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73 lines
2.2 KiB
Python
73 lines
2.2 KiB
Python
"""
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# 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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"""
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import paddle
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import paddle.nn as nn
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import paddle.nn.functional as F
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from fastdeploy.distributed.parallel_state import \
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get_tensor_model_parallel_world_size
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from fastdeploy.model_executor.layers.sample.meta_data import SamplingMetadata
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from fastdeploy.model_executor.layers.sample.ops import \
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apply_penalty_multi_scores
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from fastdeploy.platforms import current_platform
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class Sampler(nn.Layer):
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"""
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"""
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def __init__(self):
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"""
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"""
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super().__init__()
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if current_platform.is_cuda():
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self.nranks = get_tensor_model_parallel_world_size()
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self.forward = self.forward_cuda
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else:
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raise NotImplementedError()
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def forward_cuda(
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self,
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logits: paddle.Tensor,
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sampling_metadata: SamplingMetadata,
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) -> paddle.Tensor:
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"""
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"""
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logits = apply_penalty_multi_scores(
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sampling_metadata.prompt_token_ids,
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logits,
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sampling_metadata.repetition_penalties,
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sampling_metadata.frequency_penalties,
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sampling_metadata.presence_penalties,
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sampling_metadata.temperature,
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sampling_metadata.bad_words_token_ids,
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sampling_metadata.step_idx,
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sampling_metadata.min_dec_lens,
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sampling_metadata.eos_token_ids,
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)
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probs = F.softmax(logits)
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_, next_tokens = paddle.tensor.top_p_sampling(probs,
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sampling_metadata.top_p)
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if self.nranks > 1:
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paddle.distributed.broadcast(next_tokens, 0)
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return next_tokens
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