forked from mindspore-Ecosystem/mindspore
1150 lines
31 KiB
Python
1150 lines
31 KiB
Python
# Copyright 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 mindspore.context as context
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from mindspore import Tensor, jit
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from mindspore.common import dtype as mstype, Parameter
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from mindspore.nn import Cell
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import pytest
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def setup_module():
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context.set_context(mode=context.GRAPH_MODE)
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def test_while_return_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in while loop requires that the after-if func graph should not
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be called.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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if y > 0:
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return bias
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x = x - 1
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y = y + 1
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_else_break_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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if y > 0:
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return bias
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break
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_else_return_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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if y > 0:
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return bias
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return x
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_break_else_return_in_while_in_else_take_break():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: take the break branch, success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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if y > 0:
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break
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return x
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_break_else_return_in_while_in_else_take_return():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: take the return branch, success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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if y < 0:
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break
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return x
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([4], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_while_return_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through outer while to
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the else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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while x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_in_while_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through outer while to
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the outer else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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while x > 0:
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if y > 0:
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return bias
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x = x - 1
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y = y + 1
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_else_return_in_while_in_while_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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while x > 0:
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if y > 0:
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return bias
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return x
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_while_return_after_if_else_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part. The inner if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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if x > y:
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x = x + y
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else:
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x = x - y
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while x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_else_after_while_return_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part. The inner if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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return bias
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if x > y:
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x = x + y
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else:
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x = x - y
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_after_if_else_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner second if requires that the after-if func graph should not
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be called, and this information should be propagated through if to
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the outer else part. The inner first if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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if x > y:
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x = x + y
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else:
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x = x - y
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if x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_else_after_if_return_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner second if requires that the after-if func graph should not
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be called, and this information should be propagated through if to
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the outer else part. The inner second if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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if x > 0:
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return bias
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if x > y:
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x = x + y
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else:
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x = x - y
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_while_return_in_else_after_if_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part. The first if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if x > y:
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x = x + y
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else:
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x = x - y
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if bias > y:
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y = x + y
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else:
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while x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_else_after_by_while_return_in_else():
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"""
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Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
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the outer else part. The second if/else can be transformed.
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Expectation: success
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"""
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@jit
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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while x > 0:
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return bias
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if x > y:
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x = x + y
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else:
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x = x - y
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_return_in_else_after_if_else():
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"""
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Feature: Parallel if transformation.
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Description: return in else of the second if/else requires that the after-if func graph should not
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be called, and this information should be propagated through if to
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the outer else part. The first if/else can be transformed.
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Expectation: success
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"""
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|
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@jit
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def foo(x, y, bias):
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if x > y:
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x = x + y
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else:
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x = x - y
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if bias > y:
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y = x + y
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else:
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if x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_else_after_by_if_return_in_else():
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"""
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|
Feature: Parallel if transformation.
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Description: return in inner second if requires that the after-if func graph should not
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be called, and this information should be propagated through if to
|
|
the outer else part. The second first if/else can be transformed.
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|
Expectation: success
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"""
|
|
|
|
@jit
|
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def foo(x, y, bias):
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if bias > y:
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y = x + y
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else:
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if x > 0:
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return bias
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if x > y:
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x = x + y
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else:
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x = x - y
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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def test_if_else_in_if_while_return_in_else():
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"""
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|
Feature: Parallel if transformation.
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Description: return in inner while loop requires that the after-if func graph should not
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be called, and this information should be propagated through while to
|
|
the outer else part. The inner if/else in the first if can be transformed.
|
|
Expectation: success
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"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
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if bias > y:
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y = x + y
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if x > y:
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x = x + y
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else:
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x = x - y
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else:
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while x > 0:
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return bias
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return x + y
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
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bias = Tensor([-5], mstype.int32)
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expect = Tensor([-5], mstype.int32)
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ret = foo(x, y, bias)
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assert ret == expect
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|
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|
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def test_if_else_in_if_if_return_in_else():
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"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in else of the first if/else requires that the after-if func graph should not
|
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be called, and this information should be propagated through if to
|
|
the outer else part. The if/else inside the first if can be transformed.
