# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np import paddle from fastdeploy.model_executor.ops.gpu import get_padding_offset class TestGetPaddingOffset(unittest.TestCase): def test_get_padding_offset(self): max_len = 10 seq_lens = np.array([4, 3, 6], "int32").reshape(-1, 1) cum_offset = np.cumsum((max_len - seq_lens).flatten(), -1, "int32") token_num = np.sum(seq_lens) input_ids = np.array( [[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" ) ( x_remove_padding, batch_id_per_token, cu_seqlens_q, cu_seqlens_k, ) = get_padding_offset( paddle.to_tensor(input_ids), paddle.to_tensor(cum_offset), paddle.to_tensor(token_num), paddle.to_tensor(seq_lens), ) ref_x_remove_padding = np.array([8, 7, 8, 2, 4, 5, 5, 7, 6, 1, 7, 2, 6], "int64") ref_batch_id_per_token = np.array([0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2, 2], "int32") ref_cu_seqlens_q = np.array([0, 4, 7, 13], "int32") ref_cu_seqlens_k = np.array([0, 4, 7, 13], "int32") np.testing.assert_allclose(x_remove_padding.numpy(), ref_x_remove_padding) np.testing.assert_allclose(batch_id_per_token.numpy(), ref_batch_id_per_token) np.testing.assert_allclose(cu_seqlens_q.numpy(), ref_cu_seqlens_q) np.testing.assert_allclose(cu_seqlens_k.numpy(), ref_cu_seqlens_k) if __name__ == "__main__": unittest.main()