# 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 speculate_get_seq_lens_output class TestSpeculateGetSeqLensOutput(unittest.TestCase): def run_seq_lens(self, input_values): paddle.seed(42) np.random.seed(42) seq_lens_this_time = paddle.to_tensor(input_values[0], dtype="int32") seq_lens_encoder = paddle.to_tensor(input_values[1], dtype="int32") seq_lens_decoder = paddle.to_tensor(input_values[2], dtype="int32") seq_lens_output = speculate_get_seq_lens_output(seq_lens_this_time, seq_lens_encoder, seq_lens_decoder)[0] return seq_lens_output def test_speculate_get_seq_lens_output1(self): input_values = [[7], [0], [0]] output_value = 7 result = self.run_seq_lens(input_values) np.testing.assert_allclose(result.numpy(), output_value) def test_speculate_get_seq_lens_output2(self): input_values = [[7], [1], [0]] output_value = 1 result = self.run_seq_lens(input_values) np.testing.assert_allclose(result.numpy(), output_value) def test_speculate_get_seq_lens_output3(self): input_values = [[1], [1], [0]] output_value = 1 result = self.run_seq_lens(input_values) np.testing.assert_allclose(result.numpy(), output_value) def test_speculate_get_seq_lens_output4(self): input_values = [[0], [1], [0]] output_value = 0 result = self.run_seq_lens(input_values) np.testing.assert_allclose(result.numpy(), output_value) if __name__ == "__main__": unittest.main()