根据错误信息,add_code_sample_docstrings()函数不接受名为'tokenizer_c'的关键字参数。实际上,错误信息中的参数名应该是'tokenizer_class',而不是'tokenizer_c'。这可能是由于输入错误或复制粘贴时的笔误。 确认是否误将其他函数或方法的参数错误地传递给了add_code_sample_docstrings(): 看起来像是误将'tokenizer...
Code for the paper "Language Models are Unsupervised Multitask Learners" - TypeError: add_code_sample_docstrings() got an unexpected keyword argument 'tokenizer_class' · Issue #299 · openai/gpt-2
When I tried your command for wikiQA t5 prefix, I got the following error: File "/home/pouramini/UnifiedSKG/models/unified/prefixtuning.py", line 8, in <module> from ..prompt.modeling_auto import AutoModelForSeq2SeqLM File "/home/pourami...
The most important information in the above example is the amount and meaning of the arguments passed to the two new methods; these are described in docstrings within the example. The final phase of the data life cycle, as well as the last part of the code ...
For all add-ons, follow Python’sPEP 8andPEP 257guidelines for docstring conventions. There is no consensus on the format of the actual content of docstrings inAnaconda; the only requirement is that they are human-readable. If you plan to use auto-generated...
def append_call_sample_docstring(model_class, checkpoint, output_type, config_class, mask=None, revision=None): model_class.__call__ = copy_func(model_class.__call__) model_class.__call__ = add_code_sample_docstrings( checkpoint=checkpoint, output_type=output_type, config_class=config_cl...
@add_start_docstrings_to_model_forward(OPT_INPUTS_DOCSTRING) @add_code_sample_docstrings( checkpoint=_CHECKPOINT_FOR_DOC, output_type=BaseModelOutputWithPast, config_class=_CONFIG_FOR_DOC, expected_output=_EXPECTED_OUTPUT_SHAPE, ) def forward( self, input_ids: torch.LongTensor = None, attentio...
If you plan to use auto-generated documentation for your add-on, docstrings should follow the guidelines for the toolkit you use to accomplish this. You can include a category subpackage if an add-on needs to define a new category, but this is not recommended. ...
The most important information in the above example is the amount and meaning of the arguments passed to the two new methods; these are described in docstrings within the example. The final phase of the data life cycle, as well as the last part of the code ...
add_code_sample_docstrings ) from transformers.modeling_utils import PreTrainedModel, SequenceSummary #from transformers.src.transformers.pytorch_utils import Conv1D, find_pruneable_heads_and_indices, prune_conv1d_layer from transformers.models.gpt2 import GPT2Config, GPT2PreTrainedModelfrom...