#!/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)