From 387217bd3e9a564cd84d4c4cc3c2f25ce30966bc Mon Sep 17 00:00:00 2001 From: Lysandre Date: Mon, 13 Jan 2020 13:27:34 +0100 Subject: [PATCH] Added example usage --- docs/source/model_doc/xlnet.rst | 4 ++-- src/transformers/configuration_bert.py | 17 +++++++++++++++++ src/transformers/configuration_camembert.py | 17 +++++++++++++++++ src/transformers/configuration_ctrl.py | 17 +++++++++++++++++ src/transformers/configuration_distilbert.py | 17 +++++++++++++++++ src/transformers/configuration_gpt2.py | 17 +++++++++++++++++ src/transformers/configuration_openai.py | 17 +++++++++++++++++ src/transformers/configuration_transfo_xl.py | 17 +++++++++++++++++ src/transformers/configuration_xlm.py | 19 ++++++++++++++++++- src/transformers/configuration_xlnet.py | 19 ++++++++++++++++++- 10 files changed, 157 insertions(+), 4 deletions(-) diff --git a/docs/source/model_doc/xlnet.rst b/docs/source/model_doc/xlnet.rst index 10f06b76ad..0317fa0d78 100644 --- a/docs/source/model_doc/xlnet.rst +++ b/docs/source/model_doc/xlnet.rst @@ -39,14 +39,14 @@ XLNet ``XLNetForTokenClassification`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -.. autoclass:: transformers.XLNetForTokenClassification` +.. autoclass:: transformers.XLNetForTokenClassification :members: ``XLNetForMultipleChoice`` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -.. autoclass:: transformers.XLNetForMultipleChoice` +.. autoclass:: transformers.XLNetForMultipleChoice :members: diff --git a/src/transformers/configuration_bert.py b/src/transformers/configuration_bert.py index 62bc43f46e..c61fc418b7 100644 --- a/src/transformers/configuration_bert.py +++ b/src/transformers/configuration_bert.py @@ -88,6 +88,23 @@ class BertConfig(PretrainedConfig): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (:obj:`float`, optional, defaults to 1e-12): The epsilon used by the layer normalization layers. + + Example:: + + from transformers import BertModel, BertConfig + + # Initializing a BERT bert-base-uncased style configuration + configuration = BertConfig() + + # Initializing a model from the bert-base-uncased style configuration + model = BertModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = BERT_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_camembert.py b/src/transformers/configuration_camembert.py index 0063e4ada3..6765fd61b1 100644 --- a/src/transformers/configuration_camembert.py +++ b/src/transformers/configuration_camembert.py @@ -41,5 +41,22 @@ class CamembertConfig(RobertaConfig): The :class:`~transformers.CamembertConfig` class directly inherits :class:`~transformers.BertConfig`. It reuses the same defaults. Please check the parent class for more information. + + Example:: + + from transformers import CamembertModel, CamembertConfig + + # Initializing a CamemBERT configuration + configuration = CamembertConfig() + + # Initializing a model from the configuration + model = CamembertModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_ctrl.py b/src/transformers/configuration_ctrl.py index 446ebffed7..ea1e861a18 100644 --- a/src/transformers/configuration_ctrl.py +++ b/src/transformers/configuration_ctrl.py @@ -63,6 +63,23 @@ class CTRLConfig(PretrainedConfig): The epsilon to use in the layer normalization layers initializer_range (:obj:`float`, optional, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + + Example:: + + from transformers import CTRLModel, CTRLConfig + + # Initializing a CTRL configuration + configuration = CTRLConfig() + + # Initializing a model from the configuration + model = CTRLModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_distilbert.py b/src/transformers/configuration_distilbert.py index ffad013704..a2f541b679 100644 --- a/src/transformers/configuration_distilbert.py +++ b/src/transformers/configuration_distilbert.py @@ -74,6 +74,23 @@ class DistilBertConfig(PretrainedConfig): seq_classif_dropout (:obj:`float`, optional, defaults to 0.2): The dropout probabilities used in the sequence classification model :class:`~tranformers.DistilBertForSequenceClassification`. + + Example:: + + from transformers import DistilBertModel, DistilBertConfig + + # Initializing a DistilBERT configuration + configuration = DistilBertConfig() + + # Initializing a model from the configuration + model = DistilBertModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_gpt2.py b/src/transformers/configuration_gpt2.py index 