past_key_values(tuple(tuple(torch.FloatTensor)),可选,当传递use_cache=True或当config.use_cache=True时返回)— 长度为config.n_layers的tuple(torch.FloatTensor)元组,每个元组有 2 个形状为(batch_size, num_heads, sequence_length, embed
# 最大位置编码长度hidden_size,# 隐藏层大小intermediate_size,# 中间层大小num_hidden_layers,# 隐藏层层数num_attention_heads,# 注意力头的数量hidden_act,# 隐藏层激活函数initializer_range,# 参数初始化范围layer_norm_eps,# 层归一化 epsilon 参数use_cache,# 是否使用缓存rope_theta,...
TFMaskedLMOutput, TFMultipleChoiceModelOutput, TFQuestionAnsweringModelOutput, TFSequenceClassifierOutput, TFTokenClassifierOutput, )# 导入模块中的各类实用函数和损失函数from...modeling_tf_utilsimport( TFCausalLanguageModelingLoss, TFMaskedLanguageModelingLoss, TFModelInputType, TFMultipleChoiceLoss, TFPreTrain...
past_key_values=next_cache, hidden_states=all_hidden_states, attentions=all_self_attns, ) LlamaDecoderLayer类,用来做attention和ffn计算 self.self_attn = LLAMA_ATTENTION_CLASSES[config._attn_implementation](config=config, layer_idx=layer_idx) self.mlp = LlamaMLP(config) self.input_layernorm = ...
class: ktransformers.operators.attention.KDeepseekV2Attention # optimized MLA implementationkwargs:generate_device: "cuda"prefill_device: "cuda"absorb_for_prefill: False # change this to True to enable long context(prefill may slower).9. 修改:- match:name: "^model\\.layers\\..*\\.self_...
implementation’s data format, it will be padded to 64 bytes, which results in 32 times the memory cost in 16-bit and 64 times the memory cost in 8-bit precision. Such an increase in buffer size will significantly reduce the chance of L2 cache residency and increase the chance of ...
To check if each model has an implementation in Flax, PyTorch or TensorFlow, or has an associated tokenizer backed by the 🤗 Tokenizers library, refer to this table.These implementations have been tested on several datasets (see the example scripts) and should match the performance of the ...
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. This specific repository is geared towards integration with eventual Alphafold2 replication. - lucidrains/se3-transformer-pytorch
past_key_values(Cache或tuple(tuple(torch.FloatTensor)),可选)— 预先计算的隐藏状态(自注意力块和交叉注意力块中的键和值),可用于加速顺序解码。这通常包括模型在先前解码阶段返回的past_key_values,当use_cache=True或config.use_cache=True时。允许两种格式: 一个Cache 实例; 长度为config.n_layers的tuple(...
In this section, we will explain how to write an operator that can be injected, using the implementation of a new linear as an example. First, all injectable operators need to inherit from the BaseInjectedModule class, which inherits some attributes required by our injection framework. Its init...