# 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. """ GPT model configuration""" from __future__ import annotations from typing import Dict from paddlenlp.transformers.configuration_utils import PretrainedConfig __all__ = ["GPT_PRETRAINED_INIT_CONFIGURATION", "GPTConfig", "GPT_PRETRAINED_RESOURCE_FILES_MAP"] GPT_PRETRAINED_INIT_CONFIGURATION = { "gpt-cpm-large-cn": { # 2.6B "vocab_size": 30000, "hidden_size": 2560, "num_hidden_layers": 32, "num_attention_heads": 32, "intermediate_size": 10240, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "pad_token_id": 0, "eos_token_id": 7, "bos_token_id": 0, "eol_token_id": 3, }, "gpt-cpm-small-cn-distill": { # 109M "vocab_size": 30000, "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": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "pad_token_id": 0, "eos_token_id": 7, "bos_token_id": 0, "eol_token_id": 3, }, "gpt3-13B-en": { # 13B "vocab_size": 50304, "hidden_size": 5120, "num_hidden_layers": 40, "num_attention_heads": 128, "intermediate_size": 20480, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt3-1.3B-en": { # 1.3B "vocab_size": 50304, "hidden_size": 2048, "num_hidden_layers": 24, "num_attention_heads": 16, "intermediate_size": 8192, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt2-xl-en": { # 1558M "vocab_size": 50257, "hidden_size": 1600, "num_hidden_layers": 48, "num_attention_heads": 25, "intermediate_size": 6400, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt2-large-en": { # 774M "vocab_size": 50257, "hidden_size": 1280, "num_hidden_layers": 36, "num_attention_heads": 20, "intermediate_size": 5120, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt2-medium-en": { # 345M "vocab_size": 50304, "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": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt2-en": { # 117M "vocab_size": 50257, "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": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, "gpt2-small-en": { # config for CE "vocab_size": 50304, "hidden_size": 1024, "num_hidden_layers": 4, "num_attention_heads": 4, "intermediate_size": 4096, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "max_position_embeddings": 1024, "type_vocab_size": 1, # no use "initializer_range": 0.02, "eos_token_id": 50256, "eol_token_id": 198, }, } GPT_PRETRAINED_RESOURCE_FILES_MAP = { "model_state": { "gpt-cpm-large-cn": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt-cpm-large-cn.pdparams", "gpt-cpm-small-cn-distill": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt-cpm-small-cn-distill.pdparams", "gpt2-en": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt2-en.pdparams", "gpt2-medium-en": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt2-medium-en.pdparams", "gpt2-large-en": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt2-large-en.pdparams", "gpt2-xl-en": "https://bj.bcebos.com/paddlenlp/models/transformers/gpt/gpt2-xl-en.pdparams", } } class GPTConfig(PretrainedConfig): r""" This is the configuration class to store the configuration of a [`GPTModel`] or a [`TFGPTModel`]. It is used to instantiate a GPT 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 GPT gpt-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 GPT model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`GPTModel`] or [`TFGPTModel`]. 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 [`GPTModel`] or [`TFGPTModel`]. 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 GPTModel, GPTConfig >>> # Initializing a GPT gpt-base-uncased style configuration >>> configuration = GPTConfig() >>> # Initializing a model from the gpt-base-uncased style configuration >>> model = GPTModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "gpt" attribute_map: Dict[str, str] = { "num_classes": "num_labels", "dropout": "classifier_dropout", "n_positions": "max_position_embeddings", "n_embd": "hidden_size", "n_layer": "num_hidden_layers", "n_head": "num_attention_heads", "n_inner": "intermediate_size", "activation_function": "hidden_act", "resid_pdrop": "attention_probs_dropout_prob", } pretrained_init_configuration = GPT_PRETRAINED_INIT_CONFIGURATION def __init__( self, vocab_size: int = 50304, 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, eos_token_id: int = 7, bos_token_id: int = 0, eol_token_id: int = 3, topo: int = None, **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.pad_token_id = pad_token_id self.eos_token_id = eos_token_id self.bos_token_id = bos_token_id self.eol_token_id = eol_token_id self.topo = topo