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| # coding=utf-8 | |
| # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. | |
| # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """ ALBERT model configuration """ | |
| from transformers.configuration_utils import PretrainedConfig | |
| ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = { | |
| "albert-base-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-base-config.json", | |
| "albert-large-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-large-config.json", | |
| "albert-xlarge-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xlarge-config.json", | |
| "albert-xxlarge-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xxlarge-config.json", | |
| "albert-base-v2": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-base-v2-config.json", | |
| "albert-large-v2": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-large-v2-config.json", | |
| "albert-xlarge-v2": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xlarge-v2-config.json", | |
| "albert-xxlarge-v2": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xxlarge-v2-config.json", | |
| } | |
| class AlbertConfig(PretrainedConfig): | |
| r""" | |
| This is the configuration class to store the configuration of an :class:`~transformers.AlbertModel`. | |
| It is used to instantiate an ALBERT model according to the specified arguments, defining the model | |
| architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of | |
| the ALBERT `xxlarge <https://huggingface.co/albert-xxlarge-v2>`__ architecture. | |
| Configuration objects inherit from :class:`~transformers.PretrainedConfig` and can be used | |
| to control the model outputs. Read the documentation from :class:`~transformers.PretrainedConfig` | |
| for more information. | |
| Args: | |
| vocab_size (:obj:`int`, optional, defaults to 30000): | |
| Vocabulary size of the ALBERT model. Defines the different tokens that | |
| can be represented by the `inputs_ids` passed to the forward method of :class:`~transformers.AlbertModel`. | |
| embedding_size (:obj:`int`, optional, defaults to 128): | |
| Dimensionality of vocabulary embeddings. | |
| hidden_size (:obj:`int`, optional, defaults to 4096): | |
| Dimensionality of the encoder layers and the pooler layer. | |
| num_hidden_layers (:obj:`int`, optional, defaults to 12): | |
| Number of hidden layers in the Transformer encoder. | |
| num_hidden_groups (:obj:`int`, optional, defaults to 1): | |
| Number of groups for the hidden layers, parameters in the same group are shared. | |
| num_attention_heads (:obj:`int`, optional, defaults to 64): | |
| Number of attention heads for each attention layer in the Transformer encoder. | |
| intermediate_size (:obj:`int`, optional, defaults to 16384): | |
| The dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. | |
| inner_group_num (:obj:`int`, optional, defaults to 1): | |
| The number of inner repetition of attention and ffn. | |
| hidden_act (:obj:`str` or :obj:`function`, optional, defaults to "gelu_new"): | |
| The non-linear activation function (function or string) in the encoder and pooler. | |
| If string, "gelu", "relu", "swish" and "gelu_new" are supported. | |
| hidden_dropout_prob (:obj:`float`, optional, defaults to 0): | |
| The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. | |
| attention_probs_dropout_prob (:obj:`float`, optional, defaults to 0): | |
| The dropout ratio for the attention probabilities. | |
| max_position_embeddings (:obj:`int`, optional, defaults to 512): | |
| The maximum sequence length that this model might ever be used with. Typically set this to something | |
| large (e.g., 512 or 1024 or 2048). | |
| type_vocab_size (:obj:`int`, optional, defaults to 2): | |
| The vocabulary size of the `token_type_ids` passed into :class:`~transformers.AlbertModel`. | |
| initializer_range (:obj:`float`, optional, defaults to 0.02): | |
| 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. | |
| classifier_dropout_prob (:obj:`float`, optional, defaults to 0.1): | |
| The dropout ratio for attached classifiers. | |
| Example:: | |
| from transformers import AlbertConfig, AlbertModel | |
| # Initializing an ALBERT-xxlarge style configuration | |
| albert_xxlarge_configuration = AlbertConfig() | |
| # Initializing an ALBERT-base style configuration | |
| albert_base_configuration = AlbertConfig( | |
| hidden_size=768, | |
| num_attention_heads=12, | |
| intermediate_size=3072, | |
| ) | |
| # Initializing a model from the ALBERT-base style configuration | |
| model = AlbertModel(albert_xxlarge_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 = ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP | |
| model_type = "albert" | |
| def __init__( | |
| self, | |
| vocab_size=30000, | |
| embedding_size=128, | |
| hidden_size=4096, | |
| num_hidden_layers=12, | |
| num_hidden_groups=1, | |
| num_attention_heads=64, | |
| intermediate_size=16384, | |
| inner_group_num=1, | |
| hidden_act="gelu_new", | |
| hidden_dropout_prob=0, | |
| attention_probs_dropout_prob=0, | |
| max_position_embeddings=512, | |
| type_vocab_size=2, | |
| initializer_range=0.02, | |
| layer_norm_eps=1e-12, | |
| classifier_dropout_prob=0.1, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.vocab_size = vocab_size | |
| self.embedding_size = embedding_size | |
| self.hidden_size = hidden_size | |
| self.num_hidden_layers = num_hidden_layers | |
| self.num_hidden_groups = num_hidden_groups | |
| self.num_attention_heads = num_attention_heads | |
| self.inner_group_num = inner_group_num | |
| self.hidden_act = hidden_act | |
| self.intermediate_size = intermediate_size | |
| self.hidden_dropout_prob = hidden_dropout_prob | |
| self.attention_probs_dropout_prob = attention_probs_dropout_prob | |
| self.max_position_embeddings = max_position_embeddings | |
| self.type_vocab_size = type_vocab_size | |
| self.initializer_range = initializer_range | |
| self.layer_norm_eps = layer_norm_eps | |
| self.classifier_dropout_prob = classifier_dropout_prob | |