forked from mindspore-Ecosystem/mindspore
110 lines
3.9 KiB
Python
110 lines
3.9 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
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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.rewrite import SymbolTree
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import mindspore.nn as nn
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import pytest
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class SimpleNet(nn.Cell):
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def __init__(self):
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super().__init__()
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self.mul = P.Mul()
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self.dense = nn.Dense(in_channels=32, out_channels=32, weight_init="ones")
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self.mean = P.ReduceMean(keep_dims=False)
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self.split = P.Split(axis=1, output_num=3)
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def construct(self, x, y):
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x = self.dense(x)
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y, _, _ = self.split(y)
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y = self.mean(y, (2, 3))
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x = self.mul(x, 1)
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return x, y
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def test_create_call_function_ok():
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"""
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Feature: Create a call function node.
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Description: Call create_call_function to create a call function node.
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Expectation: Success.
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"""
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net = SimpleNet()
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stree = SymbolTree.create(net)
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new_node = stree.create_call_function(F.abs, ["x"], ["abc"], {})
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for node in stree.nodes():
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if node.get_instance_type() == P.ReduceMean:
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pos = stree.after(node)
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stree.insert(pos, new_node)
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new_node_1 = stree.create_call_function(F.abs, ["x"], [node], {})
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stree.insert(pos, new_node_1)
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new_node_2 = stree.create_call_function(F.scalar_to_tensor, ["x"], [2], {'dtype': mindspore.float16})
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stree.insert(pos, new_node_2)
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new_node_3 = stree.create_call_function(F.scalar_to_tensor, ["x"], [2, mindspore.float16])
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stree.insert(pos, new_node_3)
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def test_create_call_function_fail():
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"""
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Feature: Create a call function node.
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Description: Call create_call_function to create a call function node.
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Expectation: raise TypeError.
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"""
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net = SimpleNet()
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stree = SymbolTree.create(net)
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for node in stree.nodes():
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if node.get_instance_type() == P.ReduceMean:
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with pytest.raises(TypeError):
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_ = stree.create_call_function(F.cast, ["x"], [node, mindspore.float16], {})
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def test_create_call_function_fail_0():
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"""
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Feature: Create a call function node.
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Description: Call create_call_function to create a call function node.
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Expectation: raise TypeError.
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"""
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net = SimpleNet()
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stree = SymbolTree.create(net)
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for node in stree.nodes():
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if node.get_instance_type() == P.ReduceMean:
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with pytest.raises(TypeError):
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_ = stree.create_call_function(F.scalar_to_tensor, "x", [2], {'dtype': mindspore.int32})
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def test_create_call_function_fail_1():
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"""
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Feature: Create a call function node.
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Description: Call create_call_function to create a call function node.
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Expectation: raise TypeError.
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"""
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net = SimpleNet()
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stree = SymbolTree.create(net)
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with pytest.raises(TypeError):
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_ = stree.create_call_function(F.abs, "x", ["abc", [1, 2]], {})
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with pytest.raises(TypeError):
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_ = stree.create_call_function(F.abs, "x", [], {})
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with pytest.raises(TypeError):
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_ = stree.create_call_function(F.scalar_to_tensor, ["x"], [2], {'dtype': mindspore.int32})
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with pytest.raises(TypeError):
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t = mindspore.Tensor(1, mindspore.int32)
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_ = stree.create_call_function(F.scalar_to_tensor, ["x"], [t, mindspore.float16])
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