wehub-resource-sync
199 lines
8.1 KiB
Python
199 lines
8.1 KiB
Python
# Copyright (c) 2023 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.
|
|
""" ErnieCode model configuration"""
|
|
from __future__ import annotations
|
|
|
|
from typing import Dict
|
|
|
|
from paddlenlp.transformers.configuration_utils import PretrainedConfig
|
|
|
|
__all__ = ["ERNIECODE_PRETRAINED_INIT_CONFIGURATION", "ErnieCodeConfig", "ERNIECODE_PRETRAINED_RESOURCE_FILES_MAP"]
|
|
|
|
ERNIECODE_PRETRAINED_INIT_CONFIGURATION = {
|
|
"ernie-code-base": {
|
|
"d_ff": 2048,
|
|
"d_kv": 64,
|
|
"d_model": 768,
|
|
"decoder_start_token_id": 0,
|
|
"dense_act_fn": "gelu_new",
|
|
"dropout_rate": 0.1,
|
|
"enable_recompute": False,
|
|
"eos_token_id": 1,
|
|
"feed_forward_proj": "gated-gelu",
|
|
"initializer_factor": 1.0,
|
|
"is_encoder_decoder": True,
|
|
"is_gated_act": True,
|
|
"layer_norm_epsilon": 1e-06,
|
|
"model_type": "ErnieCode",
|
|
"num_decoder_layers": 12,
|
|
"num_heads": 12,
|
|
"num_layers": 12,
|
|
"output_past": True,
|
|
"pad_token_id": 0,
|
|
"relative_attention_max_distance": 128,
|
|
"relative_attention_num_buckets": 32,
|
|
"tie_word_embeddings": False,
|
|
"tokenizer_class": "ErnieCodeTokenizer",
|
|
"transformers_version": "4.20.1",
|
|
"use_cache": True,
|
|
"vocab_size": 250105,
|
|
},
|
|
"ernie-code-base-L512": {
|
|
"d_ff": 2048,
|
|
"d_kv": 64,
|
|
"d_model": 768,
|
|
"decoder_start_token_id": 0,
|
|
"dense_act_fn": "gelu_new",
|
|
"dropout_rate": 0.1,
|
|
"enable_recompute": False,
|
|
"eos_token_id": 1,
|
|
"feed_forward_proj": "gated-gelu",
|
|
"initializer_factor": 1.0,
|
|
"is_encoder_decoder": True,
|
|
"is_gated_act": True,
|
|
"layer_norm_epsilon": 1e-06,
|
|
"model_type": "ErnieCode",
|
|
"num_decoder_layers": 12,
|
|
"num_heads": 12,
|
|
"num_layers": 12,
|
|
"output_past": True,
|
|
"pad_token_id": 0,
|
|
"relative_attention_max_distance": 128,
|
|
"relative_attention_num_buckets": 32,
|
|
"tie_word_embeddings": False,
|
|
"tokenizer_class": "ErnieCodeTokenizer",
|
|
"transformers_version": "4.20.1",
|
|
"use_cache": True,
|
|
"vocab_size": 250105,
|
|
},
|
|
}
|
|
|
|
ERNIECODE_PRETRAINED_RESOURCE_FILES_MAP = {
|
|
"model_state": {
|
|
"ernie-code-base": "https://bj.bcebos.com/paddlenlp/models/transformers/ernie-code/ernie-code-base/model_state.pdparams",
|
|
"ernie-code-base-L512": "https://bj.bcebos.com/paddlenlp/models/transformers/ernie-code/ernie-code-base-L512/model_state.pdparams",
|
|
}
|
|
}
|
|
|
|
|
|
class ErnieCodeConfig(PretrainedConfig):
|
|
r"""
|
|
This is the configuration class to store the configuration of a [`ErnieCodeModel`]. It is used to
|
|
instantiate a bert model according to the specified arguments, defining the model 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 250112):
|
|
Vocabulary size of the ErnieCode model. Defines the number of different tokens that can be represented by the
|
|
`inputs_ids` passed when calling [`ErnieCodeModel`].
|
|
d_model (`int`, *optional*, defaults to 512):
|
|
Size of the encoder layers and the pooler layer.
|
|
d_kv (`int`, *optional*, defaults to 64):
|
|
Size of the key, query, value projections per attention head. `d_kv` has to be equal to `d_model //
|
|
num_heads`.
|
|
d_ff (`int`, *optional*, defaults to 1024):
|
|
Size of the intermediate feed forward layer in each `ErnieCodeBlock`.
