【发布时间】:2022-01-14 17:39:27
【问题描述】:
将 PyTorch 字典数据集 传递到 TensorBoard add_graph(model, data) 的正确方法是什么。
May 看起来类似于Question1、Qeustion2 和Question3,但是找不到正确的处理字典数据集的方法。
错误信息
跟踪函数的字典输入必须具有一致的类型。找到张量和列表[str]
发生错误,未保存图表
以下是我的项目匿名脚本。
train.py
from torch.utils.tensorboard import SummaryWriter
from models import CustomModel
from datasets import CustomDataset
writer = SummaryWriter()
# Dataset
dataset = CustomDataset(params ...)
train_dataset = [dataset[i] for i in range(0, k)]
train_dataloader = DataLoader(train_dataset, batch_size=32, shuffle=True)
# Model & TensorBoard
model = CustomModel(params....)
writer.add_graph(model, next(iter(train_dataloader))) # ---- HERE ----
datasets.py
class CustomDataset(Dataset):
def __init__(self, ...):
...
self.x_sequences = pad_sequence(x_sequences, batch_first=True, padding_value=0)
self.y_label = torch.LongTensor(label_list)
...
def __len__(self):
return len(self.y_label)
def __getitem__(self, index):
...
return {
"x_categoricals": self.x_categoricals[index],
"x_sequences": self.x_sequences[index],
"y_label": self.y_label[index],
"info": self.info[index],
}
【问题讨论】:
标签: pytorch tensorboard