forked from mindspore-Ecosystem/mindspore
399 lines
12 KiB
Python
399 lines
12 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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import sys
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import pytest
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from mindspore import Tensor, context, Parameter
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from mindspore.ops import operations as P
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from mindspore.ops import functional as F
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from mindspore.nn import Cell
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import mindspore as ms
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def test_inner_scalar_divisor():
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"""
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Feature: Check whether the divisor of inner scalar is zero.
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Description: The divisor of inner scalar must not be zero.
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Expectation: The divisor of inner scalar must not be zero.
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"""
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class Net(Cell):
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def __init__(self):
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super().__init__()
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self.param_a = Parameter(Tensor(5, ms.int32), name="param_a")
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self.param_b = Parameter(Tensor(5, ms.int32), name="param_b")
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def construct(self, x):
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return x + self.param_a + 5 / 0
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context.set_context(device_target="GPU")
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x = Tensor(2, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="The divisor could not be zero."):
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ret = net(x)
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print("ret:", ret)
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def test_inner_scalar_mod():
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"""
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Feature: Check the input of inner scalar mod.
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Description: The input of inner scalar mod must not be zero.
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Expectation: The input of inner scalar mod must not be zero.
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"""
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class Net(Cell):
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def __init__(self):
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super().__init__()
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self.param_a = Parameter(Tensor(5, ms.int32), name="param_a")
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def construct(self, x):
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return x + self.param_a + 5 % 0
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x = Tensor(2, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="Cannot perform modulo operation on zero."):
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ret = net(x)
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print("ret:", ret)
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def test_inner_scalar_mod_args_length():
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"""
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Feature: Check the length of input of inner scalar mod.
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Description: The length of input of inner scalar mod should not less than 2.
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Expectation: The length of input of inner scalar mod should not less than 2.
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"""
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class Net(Cell):
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def __init__(self):
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super().__init__()
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self.param_a = Parameter(Tensor(5, ms.int32), name="param_a")
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self.mod = P.Mod()
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def construct(self, x):
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return x + self.param_a + self.mod(5)
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x = Tensor(2, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'S-Prim-Mod', the size of input should be 2"):
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ret = net(x)
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print("ret:", ret)
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def test_make_range_input_is_empty():
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"""
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Feature: Check the length of inputs of make_range operator.
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Description: The inputs of make_range operator could not be empty.
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Expectation: The inputs of make_range operator could not be empty.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range():
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'range', the arguments could not be empty."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_step_zero():
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"""
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Feature: Check the length of inputs of make_range operator.
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Description: The step value of MakeRange operator could not be 0.
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Expectation: The step value of MakeRange operator could not be 0.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(1, 2, 0):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'range', the argument 'step' could not be 0."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_error_input_1():
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"""
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Feature: Check the inputs of make_range operator.
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Description: If start > stop, the step need smaller than zero.
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Expectation: If start > stop, the step need smaller than zero.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(1, -1, 3):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'range', while the argument 'start'"):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_error_input_2():
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"""
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Feature: Check the length of inputs of make_range operator.
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Description: If start < stop, the step need greater than zero.
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Expectation: If start < stop, the step need greater than zero.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(-1, 1, -3):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'range', while the argument 'start'"):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_input_type():
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"""
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Feature: Check the type of inputs of make_range operator.
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Description: The type of inputs of make_range operator must be int64.
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Expectation: The type of inputs of make_range operator must be int64.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(0, 0.02):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="The type of inputs in range operator only support int64 number."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_input_type_2():
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"""
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Feature: Check the type of inputs of make_range operator.
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Description: The type of inputs of make_range operator must be int64.
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Expectation: The type of inputs of make_range operator must be int64.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(0, 1, 3.00):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="The type of inputs in range operator only support int64 number."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_input_type_3():
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"""
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Feature: Check the type of inputs of make_range operator.
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Description: The type of inputs of make_range operator must be int64.
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Expectation: The type of inputs of make_range operator must be int64.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(3.00):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="The type of inputs in range operator only support int64 number."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_input_size():
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"""
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Feature: Check the size of inputs of make_range operator.
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Description: The size of inputs of make_range operator could not exceed 3.
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Expectation: The size of inputs of make_range operator could not exceed 3.