|
|
Expectation: success
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|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
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if bias > y:
|
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y = x + y
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if x > y:
|
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x = x + y
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else:
|
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x = x - y
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else:
|
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if x > 0:
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return bias
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|
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return x + y
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|
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x = Tensor([4], mstype.int32)
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y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_for_return_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in for loop requires that the after-if func graph should not
|
|
be called.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
return bias
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_return_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
if y > 0:
|
|
return bias
|
|
x = x - 1
|
|
y = y + 1
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_return_else_break_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
if y > 0:
|
|
return bias
|
|
break
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_return_else_return_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
if y > 0:
|
|
return bias
|
|
return x
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_for_return_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through outer for to
|
|
the else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
for _ in range(5):
|
|
return bias
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_return_in_for_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through outer for to
|
|
the outer else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
for _ in range(5):
|
|
if y > 0:
|
|
return bias
|
|
x = x - 1
|
|
y = y + 1
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_return_else_return_in_for_in_for_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
for _ in range(5):
|
|
if y > 0:
|
|
return bias
|
|
return x
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_for_return_after_if_else_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part. The inner if/else can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
if x > y:
|
|
x = x + y
|
|
else:
|
|
x = x - y
|
|
|
|
for _ in range(5):
|
|
return bias
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_else_after_for_return_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part. The inner if/else can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
return bias
|
|
if x > y:
|
|
x = x + y
|
|
else:
|
|
x = x - y
|
|
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_for_return_in_else_after_if_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part. The first if/else can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if x > y:
|
|
x = x + y
|
|
else:
|
|
x = x - y
|
|
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
return bias
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_else_after_by_for_return_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part. The second if/else can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
else:
|
|
for _ in range(5):
|
|
return bias
|
|
if x > y:
|
|
x = x + y
|
|
else:
|
|
x = x - y
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_else_in_if_for_return_in_else():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: return in inner for loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer else part. The inner if/else in the first if can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, bias):
|
|
if bias > y:
|
|
y = x + y
|
|
if x > y:
|
|
x = x + y
|
|
else:
|
|
x = x - y
|
|
else:
|
|
for _ in range(5):
|
|
return bias
|
|
return x + y
|
|
|
|
x = Tensor([4], mstype.int32)
|
|
y = Tensor([1], mstype.int32)
|
|
bias = Tensor([-5], mstype.int32)
|
|
expect = Tensor([-5], mstype.int32)
|
|
ret = foo(x, y, bias)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_by_if_break_in_if_in_while():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: break in if in while loop requires that the after-if func graph should not
|
|
be called, and this information should be propagated through for to
|
|
the outer if part. The by if can be transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, z):
|
|
out = z
|
|
while x < y:
|
|
if y > 2 * x:
|
|
out = out + out
|
|
if y > 3 * x:
|
|
y = y - 1
|
|
if y == 3 * x:
|
|
break
|
|
out = out + out
|
|
return out
|
|
|
|
x = Tensor(2, mstype.int32)
|
|
y = Tensor(8, mstype.int32)
|
|
z = Tensor([5], mstype.int32)
|
|
expect = Tensor([40], mstype.int32)
|
|
ret = foo(x, y, z)
|
|
assert ret == expect
|
|
|
|
|
|
def test_if_raise_raise():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: raise in if requires that the after-if func graph should not
|
|
be called, so it cannot be transformed. The outer if can be
|
|
transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, z):
|
|
out = z
|
|
if x >= y:
|
|
if x > y:
|
|
raise ValueError("x is bigger y")
|
|
else:
|
|
out = out * 2
|
|
out = out + out
|
|
return out
|
|
|
|
x = 3
|
|
y = 2
|
|
z = Tensor([5], mstype.int32)
|
|
with pytest.raises(ValueError):
|
|
foo(x, y, z)
|
|
|
|
|
|
def test_if_raise_not_raise():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: raise in if requires that the after-if func graph should not
|
|
be called, so it cannot be transformed. The outer if can be
|
|
transformed.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, z):
|
|
out = z
|
|
if x >= y:
|
|
if x > y:
|
|
raise ValueError("x is bigger y")
|
|
else:
|
|
out = out * 2
|
|
out = out + out
|
|
return out
|
|
|
|
x = 2
|
|
y = 2
|
|
z = Tensor([5], mstype.int32)
|
|
expected = Tensor([10], mstype.int32)
|
|
ret = foo(x, y, z)
|
|
assert ret == expected
|
|
|
|
|
|
def test_if_assert_success():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: assert in if will not affect the inner and outer if transformation.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, z):
|
|
out = z
|
|
out = z
|
|
if x >= y:
|
|
if x > y:
|
|
assert x > y
|
|
out = out * 3
|
|
else:
|
|
out = out * 2
|
|
out = out + out
|
|
return out
|
|
|
|
x = 3
|
|
y = 2
|
|
z = Tensor([5], mstype.int32)
|
|
expected = Tensor([30], mstype.int32)
|
|
ret = foo(x, y, z)
|
|
assert ret == expected
|
|
|
|
|
|
def test_if_assert_failure():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: assert in if will not affect the inner and outer if transformation.
