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63 lines
2.2 KiB
Python
63 lines
2.2 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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"""UT for air_topp_sampling kernel"""
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import subprocess
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import unittest
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import numpy as np
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import paddle
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import fastdeploy.model_executor.ops.gpu
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class Test(unittest.TestCase):
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def setUp(self):
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"""
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Initialize.
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"""
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paddle.seed(2024)
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np.random.seed(42)
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print(paddle.device.cuda.get_device_properties())
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print(paddle.__git_commit__)
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nvcc_output = subprocess.check_output(["nvcc", "--version"], universal_newlines=True)
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output = nvcc_output.split()
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release_idx = output.index("release") + 1
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self.nvcc_cuda_version = float(output[release_idx].split(",")[0])
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def test_air_topp_sampling(self):
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"""
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Check air_topp_sampling output with paddle.tensor.top_p_sampling.
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"""
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if self.nvcc_cuda_version < 12.0:
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self.skipTest("air_topp_sampling only support cu12+")
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bsz = 8
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vocab_size = 103424
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x = paddle.randn([bsz, vocab_size])
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x = paddle.nn.functional.softmax(x)
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x = paddle.cast(x, "float32")
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top_ps = paddle.to_tensor(np.random.uniform(0, 1, [bsz]).astype(np.float32))
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_, next_tokens = fastdeploy.model_executor.ops.gpu.air_topp_sampling(
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x.cuda(), top_ps.cuda(), None, None, seed=0, k=1, mode="truncated"
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)
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print(next_tokens)
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less_than_zero = next_tokens >= 0
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greater_than_vocab_size = next_tokens <= vocab_size
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accuracy = paddle.logical_and(less_than_zero, greater_than_vocab_size)
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print(f"Accuracy of results: {accuracy}")
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if __name__ == "__main__":
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unittest.main()
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