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| # 用于生成的工具 | |
| 此页面列出了所有由 [`~generation.GenerationMixin.generate`], | |
| [`~generation.GenerationMixin.greedy_search`], | |
| [`~generation.GenerationMixin.contrastive_search`], | |
| [`~generation.GenerationMixin.sample`], | |
| [`~generation.GenerationMixin.beam_search`], | |
| [`~generation.GenerationMixin.beam_sample`], | |
| [`~generation.GenerationMixin.group_beam_search`], 和 | |
| [`~generation.GenerationMixin.constrained_beam_search`]使用的实用函数。 | |
| 其中大多数仅在您研究库中生成方法的代码时才有用。 | |
| ## 生成输出 | |
| [`~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。 | |
| 这里是一个例子： | |
| ```python | |
| from transformers import GPT2Tokenizer, GPT2LMHeadModel | |
| tokenizer = GPT2Tokenizer.from_pretrained("openai-community/gpt2") | |
| model = GPT2LMHeadModel.from_pretrained("openai-community/gpt2") | |
| inputs = tokenizer("Hello, my dog is cute and ", return_tensors="pt") | |
| generation_output = model.generate(**inputs, return_dict_in_generate=True, output_scores=True) | |
| ``` | |
| `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： | |
| - `sequences`: 生成的tokens序列 | |
| - `scores`（可选）: 每个生成步骤的语言建模头的预测分数 | |
| - `hidden_states`（可选）: 每个生成步骤模型的hidden states | |
| - `attentions`（可选）: 每个生成步骤模型的注意力权重 | |
| 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`。 | |
| 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`。 | |
| 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 | |
| ```python | |
| generation_output[:2] | |
| ``` | |
| 将返回元组`(generation_output.sequences, generation_output.scores)`。 | |
| 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`。 | |
| 我们在此记录所有输出类型。 | |
| ### PyTorch | |
| [[autodoc]] generation.GenerateDecoderOnlyOutput | |
| [[autodoc]] generation.GenerateEncoderDecoderOutput | |
| [[autodoc]] generation.GenerateBeamDecoderOnlyOutput | |
| [[autodoc]] generation.GenerateBeamEncoderDecoderOutput | |
| ### TensorFlow | |
| [[autodoc]] generation.TFGreedySearchEncoderDecoderOutput | |
| [[autodoc]] generation.TFGreedySearchDecoderOnlyOutput | |
| [[autodoc]] generation.TFSampleEncoderDecoderOutput | |
| [[autodoc]] generation.TFSampleDecoderOnlyOutput | |
| [[autodoc]] generation.TFBeamSearchEncoderDecoderOutput | |
| [[autodoc]] generation.TFBeamSearchDecoderOnlyOutput | |
| [[autodoc]] generation.TFBeamSampleEncoderDecoderOutput | |
| [[autodoc]] generation.TFBeamSampleDecoderOnlyOutput | |
| [[autodoc]] generation.TFContrastiveSearchEncoderDecoderOutput | |
| [[autodoc]] generation.TFContrastiveSearchDecoderOnlyOutput | |
| ### FLAX | |
| [[autodoc]] generation.FlaxSampleOutput | |
| [[autodoc]] generation.FlaxGreedySearchOutput | |
| [[autodoc]] generation.FlaxBeamSearchOutput | |
| ## LogitsProcessor | |
| [`LogitsProcessor`] 可以用于修改语言模型头的预测分数以进行生成 | |
| ### PyTorch | |
| [[autodoc]] AlternatingCodebooksLogitsProcessor | |
| - __call__ | |
| [[autodoc]] ClassifierFreeGuidanceLogitsProcessor | |
| - __call__ | |
| [[autodoc]] EncoderNoRepeatNGramLogitsProcessor | |
| - __call__ | |
| [[autodoc]] EncoderRepetitionPenaltyLogitsProcessor | |
| - __call__ | |
| [[autodoc]] EpsilonLogitsWarper | |
| - __call__ | |
| [[autodoc]] EtaLogitsWarper | |
| - __call__ | |
| [[autodoc]] ExponentialDecayLengthPenalty | |
| - __call__ | |
| [[autodoc]] ForcedBOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] ForcedEOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] ForceTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] HammingDiversityLogitsProcessor | |
| - __call__ | |
| [[autodoc]] InfNanRemoveLogitsProcessor | |
| - __call__ | |
| [[autodoc]] LogitNormalization | |
| - __call__ | |
| [[autodoc]] LogitsProcessor | |
| - __call__ | |
