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docs/source/zh/internal/generation_utils.md
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docs/source/zh/internal/generation_utils.md
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<!--Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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rendered properly in your Markdown viewer.
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-->
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# 用于生成的工具
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此页面列出了所有由 [`~generation.GenerationMixin.generate`]。
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## 生成输出
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[`~generation.GenerationMixin.generate`] 的输出是 [`~utils.ModelOutput`] 的一个子类的实例。这个输出是一种包含 [`~generation.GenerationMixin.generate`] 返回的所有信息数据结构,但也可以作为元组或字典使用。
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这里是一个例子:
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```python
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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tokenizer = GPT2Tokenizer.from_pretrained("openai-community/gpt2")
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model = GPT2LMHeadModel.from_pretrained("openai-community/gpt2")
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inputs = tokenizer("Hello, my dog is cute and ", return_tensors="pt")
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generation_output = model.generate(**inputs, return_dict_in_generate=True, output_scores=True)
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```
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`generation_output` 的对象是 [`~generation.GenerateDecoderOnlyOutput`] 的一个实例,从该类的文档中我们可以看到,这意味着它具有以下属性:
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- `sequences`: 生成的tokens序列
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- `scores`(可选): 每个生成步骤的语言建模头的预测分数
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- `hidden_states`(可选): 每个生成步骤模型的hidden states
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- `attentions`(可选): 每个生成步骤模型的注意力权重
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在这里,由于我们传递了 `output_scores=True`,我们具有 `scores` 属性。但我们没有 `hidden_states` 和 `attentions`,因为没有传递 `output_hidden_states=True` 或 `output_attentions=True`。
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您可以像通常一样访问每个属性,如果该属性未被模型返回,则将获得 `None`。例如,在这里 `generation_output.scores` 是语言建模头的所有生成预测分数,而 `generation_output.attentions` 为 `None`。
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当我们将 `generation_output` 对象用作元组时,它只保留非 `None` 值的属性。例如,在这里它有两个元素,`loss` 然后是 `logits`,所以
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```python
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generation_output[:2]
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```
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将返回元组`(generation_output.sequences, generation_output.scores)`。
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当我们将`generation_output`对象用作字典时,它只保留非`None`的属性。例如,它有两个键,分别是`sequences`和`scores`。
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我们在此记录所有输出类型。
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### PyTorch
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[[autodoc]] generation.GenerateDecoderOnlyOutput
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[[autodoc]] generation.GenerateEncoderDecoderOutput
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[[autodoc]] generation.GenerateBeamDecoderOnlyOutput
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[[autodoc]] generation.GenerateBeamEncoderDecoderOutput
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## LogitsProcessor
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[`LogitsProcessor`] 可以用于修改语言模型头的预测分数以进行生成
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### PyTorch
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[[autodoc]] AlternatingCodebooksLogitsProcessor
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- __call__
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[[autodoc]] ClassifierFreeGuidanceLogitsProcessor
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- __call__
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[[autodoc]] EncoderNoRepeatNGramLogitsProcessor
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- __call__
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[[autodoc]] EncoderRepetitionPenaltyLogitsProcessor
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- __call__
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[[autodoc]] EpsilonLogitsWarper
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- __call__
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[[autodoc]] EtaLogitsWarper
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- __call__
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[[autodoc]] ExponentialDecayLengthPenalty
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- __call__
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[[autodoc]] ForcedBOSTokenLogitsProcessor
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- __call__
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[[autodoc]] ForcedEOSTokenLogitsProcessor
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- __call__
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[[autodoc]] InfNanRemoveLogitsProcessor
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- __call__
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[[autodoc]] LogitNormalization
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- __call__
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[[autodoc]] LogitsProcessor
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- __call__
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[[autodoc]] LogitsProcessorList
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- __call__
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[[autodoc]] MinLengthLogitsProcessor
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- __call__
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[[autodoc]] MinNewTokensLengthLogitsProcessor
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- __call__
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[[autodoc]] NoBadWordsLogitsProcessor
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- __call__
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[[autodoc]] NoRepeatNGramLogitsProcessor
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- __call__
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[[autodoc]] PrefixConstrainedLogitsProcessor
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- __call__
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[[autodoc]] RepetitionPenaltyLogitsProcessor
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- __call__
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[[autodoc]] SequenceBiasLogitsProcessor
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- __call__
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[[autodoc]] SuppressTokensAtBeginLogitsProcessor
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- __call__
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[[autodoc]] SuppressTokensLogitsProcessor
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- __call__
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[[autodoc]] TemperatureLogitsWarper
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- __call__
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[[autodoc]] TopKLogitsWarper
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- __call__
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[[autodoc]] TopPLogitsWarper
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- __call__
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[[autodoc]] TypicalLogitsWarper
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- __call__
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[[autodoc]] UnbatchedClassifierFreeGuidanceLogitsProcessor
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- __call__
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[[autodoc]] WhisperTimeStampLogitsProcessor
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- __call__
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## StoppingCriteria
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可以使用[`StoppingCriteria`]来更改停止生成的时间(除了EOS token以外的方法)。请注意,这仅适用于我们的PyTorch实现。
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[[autodoc]] StoppingCriteria
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- __call__
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[[autodoc]] StoppingCriteriaList
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- __call__
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[[autodoc]] MaxLengthCriteria
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- __call__
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[[autodoc]] MaxTimeCriteria
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- __call__
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## Streamers
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[[autodoc]] TextStreamer
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[[autodoc]] TextIteratorStreamer
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