|
|
num_layers (`int`, *optional*, defaults to 8):
|
|
Number of hidden layers in the Transformer encoder.
|
|
num_decoder_layers (`int`, *optional*):
|
|
Number of hidden layers in the Transformer decoder. Will use the same value as `num_layers` if not set.
|
|
num_heads (`int`, *optional*, defaults to 6):
|
|
Number of attention heads for each attention layer in the Transformer encoder.
|
|
relative_attention_num_buckets (`int`, *optional*, defaults to 32):
|
|
The number of buckets to use for each attention layer.
|
|
relative_attention_max_distance (`int`, *optional*, defaults to 128):
|
|
The maximum distance of the longer sequences for the bucket separation.
|
|
dropout_rate (`float`, *optional*, defaults to 0.1):
|
|
The ratio for all dropout layers.
|
|
layer_norm_eps (`float`, *optional*, defaults to 1e-6):
|
|
The epsilon used by the layer normalization layers.
|
|
initializer_factor (`float`, *optional*, defaults to 1):
|
|
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
|
|
testing).
|
|
feed_forward_proj (`string`, *optional*, defaults to `"gated-gelu"`):
|
|
he non-linear activation function (function or string) in the feed forward layer in the residual attention block.
|
|
If string, `"relu"`, `"gated-gelu"` are supported. Defaults to `"gated-gelu"`.
|
|
use_cache (`bool`, *optional*, defaults to `True`):
|
|
Whether or not the model should return the last key/values attentions (not used by all models).
|
|
pad_token_id (int, optional):
|
|
The id of the `padding` token. Defaults to `0`.
|
|
bos_token_id (int, optional):
|
|
The id of the `bos` token. Defaults to `0`.
|
|
eos_token_id (int, optional):
|
|
The id of the `eos` token. Defaults to `1`.
|
|
enable_recompute (bool, optional):
|
|
Whether to recompute cache.
|
|
|
|
"""
|
|
model_type = "ErnieCode"
|
|
attribute_map: Dict[str, str] = {
|
|
"hidden_size": "d_model",
|
|
"num_attention_heads": "num_heads",
|
|
"num_hidden_layers": "num_layers",
|
|
"num_classes": "num_labels",
|
|
}
|
|
pretrained_init_configuration = ERNIECODE_PRETRAINED_INIT_CONFIGURATION
|
|
|
|
def __init__(
|
|
self,
|
|
vocab_size: int = 250112,
|
|
d_model: int = 512,
|
|
d_kv: int = 64,
|
|
d_ff: int = 1024,
|
|
num_layers: int = 8,
|
|
num_decoder_layers: int = None,
|
|
num_heads: int = 6,
|
|
relative_attention_num_buckets: int = 32,
|
|
relative_attention_max_distance: int = 128,
|
|
dropout_rate: float = 0.1,
|
|
layer_norm_epsilon: float = 1e-6,
|
|
initializer_factor: float = 1.0,
|
|
feed_forward_proj: str = "gated-gelu",
|
|
is_encoder_decoder: bool = True,
|
|
use_cache: bool = True,
|
|
bos_token_id: int = 0,
|
|
pad_token_id: int = 0,
|
|
eos_token_id: int = 1,
|
|
enable_recompute: bool = False,
|
|
**kwargs
|
|
):
|
|
|
|
super().__init__(
|
|
bos_token_id=bos_token_id,
|
|
pad_token_id=pad_token_id,
|
|
eos_token_id=eos_token_id,
|
|
is_encoder_decoder=is_encoder_decoder,
|
|
**kwargs,
|
|
)
|
|
self.enable_recompute = enable_recompute
|
|
self.vocab_size = vocab_size
|
|
self.d_model = d_model
|
|
self.d_kv = d_kv
|
|
self.d_ff = d_ff
|
|
self.num_layers = num_layers
|
|
self.num_decoder_layers = (
|
|
num_decoder_layers if num_decoder_layers is not None else self.num_layers
|
|
) # default = symmetry
|
|
self.num_heads = num_heads
|
|
self.relative_attention_num_buckets = relative_attention_num_buckets
|
|
self.relative_attention_max_distance = relative_attention_max_distance
|
|
self.dropout_rate = dropout_rate
|
|
self.layer_norm_epsilon = layer_norm_epsilon
|
|
self.initializer_factor = initializer_factor
|
|
self.feed_forward_proj = feed_forward_proj
|
|
self.use_cache = use_cache
|