| [[autodoc]] LogitsProcessorList | |
| - __call__ | |
| [[autodoc]] LogitsWarper | |
| - __call__ | |
| [[autodoc]] MinLengthLogitsProcessor | |
| - __call__ | |
| [[autodoc]] MinNewTokensLengthLogitsProcessor | |
| - __call__ | |
| [[autodoc]] NoBadWordsLogitsProcessor | |
| - __call__ | |
| [[autodoc]] NoRepeatNGramLogitsProcessor | |
| - __call__ | |
| [[autodoc]] PrefixConstrainedLogitsProcessor | |
| - __call__ | |
| [[autodoc]] RepetitionPenaltyLogitsProcessor | |
| - __call__ | |
| [[autodoc]] SequenceBiasLogitsProcessor | |
| - __call__ | |
| [[autodoc]] SuppressTokensAtBeginLogitsProcessor | |
| - __call__ | |
| [[autodoc]] SuppressTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TemperatureLogitsWarper | |
| - __call__ | |
| [[autodoc]] TopKLogitsWarper | |
| - __call__ | |
| [[autodoc]] TopPLogitsWarper | |
| - __call__ | |
| [[autodoc]] TypicalLogitsWarper | |
| - __call__ | |
| [[autodoc]] UnbatchedClassifierFreeGuidanceLogitsProcessor | |
| - __call__ | |
| [[autodoc]] WhisperTimeStampLogitsProcessor | |
| - __call__ | |
| ### TensorFlow | |
| [[autodoc]] TFForcedBOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFForcedEOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFForceTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFLogitsProcessorList | |
| - __call__ | |
| [[autodoc]] TFLogitsWarper | |
| - __call__ | |
| [[autodoc]] TFMinLengthLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFNoBadWordsLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFNoRepeatNGramLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFRepetitionPenaltyLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFSuppressTokensAtBeginLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFSuppressTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] TFTemperatureLogitsWarper | |
| - __call__ | |
| [[autodoc]] TFTopKLogitsWarper | |
| - __call__ | |
| [[autodoc]] TFTopPLogitsWarper | |
| - __call__ | |
| ### FLAX | |
| [[autodoc]] FlaxForcedBOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxForcedEOSTokenLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxForceTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxLogitsProcessorList | |
| - __call__ | |
| [[autodoc]] FlaxLogitsWarper | |
| - __call__ | |
| [[autodoc]] FlaxMinLengthLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxSuppressTokensAtBeginLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxSuppressTokensLogitsProcessor | |
| - __call__ | |
| [[autodoc]] FlaxTemperatureLogitsWarper | |
| - __call__ | |
| [[autodoc]] FlaxTopKLogitsWarper | |
| - __call__ | |
| [[autodoc]] FlaxTopPLogitsWarper | |
| - __call__ | |
| [[autodoc]] FlaxWhisperTimeStampLogitsProcessor | |
| - __call__ | |
| ## StoppingCriteria | |
| 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。 | |
| [[autodoc]] StoppingCriteria | |
| - __call__ | |
| [[autodoc]] StoppingCriteriaList | |
| - __call__ | |
| [[autodoc]] MaxLengthCriteria | |
| - __call__ | |
| [[autodoc]] MaxTimeCriteria | |
| - __call__ | |
| ## Constraints | |
| 可以使用[`Constraint`]来强制生成结果包含输出中的特定tokens或序列。请注意，这仅适用于我们的PyTorch实现。 | |
| [[autodoc]] Constraint | |
| [[autodoc]] PhrasalConstraint | |
| [[autodoc]] DisjunctiveConstraint | |
| [[autodoc]] ConstraintListState | |
| ## BeamSearch | |
| [[autodoc]] BeamScorer | |
| - process | |
| - finalize | |
| [[autodoc]] BeamSearchScorer | |
| - process | |
| - finalize | |
| [[autodoc]] ConstrainedBeamSearchScorer | |
| - process | |
| - finalize | |
| ## Utilities | |
| [[autodoc]] top_k_top_p_filtering | |
| [[autodoc]] tf_top_k_top_p_filtering | |
| ## Streamers | |
| [[autodoc]] TextStreamer | |
| [[autodoc]] TextIteratorStreamer | |