Upload configuration_codegen.py
Browse files- configuration_codegen.py +87 -0
configuration_codegen.py
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# coding=utf-8
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# Copyright 2021 The EleutherAI and HuggingFace Teams. All rights reserved.
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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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# Modified configuration implementation based on https://github.com/huggingface/transformers/blob/main/src/transformers/models/gptj/configuration_gptj.py
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from transformers.configuration_utils import PretrainedConfig
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from transformers.utils import logging
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logger = logging.get_logger(__name__)
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class CodeGenConfig(PretrainedConfig):
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model_type = "codegen"
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def __init__(
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self,
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vocab_size=50400,
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n_positions=2048,
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n_ctx=2048,
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n_embd=4096,
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n_layer=28,
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n_head=16,
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rotary_dim=64,
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n_inner=None,
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activation_function="gelu_new",
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resid_pdrop=0.0,
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embd_pdrop=0.0,
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attn_pdrop=0.0,
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layer_norm_epsilon=1e-5,
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initializer_range=0.02,
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scale_attn_weights=True,
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gradient_checkpointing=False,
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use_cache=True,
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bos_token_id=50256,
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eos_token_id=50256,
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**kwargs
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):
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super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
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self.vocab_size = vocab_size
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self.n_ctx = n_ctx
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self.n_positions = n_positions
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self.n_embd = n_embd
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self.n_layer = n_layer
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self.n_head = n_head
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self.n_inner = n_inner
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self.rotary_dim = rotary_dim
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self.activation_function = activation_function
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self.resid_pdrop = resid_pdrop
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self.embd_pdrop = embd_pdrop
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self.attn_pdrop = attn_pdrop
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self.layer_norm_epsilon = layer_norm_epsilon
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self.initializer_range = initializer_range
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self.gradient_checkpointing = gradient_checkpointing
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self.scale_attn_weights = scale_attn_weights
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self.use_cache = use_cache
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self.bos_token_id = bos_token_id
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self.eos_token_id = eos_token_id
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@property
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def max_position_embeddings(self):
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return self.n_positions
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@property
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def hidden_size(self):
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return self.n_embd
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@property
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def num_attention_heads(self):
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return self.n_head
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@property
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def num_hidden_layers(self):
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return self.n_layer
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