Fix push_to_hub docstring and make it appear in doc (#12770)

docs/source/main_classes/configuration.rst

@@ -22,4 +22,5 @@ PretrainedConfig
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. autoclass:: transformers.PretrainedConfig
+    :special-members: push_to_hub
     :members:

docs/source/main_classes/model.rst

@@ -35,6 +35,7 @@ PreTrainedModel
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. autoclass:: transformers.PreTrainedModel
+    :special-members: push_to_hub
     :members:
 
 
@@ -80,6 +81,7 @@ TFPreTrainedModel
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. autoclass:: transformers.TFPreTrainedModel
+    :special-members: push_to_hub
     :members:
 
 
@@ -94,6 +96,7 @@ FlaxPreTrainedModel
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. autoclass:: transformers.FlaxPreTrainedModel
+    :special-members: push_to_hub
     :members:
 
 

docs/source/main_classes/tokenizer.rst

@@ -53,10 +53,8 @@ PreTrainedTokenizer
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. autoclass:: transformers.PreTrainedTokenizer
-    :special-members: __call__
-    :members: batch_decode, convert_ids_to_tokens, convert_tokens_to_ids, convert_tokens_to_string, decode, encode, 
-        get_added_vocab, get_special_tokens_mask, num_special_tokens_to_add, prepare_for_tokenization, tokenize,
-        vocab_size
+    :special-members: __call__, batch_decode, decode, encode, push_to_hub
+    :members: 
 
 
 PreTrainedTokenizerFast
@@ -68,10 +66,8 @@ loaded very simply into 🤗 transformers. Take a look at the :doc:`Using tokeni
 <../fast_tokenizers>` page to understand how this is done.
 
 .. autoclass:: transformers.PreTrainedTokenizerFast
-    :special-members: __call__
-    :members: batch_decode, convert_ids_to_tokens, convert_tokens_to_ids, convert_tokens_to_string, decode, encode, 
-        get_added_vocab, get_special_tokens_mask, num_special_tokens_to_add,
-        set_truncation_and_padding,tokenize, vocab_size
+    :special-members: __call__, batch_decode, decode, encode, push_to_hub
+    :members:
 
 
 BatchEncoding

src/transformers/configuration_utils.py

@@ -22,7 +22,15 @@ import os
 from typing import Any, Dict, Tuple, Union
 
 from . import __version__
-from .file_utils import CONFIG_NAME, PushToHubMixin, cached_path, hf_bucket_url, is_offline_mode, is_remote_url
+from .file_utils import (
+    CONFIG_NAME,
+    PushToHubMixin,
+    cached_path,
+    copy_func,
+    hf_bucket_url,
+    is_offline_mode,
+    is_remote_url,
+)
 from .utils import logging
 
 
@@ -729,3 +737,9 @@ class PretrainedConfig(PushToHubMixin):
                 )
 
             setattr(self, k, v)
+
+
+PretrainedConfig.push_to_hub = copy_func(PretrainedConfig.push_to_hub)
+PretrainedConfig.push_to_hub.__doc__ = PretrainedConfig.push_to_hub.__doc__.format(
+    object="config", object_class="AutoConfig", object_files="configuration file"
+)

src/transformers/file_utils.py

@@ -1991,14 +1991,14 @@ class PushToHubMixin:
         use_auth_token: Optional[Union[bool, str]] = None,
     ) -> str:
         """
-        Upload model checkpoint or tokenizer files to the 🤗 Model Hub while synchronizing a local clone of the repo in
+        Upload the {object_files} to the 🤗 Model Hub while synchronizing a local clone of the repo in
         :obj:`repo_path_or_name`.
 
         Parameters:
             repo_path_or_name (:obj:`str`, `optional`):
-                Can either be a repository name for your model or tokenizer in the Hub or a path to a local folder (in
-                which case the repository will have the name of that local folder). If not specified, will default to
-                the name given by :obj:`repo_url` and a local directory with that name will be created.
+                Can either be a repository name for your {object} in the Hub or a path to a local folder (in which case
+                the repository will have the name of that local folder). If not specified, will default to the name
+                given by :obj:`repo_url` and a local directory with that name will be created.
             repo_url (:obj:`str`, `optional`):
                 Specify this in case you want to push to an existing repository in the hub. If unspecified, a new
                 repository will be created in your namespace (unless you specify an :obj:`organization`) with
@@ -2008,11 +2008,9 @@ class PushToHubMixin:
                 the current working directory. This will slow things down if you are making changes in an existing repo
                 since you will need to clone the repo before every push.
             commit_message (:obj:`str`, `optional`):
-                Message to commit while pushing. Will default to :obj:`"add config"`, :obj:`"add tokenizer"` or
-                :obj:`"add model"` depending on the type of the class.
+                Message to commit while pushing. Will default to :obj:`"add {object}"`.
             organization (:obj:`str`, `optional`):
-                Organization in which you want to push your model or tokenizer (you must be a member of this
-                organization).
+                Organization in which you want to push your {object} (you must be a member of this organization).
             private (:obj:`bool`, `optional`):
                 Whether or not the repository created should be private (requires a paying subscription).
             use_auth_token (:obj:`bool` or :obj:`str`, `optional`):
@@ -2022,29 +2020,27 @@ class PushToHubMixin:
 
 
         Returns:
-            The url of the commit of your model in the given repository.
+            :obj:`str`: The url of the commit of your {object} in the given repository.
 
