113 lines
3.7 KiB
Python
113 lines
3.7 KiB
Python
# coding=utf-8
|
|
# Copyright 2022 The OpenBMB team.
|
|
#
|
|
# 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.
|
|
|
|
from typing import List, Optional, Tuple
|
|
|
|
import torch
|
|
import torch.nn.functional as F
|
|
from transformers.configuration_utils import PretrainedConfig
|
|
from typing_extensions import TypedDict
|
|
|
|
import math
|
|
|
|
|
|
class CPMDragonflyConfig(PretrainedConfig):
|
|
model_type = "cpm_dragonfly"
|
|
keys_to_ignore_at_inference = ["past_key_values"]
|
|
attribute_map = {
|
|
"scale_emb": "scale_emb",
|
|
"scale_depth": "scale_depth",
|
|
"scale": "scale",
|
|
"attention_scale": "attention_scale",
|
|
"qk_norm": "qk_norm",
|
|
"ffn_gated": "ffn_gated",
|
|
} # model specific to common
|
|
|
|
def __init__(
|
|
self,
|
|
vocab_size=32000,
|
|
hidden_size=4096,
|
|
num_attention_heads=32,
|
|
num_key_value_heads=32,
|
|
dim_head=128,
|
|
intermediate_size=11008,
|
|
num_hidden_layers=32,
|
|
dropout_p=0.0,
|
|
hidden_act="silu",
|
|
scale=True,
|
|
scale_emb: float=1.,
|
|
scale_depth: float=-1,
|
|
dim_model_base:int=None,
|
|
rms_norm_eps=1e-5,
|
|
init_std=0.02,
|
|
half: bool = True,
|
|
half_type = 'bf16',
|
|
mask_modules: Optional[List[Tuple[bool, bool]]] = None,
|
|
use_flash_attn: bool = True,
|
|
flash_attn_mask_shape="1d",
|
|
flash_impl="cuda",
|
|
base=10000,
|
|
non_checkpointing_layers_num:int = 0,
|
|
attention_scale=1,
|
|
qk_norm=False,
|
|
ffn_gated=True,
|
|
tie_lm_head=False,
|
|
max_position_embeddings=2048,
|
|
**kwargs,
|
|
):
|
|
self.vocab_size = vocab_size
|
|
self.hidden_size = hidden_size
|
|
self.num_attention_heads = num_attention_heads
|
|
self.num_key_value_heads = num_key_value_heads
|
|
self.dim_head = dim_head
|
|
self.intermediate_size = intermediate_size
|
|
self.num_hidden_layers = num_hidden_layers
|
|
self.max_position_embeddings = max_position_embeddings
|
|
self.dropout_p = dropout_p
|
|
self.hidden_act = hidden_act
|
|
self.scale = scale
|
|
self.scale_emb = scale_emb
|
|
self.half = half
|
|
self.half_type = half_type
|
|
self.dim_model_base = dim_model_base
|
|
self.scale_depth = scale_depth
|
|
self.rms_norm_eps = rms_norm_eps
|
|
self.init_std = init_std
|
|
self.flash_impl = flash_impl
|
|
self.mask_modules = mask_modules
|
|
self.use_flash_attn = use_flash_attn
|
|
self.flash_attn_mask_shape = flash_attn_mask_shape
|
|
self.base = base
|
|
self.attention_scale=attention_scale
|
|
self.qk_norm = qk_norm
|
|
self.ffn_gated = ffn_gated
|
|
self.non_checkpointing_layers_num = non_checkpointing_layers_num
|
|
self.tie_lm_head = tie_lm_head
|
|
self.use_bfloat16 = True if self.half_type == 'bf16' else False
|
|
super().__init__(architectures=["CPMDragonflyForCausalLM"])
|
|
|
|
@property
|
|
def scale_width(self,):
|
|
if self.scale:
|
|
return self.hidden_size / self.dim_model_base
|
|
else:
|
|
return 1.
|
|
|
|
@property
|
|
def scale_states(self,):
|
|
if self.scale:
|
|
return self.scale_depth / math.sqrt(self.num_hidden_layers)
|
|
else:
|
|
return 1. |