Upload configuration_codegen.py
Browse files- configuration_codegen.py +87 -0
configuration_codegen.py
ADDED
|
@@ -0,0 +1,87 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2021 The EleutherAI and HuggingFace Teams. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
# Modified configuration implementation based on https://github.com/huggingface/transformers/blob/main/src/transformers/models/gptj/configuration_gptj.py
|
| 17 |
+
|
| 18 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 19 |
+
from transformers.utils import logging
|
| 20 |
+
|
| 21 |
+
logger = logging.get_logger(__name__)
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
class CodeGenConfig(PretrainedConfig):
|
| 25 |
+
model_type = "codegen"
|
| 26 |
+
|
| 27 |
+
def __init__(
|
| 28 |
+
self,
|
| 29 |
+
vocab_size=50400,
|
| 30 |
+
n_positions=2048,
|
| 31 |
+
n_ctx=2048,
|
| 32 |
+
n_embd=4096,
|
| 33 |
+
n_layer=28,
|
| 34 |
+
n_head=16,
|
| 35 |
+
rotary_dim=64,
|
| 36 |
+
n_inner=None,
|
| 37 |
+
activation_function="gelu_new",
|
| 38 |
+
resid_pdrop=0.0,
|
| 39 |
+
embd_pdrop=0.0,
|
| 40 |
+
attn_pdrop=0.0,
|
| 41 |
+
layer_norm_epsilon=1e-5,
|
| 42 |
+
initializer_range=0.02,
|
| 43 |
+
scale_attn_weights=True,
|
| 44 |
+
gradient_checkpointing=False,
|
| 45 |
+
use_cache=True,
|
| 46 |
+
bos_token_id=50256,
|
| 47 |
+
eos_token_id=50256,
|
| 48 |
+
**kwargs
|
| 49 |
+
):
|
| 50 |
+
super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
|
| 51 |
+
|
| 52 |
+
self.vocab_size = vocab_size
|
| 53 |
+
self.n_ctx = n_ctx
|
| 54 |
+
self.n_positions = n_positions
|
| 55 |
+
self.n_embd = n_embd
|
| 56 |
+
self.n_layer = n_layer
|
| 57 |
+
self.n_head = n_head
|
| 58 |
+
self.n_inner = n_inner
|
| 59 |
+
self.rotary_dim = rotary_dim
|
| 60 |
+
self.activation_function = activation_function
|
| 61 |
+
self.resid_pdrop = resid_pdrop
|
| 62 |
+
self.embd_pdrop = embd_pdrop
|
| 63 |
+
self.attn_pdrop = attn_pdrop
|
| 64 |
+
self.layer_norm_epsilon = layer_norm_epsilon
|
| 65 |
+
self.initializer_range = initializer_range
|
| 66 |
+
self.gradient_checkpointing = gradient_checkpointing
|
| 67 |
+
self.scale_attn_weights = scale_attn_weights
|
| 68 |
+
self.use_cache = use_cache
|
| 69 |
+
|
| 70 |
+
self.bos_token_id = bos_token_id
|
| 71 |
+
self.eos_token_id = eos_token_id
|
| 72 |
+
|
| 73 |
+
@property
|
| 74 |
+
def max_position_embeddings(self):
|
| 75 |
+
return self.n_positions
|
| 76 |
+
|
| 77 |
+
@property
|
| 78 |
+
def hidden_size(self):
|
| 79 |
+
return self.n_embd
|
| 80 |
+
|
| 81 |
+
@property
|
| 82 |
+
def num_attention_heads(self):
|
| 83 |
+
return self.n_head
|
| 84 |
+
|
| 85 |
+
@property
|
| 86 |
+
def num_hidden_layers(self):
|
| 87 |
+
return self.n_layer
|