import torch from torch import nn from torch import optim input_dim = 2 hidden_dim = 10 output_dim = 1 class NeuralNetwork(nn.Module): def __init__(self, input_dim, hidden_dim, output_dim): super(NeuralNetwork, self).__init__() self.layer_1 = nn.Linear(input_dim, hidden_dim)...
在forward方法里对head的输出进行了concatenatetorch.cat ,每个head输出维度是2,两个head,所以2+2=4。 3.6.2 Implementing multi-head attention with weight splits 虽然之前我们通过封装单头注意力CausalAttention实现了一个直观且完全功能的多头注意力模型,我们还可以创建一个名为MultiHeadAttention的独立类来实现相...
import torch.nn as nn def replace_linear_with_lora( module: nn.Module, r: int = 8, alpha: int = 16, dropout_p: float = 0.0, embed_requires_grad: bool = False, # embedding 层是否训练 norm_requires_grad: bool = False, # norm 层是否训练 head_requires_grad: bool = False, # lm...
softmax(attn_weights, dim=-1) return activations, attn_weights return activations layer = RoPEAttentionHead(config) batch = torch.randn((config['batch_size'], config['context_window'], config['d_model'])) output, attn_weights = layer(batch, return_attn_weights=True) Tip here: know the...
import torch from torch.nn import functional as F from torch import nn from pytorch_lightning.core.lightning import LightningModule from torchmetrics.functional import accuracy from torch.utils.data import DataLoader, random_split from torchvision.datasets import MNIST import os from torchvision import da...
self.o2o= nn.Linear(hidden_size +output_size, output_size) self.dropout= nn.Dropout(0.1) self.softmax= nn.LogSoftmax(dim=1)defforward(self, category, input, hidden): input_combined= torch.cat((category, input, hidden), 1) hidden=self.i2h(input_combined) ...
torch.nn.init.xavier_normal_(layer.weight)iflayer.biasisnotNone: torch.nn.init.constant_(layer.bias, val=0.0)# Initialization with given tensor.layer.weight = torch.nn.Parameter(tensor) 计算Softmax输出的准确率 score = model(images)
In some cases, when importNetworkFromPyTorch cannot convert a PyTorch layer into a MATLAB layer, the software converts the PyTorch layer into a Deep Learning Toolbox function with dlarray support. PyTorch LayerCorresponding Deep Learning Toolbox LayerAlternative Deep Learning Toolbox Function torch.nn...
from tensorflow import keras报错 import tensorflow as torch,背景不知则问,不能则学。早在17年实习时就用深度学习-卷积神经网络(CNN)在gesture、cifar-10样本数据集上做图像分类;在18年司博带着用keras做人脸识别和车牌识别。当时是新人,现在其实在深度学习方面还是
# import all you needimport osimport torchimport torchvisionimport torch.nn as nnimport torch.nn.functional as Ffrom torch.utils.data import DataLoader, random_splitfrom torchvision.datasets import MNISTfrom torchvision import datasets, transformsimport pytorch_lightning as plfrom pytorch_lightning import...