|
|
Expectation: success
|
|
"""
|
|
|
|
@jit
|
|
def foo(x, y, z):
|
|
out = z
|
|
if x >= y:
|
|
if x > y:
|
|
assert x == y
|
|
out = out * 3
|
|
else:
|
|
out = out * 2
|
|
out = out + out
|
|
return out
|
|
|
|
x = 3
|
|
y = 2
|
|
z = Tensor([5], mstype.int32)
|
|
with pytest.raises(Exception):
|
|
foo(x, y, z)
|
|
|
|
|
|
def test_weight_multiple_one_in_if():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: If the return value of the subgraph is Load, need to insert TensorMove.
|
|
"x = self.w * 1" mean that x is a copy of self.w, x and self.w are not the same object.
|
|
Expectation: success
|
|
"""
|
|
|
|
class Net(Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.w = Parameter(Tensor([4], mstype.int32), name='weight')
|
|
|
|
def construct(self, x, y):
|
|
if y != self.w:
|
|
x = self.w * 1
|
|
self.w = self.w - 1
|
|
return x + y
|
|
|
|
x = Tensor([2], mstype.int32)
|
|
y = Tensor([3], mstype.int32)
|
|
expect = Tensor([7], mstype.int32)
|
|
ret = Net()(x, y)
|
|
assert ret == expect
|
|
|
|
|
|
def test_weight_in_if():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: "x = self.w" mean that x is another name for self.w, x and self.w are the same object.
|
|
Expectation: success
|
|
"""
|
|
|
|
class Net(Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.w = Parameter(Tensor([4], mstype.int32), name='weight')
|
|
|
|
def construct(self, x, y):
|
|
if y != self.w:
|
|
x = self.w
|
|
self.w = self.w - 1
|
|
return x + y
|
|
|
|
x = Tensor([2], mstype.int32)
|
|
y = Tensor([3], mstype.int32)
|
|
expect = Tensor([6], mstype.int32)
|
|
ret = Net()(x, y)
|
|
assert ret == expect
|
|
|
|
|
|
def test_weight_tuple_in_if():
|
|
"""
|
|
Feature: Parallel if transformation.
|
|
Description: If the return value of the subgraph is Tuple(Load), need to insert TensorMove to each load.
|
|
Expectation: success
|
|
"""
|
|
|
|
class Net(Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.w1 = Parameter(Tensor([4], mstype.int32), name='weight1')
|
|
self.w2 = Parameter(Tensor([5], mstype.int32), name='weight2')
|
|
|
|
def construct(self, x, y):
|
|
if y != self.w1:
|
|
x = self.w1 * 1
|
|
self.w1 = self.w1 - 1
|
|
y = self.w2 / 1
|
|
self.w2 = self.w2 - 1
|
|
return x + y
|
|
input_x = Tensor([2], mstype.int32)
|
|
input_y = Tensor([3], mstype.int32)
|
|
expect = Tensor([9], mstype.int32)
|
|
net = Net()
|
|
ret = net(input_x, input_y)
|
|
assert ret == expect
|