encoder_layer = TransformerEncoderLayer(d_model, nhead, dim_feedforward, dropout, activation, layer_norm_eps, batch_first, **factory_kwargs) encoder_norm = LayerNorm(d_model, eps=layer_norm_eps, **factory_kwargs) self.encoder = TransformerEncoder(encoder_layer, num_encoder_layers, encoder_n...
在PyTorch中,TransformerEncoder和TransformerEncoderLayer是用于构建Transformer模型编码器部分的核心组件。以下是关于这两个类的详细解释以及如何使用它们的代码示例。 1. 导入必要的PyTorch模块 首先,我们需要导入PyTorch中的nn模块,因为TransformerEncoder和TransformerEncoderLayer都定义在这个模块中。 python import torch import...
这将把单个 transformer 层(TransformerEncoderLayer)、图像 transformer (ImageTransformer)、文本编码器 (BERTTextEncoder) 和多模态编码器 (FLAVATransformerWithoutEmbeddings)封装为单个 FSDP 单元。 这采用了一种递归封装的方法来进行有效的内存管理。例如,在单个 transformer 层的正向或反向迭代完成后,删除参数、释放内...
activation checkpointing wrapper 对单个 FLAVA transformer 层(用 TransformerEncoderLayer 表示)的应用如下所示: fromtorchmultimodal.models.flava.modelimportflava_model_for_pretrainingfrom torch.distributed.algorithms._checkpoint.checkpoint_wrapperimportapply_activation_checkpointing,checkpoint_wrapper,CheckpointImplfrom...
以下示例演示了如何用 FSDP 封装 FLAVA 模型。指定自动封装策略为:transformer_auto_wrap_policy。这将把单个 transformer 层(TransformerEncoderLayer)、图像 transformer (ImageTransformer)、文本编码器 (BERTTextEncoder) 和多模态编码器(FLAVATransformerWithoutEmbeddings)封装为单个 FSDP 单元。
Applies a multi-layer long short-term memory (LSTM) RNN to an input sequence. For each element in the input sequence, each layer computes the following function: it=σ(Wiixt+bii+Whih(t−1)+bhi)ft=σ(Wifxt+bif+Whfh(t−1)+bhf)gt=tanh(Wigxt+big+Whgh(t−1)+bhg)ot=σ(W...
activation checkpointing wrapper 对单个 FLAVA transformer 层(用 TransformerEncoderLayer 表示)的应用如下所示: from torchmultimodal.models.flava.model import flava_model_for_pretrainingfrom torch.distributed.algorithms._checkpoint.checkpoint_wrapper import apply_activation_checkpointing, checkpoint_wrapper, Checkp...
TransformerEncoder is a stack of N encoder layers Parameters Examples:: >>> encoder_layer = nn.TransformerEncoderLayer(d_model, nhead) >>> transformer_encoder = nn.TransformerEncoder(encoder_layer, num_layers) 1. 2. forward(src,mask=None,src_key_padding_mask=None)[source] ...
File"/data/miniconda3/envs/ascend-3.10.14/lib/python3.10/site-packages/deepspeed/module_inject/__init__.py", line6,in<module>from .replace_moduleimportreplace_transformer_layer, revert_transformer_layer, ReplaceWithTensorSlicing, GroupQuantizer, generic_injection ...
class SwinTransformerBlock(nn.Module): r""" Swin Transformer Block. Args: dim (int): Number of input channels. input_resolution (tuple[int]): Input resulotion. num_heads (int): Number of attention heads. window_size (int): Window size. ...