         Examples::
 
-            # Upload a model to the Hub:
-            from transformers import AutoModel
+            from transformers import {object_class}
 
-            model = BertModel.from_pretrained("bert-base-cased")
-            # Fine-tuning code
+            {object} = {object_class}.from_pretrained("bert-base-cased")
 
-            # Push the model to your namespace with the name "my-finetuned-bert" and have a local clone in the
+            # Push the {object} to your namespace with the name "my-finetuned-bert" and have a local clone in the
             # `my-finetuned-bert` folder.
-            model.push_to_hub("my-finetuned-bert")
+            {object}.push_to_hub("my-finetuned-bert")
 
-            # Push the model to your namespace with the name "my-finetuned-bert" with no local clone.
-            model.push_to_hub("my-finetuned-bert", use_temp_dir=True)
+            # Push the {object} to your namespace with the name "my-finetuned-bert" with no local clone.
+            {object}.push_to_hub("my-finetuned-bert", use_temp_dir=True)
 
-            # Push the model to an organization with the name "my-finetuned-bert" and have a local clone in the
+            # Push the {object} to an organization with the name "my-finetuned-bert" and have a local clone in the
             # `my-finetuned-bert` folder.
-            model.push_to_hub("my-finetuned-bert", organization="huggingface")
+            {object}.push_to_hub("my-finetuned-bert", organization="huggingface")
 
             # Make a change to an existing repo that has been cloned locally in `my-finetuned-bert`.
-            model.push_to_hub("my-finetuned-bert", repo_url="https://huggingface.co/sgugger/my-finetuned-bert")
+            {object}.push_to_hub("my-finetuned-bert", repo_url="https://huggingface.co/sgugger/my-finetuned-bert")
         """
         if use_temp_dir:
             # Make sure we use the right `repo_name` for the `repo_url` before replacing it.

src/transformers/modeling_flax_utils.py

@@ -490,6 +490,13 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
             logger.info(f"Model pushed to the hub in this commit: {url}")
 
 
+# To update the docstring, we need to copy the method, otherwise we change the original docstring.
+FlaxPreTrainedModel.push_to_hub = copy_func(FlaxPreTrainedModel.push_to_hub)
+FlaxPreTrainedModel.push_to_hub.__doc__ = FlaxPreTrainedModel.push_to_hub.__doc__.format(
+    object="model", object_class="FlaxAutoModel", object_files="model checkpoint"
+)
+
+
 def overwrite_call_docstring(model_class, docstring):
     # copy __call__ function to be sure docstring is changed only for this function
     model_class.__call__ = copy_func(model_class.__call__)

src/transformers/modeling_tf_utils.py

@@ -36,6 +36,7 @@ from .file_utils import (
     ModelOutput,
     PushToHubMixin,
     cached_path,
+    copy_func,
     hf_bucket_url,
     is_offline_mode,
     is_remote_url,
@@ -1392,6 +1393,13 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
         return model
 
 
+# To update the docstring, we need to copy the method, otherwise we change the original docstring.
+TFPreTrainedModel.push_to_hub = copy_func(TFPreTrainedModel.push_to_hub)
+TFPreTrainedModel.push_to_hub.__doc__ = TFPreTrainedModel.push_to_hub.__doc__.format(
+    object="model", object_class="TFAutoModel", object_files="model checkpoint"
+)
+
+
 class TFConv1D(tf.keras.layers.Layer):
     """
     1D-convolutional layer as defined by Radford et al. for OpenAI GPT (and also used in GPT-2).

src/transformers/modeling_utils.py

@@ -38,6 +38,7 @@ from .file_utils import (
     ModelOutput,
     PushToHubMixin,
     cached_path,
+    copy_func,
     hf_bucket_url,
     is_offline_mode,
     is_remote_url,
@@ -1555,6 +1556,13 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
         return retrieved_modules
 
 
+# To update the docstring, we need to copy the method, otherwise we change the original docstring.
+PreTrainedModel.push_to_hub = copy_func(PreTrainedModel.push_to_hub)
+PreTrainedModel.push_to_hub.__doc__ = PreTrainedModel.push_to_hub.__doc__.format(
+    object="model", object_class="AutoModel", object_files="model checkpoint"
+)
+
+
 class Conv1D(nn.Module):
     """
     1D-convolutional layer as defined by Radford et al. for OpenAI GPT (and also used in GPT-2).

src/transformers/tokenization_utils_base.py

@@ -43,6 +43,7 @@ from .file_utils import (
     _is_torch_device,
     add_end_docstrings,
     cached_path,
+    copy_func,
     hf_bucket_url,
     is_flax_available,
     is_offline_mode,
@@ -3371,3 +3372,10 @@ For a more complete example, see the implementation of `prepare_seq2seq_batch`.
             )
         model_inputs["labels"] = labels["input_ids"]
         return model_inputs
+
+
+# To update the docstring, we need to copy the method, otherwise we change the original docstring.
+PreTrainedTokenizerBase.push_to_hub = copy_func(PreTrainedTokenizerBase.push_to_hub)
+PreTrainedTokenizerBase.push_to_hub.__doc__ = PreTrainedTokenizerBase.push_to_hub.__doc__.format(
+    object="tokenizer", object_class="AutoTokenizer", object_files="tokenizer files"
+)