wehub-resource-sync
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
# Copyright (c) 2024 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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import numpy as np
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import utils
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from test_cinn_sub_graph import TestCinnSubGraphBase
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import paddle
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from paddle import nn
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class SoftmaxNet(nn.Layer):
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def __init__(self):
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super().__init__()
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def forward(self, x):
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return nn.functional.softmax(x, axis=-1)
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class TestSoftmax(TestCinnSubGraphBase):
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def prepare_data(self):
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self.shape = [7, 2048, 768]
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self.x = paddle.randn(self.shape, dtype="float32")
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self.x.stop_gradient = True
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def check_jit_kernel_info(self, static_fn):
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utils.check_jit_kernel_number(static_fn, 1)
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utils.check_jit_kernel_structure(static_fn, {utils.JIT_KERNEL_NAME: 1})
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def eval(self, use_cinn):
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paddle.seed(2022)
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net = SoftmaxNet()
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net = utils.apply_to_static(net, use_cinn)
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net.eval()
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out = net(self.x)
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if use_cinn:
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self.check_jit_kernel_info(net.forward)
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return out
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def test_eval(self):
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cinn_out = self.eval(use_cinn=True)
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dy_out = self.eval(use_cinn=False)
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np.testing.assert_allclose(
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cinn_out.numpy(), dy_out.numpy(), atol=1e-6, rtol=1e-6
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)
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if __name__ == '__main__':
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unittest.main()
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