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141 lines
4.8 KiB
141 lines
4.8 KiB
# 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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""" test_tensor_slice """
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import numpy as np
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import pytest
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from mindspore import Tensor
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from mindspore import context
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from mindspore.nn import Cell
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from ....mindspore_test_framework.mindspore_test import mindspore_test
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from ....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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class NetWorkSlicePositive(Cell):
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def __init__(self):
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super(NetWorkSlicePositive, self).__init__()
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self.tensor_ret0 = Tensor(np.ones([1, 2, 2], np.int32))
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self.tensor_ret1 = Tensor(np.ones([4, 7, 4], np.int32))
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self.tensor_ret2 = Tensor(np.ones([6, 8, 10], np.int32))
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self.tensor_ret3 = Tensor(np.ones([3, 8, 10], np.int32))
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def construct(self, tensor):
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ret0 = tensor[3:4:3, 1:5:2, 3:6:2] + self.tensor_ret0
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ret1 = tensor[-6:4:1, 7:-8:-1, ::3] + self.tensor_ret1
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ret2 = tensor[::, ::, ::] + self.tensor_ret2
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ret3 = tensor[::2] + self.tensor_ret3
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return ret0, ret1, ret2, ret3
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class NetWorkReduceDimension(Cell):
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def __init__(self):
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super(NetWorkReduceDimension, self).__init__()
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self.tensor_ret0 = Tensor(np.ones([2, 4, 1], np.int32))
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self.tensor_ret1 = Tensor(np.ones([3, 4], np.int32))
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self.tensor_ret2 = Tensor(np.ones([6, 8], np.int32))
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self.tensor_ret3 = Tensor(np.array(8, np.int32))
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self.tensor_ret4 = Tensor(np.ones([8, 10], np.int32))
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def construct(self, tensor):
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ret0 = tensor[0:6:3, 1:5:1, 3:5:2] + self.tensor_ret0
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ret1 = tensor[::2, 1, ::3] + self.tensor_ret1
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ret2 = tensor[::, ::, 0] + self.tensor_ret2
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ret3 = tensor[3, 2, 5] + self.tensor_ret3
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ret4 = tensor[1] + self.tensor_ret4
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return ret0, ret1, ret2, ret3, ret4
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class NetWorkStepNegative(Cell):
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def __init__(self):
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super(NetWorkStepNegative, self).__init__()
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self.tensor_ret = Tensor(np.ones([6, 5, 10], np.int32))
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def construct(self, tensor):
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ret = tensor[::1, -5::, ::-1] + self.tensor_ret
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return ret
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class NetWorkReduceToScalar(Cell):
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def __init__(self):
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super(NetWorkReduceToScalar, self).__init__()
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self.tensor_ret = Tensor(np.array(9, np.int32))
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def construct(self, tensor):
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ret = tensor[2, 3, 4] + self.tensor_ret
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return ret
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test_cases = [
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('SlicePositive', {
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'block': NetWorkSlicePositive(),
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'desc_inputs': [Tensor(np.ones([6, 8, 10], np.int32))],
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}),
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('SliceReduceDimension', {
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'block': NetWorkReduceDimension(),
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'desc_inputs': [Tensor(np.ones([6, 8, 10], np.int32))],
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}),
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('SliceNegative', {
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'block': NetWorkStepNegative(),
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'desc_inputs': [Tensor(np.ones([6, 8, 10], np.int32))],
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}),
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('SliceReduceToScalar', {
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'block': NetWorkReduceToScalar(),
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'desc_inputs': [Tensor(np.ones([6, 8, 10], np.int32))],
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}),
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]
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@mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config)
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def test_compile():
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context.set_context(mode=context.GRAPH_MODE)
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return test_cases
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def test_tensor_slice_reduce_out_of_bounds_neg():
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class NetWork(Cell):
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def __init__(self):
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super(NetWork, self).__init__()
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self.tensor_ret = Tensor(np.array(9, np.int32))
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def construct(self, tensor):
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ret = tensor[-7, 3, 4]
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return ret
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input_tensor = Tensor(np.ones([6, 8, 10], np.int32))
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net = NetWork()
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with pytest.raises(ValueError) as ex:
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net(input_tensor)
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assert "The `begin[0]` should be an int and must greater or equal to -6, but got -7" in str(ex.value)
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def test_tensor_slice_reduce_out_of_bounds_positive():
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class NetWork(Cell):
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def __init__(self):
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super(NetWork, self).__init__()
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self.tensor_ret = Tensor(np.array(9, np.int32))
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def construct(self, tensor):
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ret = tensor[6, 3, 4]
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return ret
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input_tensor = Tensor(np.ones([6, 8, 10], np.int32))
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net = NetWork()
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with pytest.raises(ValueError) as ex:
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net(input_tensor)
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assert "The `begin[0]` should be an int and must less than 6, but got 6" in str(ex.value)
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