wehub-resource-sync
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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test_ast_only,
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)
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import paddle
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from paddle.nn import Layer
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class Net(Layer):
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def __init__(self):
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super().__init__()
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self.fc = paddle.nn.Linear(16, 3)
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def forward(self, x, y, m, n):
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inputs = [x, y, m, n]
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outs = []
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for var in inputs:
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out = paddle.reshape(x, [-1, 16])
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out = self.fc(out)
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outs.append(out)
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out = paddle.stack(outs)
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return paddle.sum(out)
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class TestArgsSpecName(Dy2StTestBase):
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def read_from_dataset(self):
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self.x = paddle.randn([4, 2, 8])
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self.y = paddle.randn([4, 2, 8])
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self.m = paddle.randn([4, 2, 8])
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self.n = paddle.randn([4, 2, 8])
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@test_ast_only
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def test_spec_name_hash(self):
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net = Net()
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net = paddle.jit.to_static(net)
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# Convert into program with four input
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self.read_from_dataset()
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self.run_test(net, [self.x, self.y, self.m, self.n], 1, [0, 1, 2, 3])
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# Convert into program with three input
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self.read_from_dataset()
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self.run_test(net, [self.x, self.x, self.m, self.n], 1, [0, 0, 1, 2])
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# Convert into program with two input
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self.read_from_dataset()
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self.run_test(net, [self.x, self.x, self.m, self.m], 1, [0, 0, 1, 1])
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# Use Cache Program
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self.read_from_dataset()
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self.run_test(net, [self.n, self.n, self.y, self.y], 1, [0, 0, 1, 1])
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# Convert into program with two input
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self.read_from_dataset()
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self.run_test(net, [self.x, self.y, self.x, self.y], 1, [0, 1, 0, 1])
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# Use Cache Program
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self.read_from_dataset()
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self.run_test(net, [self.m, self.n, self.m, self.n], 1, [0, 1, 0, 1])
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# Convert into program with one input
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self.read_from_dataset()
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self.run_test(net, [self.x, self.x, self.x, self.x], 1, [0, 0, 0, 0])
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# Use Cache Program
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self.read_from_dataset()
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self.run_test(net, [self.m, self.m, self.m, self.m], 1, [0, 0, 0, 0])
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def run_test(self, net, inputs, trace_count, mode):
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out = net(*inputs)
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self.assertEqual(net.forward.get_traced_count(), trace_count)
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if __name__ == '__main__':
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unittest.main()
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