': InTupleNet(),
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'desc_inputs': [Tensor(np.ones((3, 3, 24, 24)), mstype.float32)]}),
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('TensorInTuple', {
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'block': TensorInTuple(),
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'desc_inputs': [Tensor(np.ones((3, 3, 24, 24)), mstype.float32)]}),
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('TensorNotInTuple', {
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'block': TensorNotInTuple(),
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'desc_inputs': [Tensor(np.ones((3, 3, 24, 24)), mstype.float32)]}),
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]
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test_case_lists = [test_case_ops]
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test_exec_case = functools.reduce(lambda x, y: x + y, test_case_lists)
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# use -k to select certain testcast
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# pytest tests/python/ops/test_ops.py::test_backward -k LayerNorm
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@non_graph_engine
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@mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config)
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def test_exec():
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context.set_context(mode=context.GRAPH_MODE)
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return test_exec_case
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