Fix doc errors and typos across the board (#8139)
* Fix doc errors and typos across the board * Fix a typo * Fix the CI * Fix more typos * Fix CI * More fixes * Fix CI * More fixes * More fixes
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@@ -45,7 +45,7 @@ from utils_squad import (
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write_predictions_extended,
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)
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# The follwing import is the official SQuAD evaluation script (2.0).
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# The following import is the official SQuAD evaluation script (2.0).
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# You can remove it from the dependencies if you are using this script outside of the library
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# We've added it here for automated tests (see examples/test_examples.py file)
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from utils_squad_evaluate import EVAL_OPTS
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@@ -426,8 +426,8 @@ def _improve_answer_span(doc_tokens, input_start, input_end, tokenizer, orig_ans
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#
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# However, this is not always possible. Consider the following:
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#
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# Question: What country is the top exporter of electornics?
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# Context: The Japanese electronics industry is the lagest in the world.
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# Question: What country is the top exporter of electronics?
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# Context: The Japanese electronics industry is the largest in the world.
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# Answer: Japan
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#
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# In this case, the annotator chose "Japan" as a character sub-span of
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@@ -57,7 +57,7 @@ class XxxConfig(PretrainedConfig):
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If string, :obj:`"gelu"`, :obj:`"relu"`, :obj:`"swish"` and :obj:`"gelu_new"` are supported.
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hidden_dropout_prob (:obj:`float`, `optional`, defaults to 0.1):
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The dropout probabilitiy for all fully connected layers in the embeddings, encoder, and pooler.
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The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
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attention_probs_dropout_prob (:obj:`float`, `optional`, defaults to 0.1):
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The dropout ratio for the attention probabilities.
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max_position_embeddings (:obj:`int`, `optional`, defaults to 512):
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@@ -352,7 +352,7 @@ XXX_INPUTS_DOCSTRING = r"""
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@add_start_docstrings(
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"The bare XXX Model transformer outputing raw hidden-states without any specific head on top.",
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"The bare XXX Model transformer outputting raw hidden-states without any specific head on top.",
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XXX_START_DOCSTRING,
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)
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class TFXxxModel(TFXxxPreTrainedModel):
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@@ -237,7 +237,7 @@ class XxxTokenizer(PreTrainedTokenizer):
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if token_ids_1 is not None:
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raise ValueError(
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"You should not supply a second sequence if the provided sequence of "
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"ids is already formated with special tokens for the model."
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"ids is already formatted with special tokens for the model."
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)
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return list(map(lambda x: 1 if x in [self.sep_token_id, self.cls_token_id] else 0, token_ids_0))
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