2b9042bd75..26315fd1e3 100644 --- a/src/transformers/configuration_gpt2.py +++ b/src/transformers/configuration_gpt2.py @@ -94,6 +94,23 @@ class GPT2Config(PretrainedConfig): Argument used when doing sequence summary. Used in for the multiple choice head in :class:`~transformers.GPT2DoubleHeadsModel`. Add a dropout before the projection and activation + + Example:: + + from transformers import GPT2Model, GPT2Config + + # Initializing a GPT2 configuration + configuration = GPT2Config() + + # Initializing a model from the configuration + model = GPT2Model(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_openai.py b/src/transformers/configuration_openai.py index e6fc1efce3..f55c922209 100644 --- a/src/transformers/configuration_openai.py +++ b/src/transformers/configuration_openai.py @@ -94,6 +94,23 @@ class OpenAIGPTConfig(PretrainedConfig): Argument used when doing sequence summary. Used in for the multiple choice head in :class:`~transformers.OpenAIGPTDoubleHeadsModel`. Add a dropout before the projection and activation + + Example:: + + from transformers import OpenAIGPTConfig, OpenAIGPTModel + + # Initializing a GPT configuration + configuration = OpenAIGPTConfig() + + # Initializing a model from the configuration + model = OpenAIGPTModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_transfo_xl.py b/src/transformers/configuration_transfo_xl.py index e4052408d2..d1f2ab42ee 100644 --- a/src/transformers/configuration_transfo_xl.py +++ b/src/transformers/configuration_transfo_xl.py @@ -97,6 +97,23 @@ class TransfoXLConfig(PretrainedConfig): Parameters initialized by N(0, init_std) layer_norm_epsilon (:obj:`float`, optional, defaults to 1e-5): The epsilon to use in the layer normalization layers + + Example:: + + from transformers import TransfoXLConfig, TransfoXLModel + + # Initializing a Transformer XL configuration + configuration = TransfoXLConfig() + + # Initializing a model from the configuration + model = TransfoXLModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_xlm.py b/src/transformers/configuration_xlm.py index 3dc26047d8..c34c93ebde 100644 --- a/src/transformers/configuration_xlm.py +++ b/src/transformers/configuration_xlm.py @@ -129,7 +129,7 @@ class XLMConfig(PretrainedConfig): :class:`~transformers.XLMForSequenceClassification`. Add a dropout before the projection and activation start_n_top (:obj:`int`, optional, defaults to 5): - Used in the SQuAD evaluation script for XLM and XLNetV. + Used in the SQuAD evaluation script for XLM and XLNet. end_n_top (:obj:`int`, optional, defaults to 5): Used in the SQuAD evaluation script for XLM and XLNet. mask_token_id (:obj:`int`, optional, defaults to 0): @@ -137,6 +137,23 @@ class XLMConfig(PretrainedConfig): lang_id (:obj:`int`, optional, defaults to 1): The ID of the language used by the model. This parameter is used when generating text in a given language. + + Example:: + + from transformers import XLMConfig, XLMModel + + # Initializing a XLM configuration + configuration = XLMConfig() + + # Initializing a model from the configuration + model = XLMModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = XLM_PRETRAINED_CONFIG_ARCHIVE_MAP diff --git a/src/transformers/configuration_xlnet.py b/src/transformers/configuration_xlnet.py index 7fe427344d..24da0ca7c7 100644 --- a/src/transformers/configuration_xlnet.py +++ b/src/transformers/configuration_xlnet.py @@ -106,9 +106,26 @@ class XLNetConfig(PretrainedConfig): :class:`~transformers.XLNetForSequenceClassification` and :class:`~transformers.XLNetForMultipleChoice`. Add a dropout after the projection and activation start_n_top (:obj:`int`, optional, defaults to 5): - Used in the SQuAD evaluation script for XLM and XLNetV. + Used in the SQuAD evaluation script for XLM and XLNet. end_n_top (:obj:`int`, optional, defaults to 5): Used in the SQuAD evaluation script for XLM and XLNet. + + Example:: + + from transformers import XLNetConfig, XLNetModel + + # Initializing a XLNet configuration + configuration = XLNetConfig() + + # Initializing a model from the configuration + model = XLNetModel(configuration) + + # Accessing the model configuration + configuration = model.config + + Attributes: + pretrained_config_archive_map (Dict[str, str]): + A dictionary containing all the available pre-trained checkpoints. """ pretrained_config_archive_map = XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP