wehub-resource-sync
408 lines
16 KiB
Python
408 lines
16 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. 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.
|
|
""" BERT model configuration"""
|
|
from __future__ import annotations
|
|
|
|
from typing import Dict
|
|
|
|
from paddlenlp.transformers.configuration_utils import PretrainedConfig
|
|
|
|
__all__ = ["BERT_PRETRAINED_INIT_CONFIGURATION", "BertConfig", "BERT_PRETRAINED_RESOURCE_FILES_MAP"]
|
|
|
|
BERT_PRETRAINED_INIT_CONFIGURATION = {
|
|
"bert-base-uncased": {
|
|
"vocab_size": 30522,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-large-uncased": {
|
|
"vocab_size": 30522,
|
|
"hidden_size": 1024,
|
|
"num_hidden_layers": 24,
|
|
"num_attention_heads": 16,
|
|
"intermediate_size": 4096,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-base-multilingual-uncased": {
|
|
"vocab_size": 105879,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-base-cased": {
|
|
"vocab_size": 28996,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-base-chinese": {
|
|
"vocab_size": 21128,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-base-multilingual-cased": {
|
|
"vocab_size": 119547,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-large-cased": {
|
|
"vocab_size": 28996,
|
|
"hidden_size": 1024,
|
|
"num_hidden_layers": 24,
|
|
"num_attention_heads": 16,
|
|
"intermediate_size": 4096,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-wwm-chinese": {
|
|
"vocab_size": 21128,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"bert-wwm-ext-chinese": {
|
|
"vocab_size": 21128,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"macbert-base-chinese": {
|
|
"vocab_size": 21128,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"macbert-large-chinese": {
|
|
"vocab_size": 21128,
|
|
"hidden_size": 1024,
|
|
"num_hidden_layers": 24,
|
|
"num_attention_heads": 16,
|
|
"intermediate_size": 4096,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"simbert-base-chinese": {
|
|
"vocab_size": 13685,
|
|
"hidden_size": 768,
|
|
"num_hidden_layers": 12,
|
|
"num_attention_heads": 12,
|
|
"intermediate_size": 3072,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"max_position_embeddings": 512,
|
|
"type_vocab_size": 2,
|
|
"initializer_range": 0.02,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-base": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 768,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 3072,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 12,
|
|
"num_hidden_layers": 12,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-medium": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 512,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 2048,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 8,
|
|
"num_hidden_layers": 8,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-6l-768h": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 768,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 3072,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 12,
|
|
"num_hidden_layers": 6,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-small": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 512,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 2048,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 8,
|
|
"num_hidden_layers": 4,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-mini": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 256,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 1024,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 4,
|
|
"num_hidden_layers": 4,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
"uer/chinese-roberta-tiny": {
|
|
"attention_probs_dropout_prob": 0.1,
|
|
"hidden_act": "gelu",
|
|
"hidden_dropout_prob": 0.1,
|
|
"hidden_size": 128,
|
|
"initializer_range": 0.02,
|
|
"intermediate_size": 512,
|
|
"max_position_embeddings": 512,
|
|
"num_attention_heads": 2,
|
|
"num_hidden_layers": 2,
|
|
"type_vocab_size": 2,
|
|
"vocab_size": 21128,
|
|
"pad_token_id": 0,
|
|
},
|
|
}
|
|
|
|
BERT_PRETRAINED_RESOURCE_FILES_MAP = {
|
|
"model_state": {
|
|
"bert-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/bert-base-uncased.pdparams",
|
|
"bert-large-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/bert-large-uncased.pdparams",
|
|
"bert-base-multilingual-uncased": "http://bj.bcebos.com/paddlenlp/models/transformers/bert-base-multilingual-uncased.pdparams",
|
|
"bert-base-cased": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-base-cased.pdparams",
|
|
"bert-base-chinese": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-base-chinese.pdparams",
|
|
"bert-base-multilingual-cased": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-base-multilingual-cased.pdparams",
|
|
"bert-large-cased": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-large-cased.pdparams",
|
|
"bert-wwm-chinese": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-wwm-chinese.pdparams",
|
|
"bert-wwm-ext-chinese": "http://bj.bcebos.com/paddlenlp/models/transformers/bert/bert-wwm-ext-chinese.pdparams",
|
|
"macbert-base-chinese": "https://bj.bcebos.com/paddlenlp/models/transformers/macbert/macbert-base-chinese.pdparams",
|
|
"macbert-large-chinese": "https://bj.bcebos.com/paddlenlp/models/transformers/macbert/macbert-large-chinese.pdparams",
|
|
"simbert-base-chinese": "https://bj.bcebos.com/paddlenlp/models/transformers/simbert/simbert-base-chinese-v1.pdparams",
|
|
"uer/chinese-roberta-base": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_base.pdparams",
|
|
"uer/chinese-roberta-medium": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_medium.pdparams",
|
|
"uer/chinese-roberta-6l-768h": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_6l_768h.pdparams",
|
|
"uer/chinese-roberta-small": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_small.pdparams",
|
|
"uer/chinese-roberta-mini": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_mini.pdparams",
|
|
"uer/chinese-roberta-tiny": "https://bj.bcebos.com/paddlenlp/models/transformers/uer/chinese_roberta_tiny.pdparams",
|
|
}
|
|
}
|
|
|
|
|
|
class BertConfig(PretrainedConfig):
|
|
r"""
|
|
This is the configuration class to store the configuration of a [`BertModel`] or a [`TFBertModel`]. It is used to
|
|
instantiate a BERT 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 BERT
|
|
bert-base-uncased architecture.
|
|
|
|
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
|
documentation from [`PretrainedConfig`] for more information.
|
|
|
|
|
|
Args:
|
|
vocab_size (`int`, *optional*, defaults to 30522):
|
|
Vocabulary size of the BERT model. Defines the number of different tokens that can be represented by the
|
|
`inputs_ids` passed when calling [`BertModel`] or [`TFBertModel`].
|
|
hidden_size (`int`, *optional*, defaults to 768):
|
|
Dimensionality of the encoder layers and the pooler layer.
|
|
num_hidden_layers (`int`, *optional*, defaults to 12):
|
|
Number of hidden layers in the Transformer encoder.
|
|
num_attention_heads (`int`, *optional*, defaults to 12):
|
|
Number of attention heads for each attention layer in the Transformer encoder.
|
|
intermediate_size (`int`, *optional*, defaults to 3072):
|
|
Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
|
|
hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu"`):
|
|
The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
|
|
`"relu"`, `"silu"` and `"gelu_new"` are supported.
|
|
hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
|
|
The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
|
|
attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
|
|
The dropout ratio for the attention probabilities.
|
|
max_position_embeddings (`int`, *optional*, defaults to 512):
|
|
The maximum sequence length that this model might ever be used with. Typically set this to something large
|
|
just in case (e.g., 512 or 1024 or 2048).
|
|
type_vocab_size (`int`, *optional*, defaults to 2):
|
|
The vocabulary size of the `token_type_ids` passed when calling [`BertModel`] or [`TFBertModel`].
|
|
initializer_range (`float`, *optional*, defaults to 0.02):
|
|
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
|
layer_norm_eps (`float`, *optional*, defaults to 1e-12):
|
|
The epsilon used by the layer normalization layers.
|
|
position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
|
|
Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For
|
|
positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to
|
|
[Self-Attention with Relative Position Representations (Shaw et al.)](https://arxiv.org/abs/1803.02155).
|
|
For more information on `"relative_key_query"`, please refer to *Method 4* in [Improve Transformer Models
|
|
with Better Relative Position Embeddings (Huang et al.)](https://arxiv.org/abs/2009.13658).
|
|
use_cache (`bool`, *optional*, defaults to `True`):
|
|
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
|
relevant if `config.is_decoder=True`.
|
|
classifier_dropout (`float`, *optional*):
|
|
The dropout ratio for the classification head.
|
|
|
|
Examples:
|
|
|
|
```python
|
|
>>> from paddlenlp.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
|
|
```"""
|
|
model_type = "bert"
|
|
attribute_map: Dict[str, str] = {"dropout": "classifier_dropout", "num_classes": "num_labels"}
|
|
pretrained_init_configuration = BERT_PRETRAINED_INIT_CONFIGURATION
|
|
|
|
def __init__(
|
|
self,
|
|
vocab_size: int = 30522,
|
|
hidden_size: int = 768,
|
|
num_hidden_layers: int = 12,
|
|
num_attention_heads: int = 12,
|
|
intermediate_size: int = 3072,
|
|
hidden_act: str = "gelu",
|
|
hidden_dropout_prob: float = 0.1,
|
|
attention_probs_dropout_prob: float = 0.1,
|
|
max_position_embeddings: int = 512,
|
|
type_vocab_size: int = 16,
|
|
initializer_range: float = 0.02,
|
|
pad_token_id: int = 0,
|
|
pool_act: str = "tanh",
|
|
fuse: bool = False,
|
|
layer_norm_eps=1e-12,
|
|
use_cache=False,
|
|
**kwargs
|
|
):
|
|
super().__init__(pad_token_id=pad_token_id, **kwargs)
|
|
self.vocab_size = vocab_size
|
|
self.hidden_size = hidden_size
|
|
self.num_hidden_layers = num_hidden_layers
|
|
self.num_attention_heads = num_attention_heads
|
|
self.intermediate_size = intermediate_size
|
|
self.hidden_act = hidden_act
|
|
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.pool_act = pool_act
|
|
self.fuse = fuse
|
|
|
|
self.layer_norm_eps = layer_norm_eps
|
|
self.use_cache = use_cache
|