From ee4dca6e8d181e45a79b8fd9462f23ab07ef137e Mon Sep 17 00:00:00 2001 From: Stefan Schweter Date: Thu, 9 Jun 2022 21:24:38 +0200 Subject: [PATCH 1/3] rembert: fix python codeblock --- .../models/rembert/configuration_rembert.py | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/src/transformers/models/rembert/configuration_rembert.py b/src/transformers/models/rembert/configuration_rembert.py index 589c40bdcb98d..732d75c5cc2b3 100644 --- a/src/transformers/models/rembert/configuration_rembert.py +++ b/src/transformers/models/rembert/configuration_rembert.py @@ -21,7 +21,7 @@ logger = logging.get_logger(__name__) REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = { - "rembert": "https://huggingface.co/google/rembert/resolve/main/config.json", + "google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json", # See all RemBERT models at https://huggingface.co/models?filter=rembert } @@ -80,16 +80,17 @@ class RemBertConfig(PretrainedConfig): Example: ```python + >>> from transformers import RemBertModel, RemBertConfig - ``` + >>> # Initializing a RemBERT rembert style configuration + >>> configuration = RemBertConfig() - >>> from transformers import RemBertModel, RemBertConfig >>> # Initializing a RemBERT rembert style - configuration >>> configuration = RemBertConfig() + >>> # Initializing a model from the rembert style configuration + >>> model = RemBertModel(configuration) - >>> # Initializing a model from the rembert style configuration >>> model = RemBertModel(configuration) - - >>> # Accessing the model configuration >>> configuration = model.config - """ + >>> # Accessing the model configuration + >>> configuration = model.config + ```""" model_type = "rembert" def __init__( From ce718f0be9c3ad831769821e19e94386db9523c9 Mon Sep 17 00:00:00 2001 From: Stefan Schweter Date: Thu, 9 Jun 2022 21:25:32 +0200 Subject: [PATCH 2/3] rembert: use correct google/rembert checkpoint name in documentation --- src/transformers/models/rembert/modeling_rembert.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/transformers/models/rembert/modeling_rembert.py b/src/transformers/models/rembert/modeling_rembert.py index 08fd7d3e2d065..b6c20cb689d86 100755 --- a/src/transformers/models/rembert/modeling_rembert.py +++ b/src/transformers/models/rembert/modeling_rembert.py @@ -786,7 +786,7 @@ class PreTrainedModel @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=BaseModelOutputWithPastAndCrossAttentions, config_class=_CONFIG_FOR_DOC, ) @@ -939,7 +939,7 @@ def set_output_embeddings(self, new_embeddings): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=MaskedLMOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1184,7 +1184,7 @@ def __init__(self, config): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=SequenceClassifierOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1281,7 +1281,7 @@ def __init__(self, config): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=MultipleChoiceModelOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1374,7 +1374,7 @@ def __init__(self, config): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TokenClassifierOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1453,7 +1453,7 @@ def __init__(self, config): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=QuestionAnsweringModelOutput, config_class=_CONFIG_FOR_DOC, ) From d5abe2f130148ba7c9a1d145400fa012477b54da Mon Sep 17 00:00:00 2001 From: Stefan Schweter Date: Thu, 9 Jun 2022 21:25:49 +0200 Subject: [PATCH 3/3] rembert: use correct google/rembert checkpoint name in TF documentation --- .../models/rembert/modeling_tf_rembert.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/transformers/models/rembert/modeling_tf_rembert.py b/src/transformers/models/rembert/modeling_tf_rembert.py index 92d4604b6c3d8..2e25dafed4830 100644 --- a/src/transformers/models/rembert/modeling_tf_rembert.py +++ b/src/transformers/models/rembert/modeling_tf_rembert.py @@ -938,7 +938,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFBaseModelOutputWithPoolingAndCrossAttentions, config_class=_CONFIG_FOR_DOC, ) @@ -1041,7 +1041,7 @@ def get_lm_head(self) -> tf.keras.layers.Layer: @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFMaskedLMOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1131,7 +1131,7 @@ def prepare_inputs_for_generation(self, input_ids, past=None, attention_mask=Non @unpack_inputs @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFCausalLMOutputWithCrossAttentions, config_class=_CONFIG_FOR_DOC, ) @@ -1262,7 +1262,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFSequenceClassifierOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1352,7 +1352,7 @@ def dummy_inputs(self) -> Dict[str, tf.Tensor]: @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFMultipleChoiceModelOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1471,7 +1471,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFTokenClassifierOutput, config_class=_CONFIG_FOR_DOC, ) @@ -1550,7 +1550,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs): @add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( processor_class=_TOKENIZER_FOR_DOC, - checkpoint="rembert", + checkpoint="google/rembert", output_type=TFQuestionAnsweringModelOutput, config_class=_CONFIG_FOR_DOC, )