mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
# Copyright (c) 2025 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 paddle
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from fastdeploy.model_executor.ops.gpu import get_padding_offset
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class TestGetPaddingOffset(unittest.TestCase):
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def test_get_padding_offset(self):
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seq_lens = np.array([4, 3, 6], "int32").reshape(-1, 1)
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token_num_cpu = np.sum(seq_lens)
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input_ids = np.array(
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[[8, 7, 8, 2, 0, 0, 0, 0, 0, 0], [4, 5, 5, 0, 0, 0, 0, 0, 0, 0], [7, 6, 1, 7, 2, 6, 0, 0, 0, 0]], "int64"
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)
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(
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x_remove_padding,
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batch_id_per_token,
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cu_seqlens_q,
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cu_seqlens_k,
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) = get_padding_offset(paddle.to_tensor(input_ids), paddle.to_tensor(seq_lens), token_num_cpu)
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ref_x_remove_padding = np.array([8, 7, 8, 2, 4, 5, 5, 7, 6, 1, 7, 2, 6], "int64")
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ref_batch_id_per_token = np.array([0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2, 2], "int32")
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ref_cu_seqlens_q = np.array([0, 4, 7, 13], "int32")
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ref_cu_seqlens_k = np.array([0, 4, 7, 13], "int32")
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np.testing.assert_allclose(x_remove_padding.numpy(), ref_x_remove_padding)
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np.testing.assert_allclose(batch_id_per_token.numpy(), ref_batch_id_per_token)
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np.testing.assert_allclose(cu_seqlens_q.numpy(), ref_cu_seqlens_q)
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np.testing.assert_allclose(cu_seqlens_k.numpy(), ref_cu_seqlens_k)
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if __name__ == "__main__":
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unittest.main()
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