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"""
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class Net(Cell):
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def construct(self, x, y):
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for _ in range(1, 2, 3, 4):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="For 'range', the size of arguments could not exceed 3."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_overflow():
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"""
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Feature: Check the size of inputs of range operator.
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Description: The size of inputs of make_range operator could not exceed 3.
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Expectation: The size of inputs of make_range operator could not exceed 3.
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"""
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class Net(Cell):
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def construct(self, x, y):
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max_index = sys.maxsize
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for _ in range(max_index - 1, max_index, 3):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="Integer overflow error occurred when traversing the range."):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_range_overflow_2():
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"""
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Feature: Check the size of inputs of make_range operator.
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Description: The size of inputs of make_range operator could not exceed 3.
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Expectation: The size of inputs of make_range operator could not exceed 3.
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"""
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class Net(Cell):
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def construct(self, x, y):
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min_index = -sys.maxsize
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for _ in range(min_index, min_index - 1, -3):
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x += y
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return x
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x = Tensor(2, dtype=ms.int32)
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y = Tensor(4, dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="Integer overflow error occurred when traversing the range."):
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ret = net(x, y)
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print("ret:", ret)
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def test_typeof():
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"""
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Feature: Check the size of inputs of typeof operator.
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Description: The size of inputs of typeof operator must be 1.
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Expectation: The size of inputs of typeof operator must be 1.
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"""
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class Net(Cell):
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def construct(self, x):
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return F.typeof(x, x)
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x = Tensor([2, 3, 4, 5], dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="The Typeof operator must requires 1 argument, "
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"but the size of arguments is 2."):
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ret = net(x)
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print("ret:", ret)
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def test_tuple_div():
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"""
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Feature: Check the size of inputs of tuple_div operator.
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Description: The size of inputs of tuple_div operator must be same.
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Expectation: The size of inputs of tuple_div operator must be same.
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"""
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class Net(Cell):
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def construct(self, x, y):
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return F.tuple_div(x, y)
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x = (8, 14, 20)
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y = (2, 2)
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net = Net()
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with pytest.raises(Exception, match="The size of inputs of 'tuple_div' operator must be the same"):
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ret = net(x, y)
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print("ret:", ret)
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def test_tuple_div_type():
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"""
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Feature: Check the size of inputs of tuple_div operator.
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Description: The type of inputs of tuple_div operator must be int64 number.
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Expectation: The type of inputs of tuple_div operator must be int64 number.
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"""
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class Net(Cell):
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def construct(self, x, y):
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return F.tuple_div(x, y)
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x = (8, 14, 20)
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y = (2, 2, 2.0)
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net = Net()
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with pytest.raises(Exception, match="The data type of inputs of 'tuple_div' operator should be an int64 number,"):
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ret = net(x, y)
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print("ret:", ret)
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def test_tuple_div_zero():
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"""
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Feature: Check the size of inputs of tuple_div operator.
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Description: The divisor value should not be 0.
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Expectation: The divisor value should not be 0.
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"""
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class Net(Cell):
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def construct(self, x, y):
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return F.tuple_div(x, y)
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x = (8, 14, 20)
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y = (2, 2, 0)
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net = Net()
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with pytest.raises(Exception, match="The divisor value should not be 0"):
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ret = net(x, y)
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print("ret:", ret)
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def test_tuple_div_input_is_not_divisible():
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"""
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Feature: Check whether the inputs of tuple_div is divisible.
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Description: The inputs of tuple_div could be divisible.
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Expectation: The inputs of tuple_div could be divisible.
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"""
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class Net(Cell):
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def construct(self, x, y):
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return F.tuple_div(x, y)
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x = (8, 14)
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y = (2, 3)
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net = Net()
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with pytest.raises(Exception, match="The inputs of 'tuple_div' operator should be divisible,"):
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ret = net(x, y)
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print("ret:", ret)
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def test_make_slice_scalar():
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"""
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Feature: Check whether the scalar input of make_slice is int or bool.
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Description: The scalar input of make_slice is int or bool.
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Expectation: The scalar input of make_slice is int or bool.
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"""
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class Net(Cell):
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def construct(self, data):
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return data[1.01:None:None]
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x = Tensor((8, 10, 12), dtype=ms.int32)
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net = Net()
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with pytest.raises(Exception, match="Slice indices must be integers or bool."):
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ret = net(x)
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print("ret:", ret)
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