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#!/usr/bin/env python
# coding=utf-8
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
from transformers.configuration_utils import PretrainedConfig
CODESAGE_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"codesage/codesage-small-v2": "https://huggingface.co/codesage/codesage-small-v2/resolve/main/config.json",
"codesage/codesage-base-v2": "https://huggingface.co/codesage/codesage-base-v2/resolve/main/config.json",
"codesage/codesage-large-v2": "https://huggingface.co/codesage/codesage-large-v2/resolve/main/config.json",
}
class CodeSageConfig(PretrainedConfig):
model_type = "codesage"
def __init__(
self,
vocab_size=50257,
max_position_embeddings=1024,
hidden_size=768,
num_hidden_layers=12,
num_attention_heads=12,
intermediate_size=3072,
activation_function="gelu_new",
residual_dropout_prob=0.1,
embedding_dropout_prob=0.1,
attention_dropout_prob=0.1,
layer_norm_epsilon=1e-5,
initializer_range=0.02,
position_embedding_type='absolute',
bos_token_id=0,
eos_token_id=0,
pad_token_id=49153,
**kwargs
):
self.vocab_size = vocab_size
self.max_position_embeddings = max_position_embeddings
self.hidden_size = hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.intermediate_size = intermediate_size
assert 'gelu' in activation_function
self.activation_function = activation_function
self.residual_dropout_prob = residual_dropout_prob
self.embedding_dropout_prob = embedding_dropout_prob
self.attention_dropout_prob = attention_dropout_prob
self.layer_norm_epsilon = layer_norm_epsilon
self.initializer_range = initializer_range
self.position_embedding_type = position_embedding_type
super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
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