PrefixEncoder 作用:在微调时(以P-Tuning V2为例),方法训练时冻结模型的全部参数,只激活PrefixEncoder的参数。 其源码如下,整体来看是比较简单的。 classPrefixEncoder(torch.nn.Module):def__init__(self, config):super().__init__() self.prefix_projection = config.prefix_projectionifself.prefix_projection...
( default=None ) prefix_projection: bool = field( default=False ) @dataclass class DataTrainingArguments: """ Arguments pertaining to what data we are going to input our model for training and eval. """ lang: Optional[str] = field(default=None, metadata={"help": "Language id for ...
bos_token_id=150004, eos_token_id=150005, mask_token_id=150000, gmask_token_id=150001, pad_token_id=0, max_sequence_length=2048, inner_hidden_size=16384, position_encoding_2d=True, quantization_bit=0, quantization_embeddings=False, pre_seq_len=None, prefix_projection=False, **kwargs )...
nn model to encode the prefix Input shape: (batch-size, prefix-length) Output shape: (batch-size, prefix-length, 2*layers*hidden) """ def __init__(self, config: ChatGLMConfig): super().__init__() # 控制是否开启前缀投影,即用两层 MLP 处理前缀嵌入 self.prefix_projection = config....
(self, prefix: torch.Tensor): # 前缀 ID 尺寸为 [BatchSize, PreSeqLen] # 根据前缀 ID 获取嵌入,尺寸为 [BatchSize, PreSeqLen, KVSize] # 如果设定了需要投影,就用两层 MLP 处理嵌入 if self.prefix_projection: prefix_tokens = self.embedding(prefix) past_key_values = self.trans(prefix_tokens...
当prefix_projection为True时,就是P-Tuning-V2方法,会在每一层前都加上新的参数;为False时,就是P-Tuning方法,仅在大模型的Embedding上新的参数。 Lora Lora的方法稍微复杂一点,但效果也不错。它的核心思想是在大型语言模型上对指定参数增加额外的低秩矩阵,然后用新的数据训练这些额外参数。具体操作也是类似的,你...
控制前缀编码器中是否启用投影变换self.prefix_projection = config.prefix_projectionif self.pre_seq_len is not None:# 如果启用了 PTuning,需要冻结除了前缀编码器的所有参数for param in self.parameters():param.requires_grad = False# 生成前缀 ID,是 0 - PreSeqLen 的数组self.prefix_tokens = torch....
prefix_projection if self.pre_seq_len is not None: # 如果启用了 PTuning,需要冻结除了前缀编码器的所有参数 for param in self.parameters(): param.requires_grad = False # 生成前缀 ID,是 0 - PreSeqLen 的数组 self.prefix_tokens = torch.arange(self.pre_seq_len).long() # 前缀编码器,用于...
Output shape: (batch-size, prefix-length, 2*layers*hidden) """def__init__(self, config: ChatGLMConfig):super().__init__()# 控制是否开启前缀投影,即用两层 MLP 处理前缀嵌入self.prefix_projection = config.prefix_projectionifself.prefix_projection:# KVSize = NLayer * 2 * NGroup * Head...
"prefix_projection": false, "quantization_bit": 0, "recompute": false, "tensor_parallel_degree": 1, "use_cache": true, "vocab_size": 130528 } W0615 10:57:07.403867 187 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime ...