mirror of
https://github.com/RYDE-WORK/MiniCPM.git
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118 lines
3.6 KiB
Python
118 lines
3.6 KiB
Python
# coding=utf-8
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# Copyright 2022 The OpenBMB team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import List
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from typing import Optional
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from typing import Tuple
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import torch
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import torch.nn.functional as F
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from typing_extensions import TypedDict
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from transformers.configuration_utils import PretrainedConfig
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class CPMDragonflyConfig(PretrainedConfig):
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model_type = "cpmdragonfly"
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keys_to_ignore_at_inference = ["past_key_values"]
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attribute_map = {
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"num_key_value_heads": "num_kv_heads",
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"hidden_act": "activate_fn",
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"hidden_size": "dim_model",
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"num_attention_heads": "num_heads",
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"intermediate_size": "dim_ff",
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"num_hidden_layers": "num_layers",
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"vocab_size": "vocab_size",
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"rms_norm_eps": "eps",
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"scale_emb": "scale_emb",
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"scale_depth": "scale_depth",
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"scale": "scale",
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"attention_scale": "attention_scale"
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}
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def __init__(
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self,
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vocab_size=32000,
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dim_model=4096,
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num_heads=32,
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num_kv_heads=32,
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dim_head=128,
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dim_ff=11008,
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num_layers=32,
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dropout_p=0.0,
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activate_fn="silu",
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scale=True,
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scale_emb: float=1.,
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scale_depth: float=-1,
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dim_model_base:int=None,
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eps=1e-5,
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init_std=0.02,
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half: bool = True,
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half_type = 'bf16',
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mask_modules: Optional[List[Tuple[bool, bool]]] = None,
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use_flash_attn: bool = True,
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flash_attn_mask_shape="1d",
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flash_impl="cuda",
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base=10000,
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non_checkpointing_layers_num:int = 0,
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attention_scale=1,
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max_position_embeddings=8192,
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rope_scaling=None,
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**kwargs,
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):
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self.vocab_size = vocab_size
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self.dim_model = dim_model
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self.num_heads = num_heads
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self.num_kv_heads = num_kv_heads
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self.dim_head = dim_head
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self.dim_ff = dim_ff
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self.num_layers = num_layers
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self.dropout_p = dropout_p
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self.activate_fn = activate_fn
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self.scale = scale
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self.scale_emb = scale_emb
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self.half = half
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self.half_type = half_type
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self.dim_model_base = dim_model_base
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self.scale_depth = scale_depth
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self.eps = eps
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self.init_std = init_std
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self.flash_impl = flash_impl
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self.mask_modules = mask_modules
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self.use_flash_attn = use_flash_attn
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self.flash_attn_mask_shape = flash_attn_mask_shape
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self.base = base
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self.attention_scale=attention_scale
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self.max_position_embeddings = max_position_embeddings
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self.non_checkpointing_layers_num = non_checkpointing_layers_num
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self.rope_scaling = rope_scaling
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super().__init__(architectures=["CPMDragonflyForCausalLM"])
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@property
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def scale_width(self,):
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if self.scale:
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return self.dim_model / self.dim_model_base
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else:
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return 1.
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@property
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def dtype(self, ):
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if self.half:
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if self.half_type == 'bf16':
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return torch.bfloat16
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else:
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return torch.half
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else:
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return torch.float
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