写出from torchtext.legacy import data，使用Adam优化器和50个epochs，用floattensor和Word2Vec作为模型的初始化的代码

from torchtext.legacy import data
import torch
import torch.nn as nn
from torch.optim import Adam

# 定义模型
class MyModel(nn.Module):
    def __init__(self, initializer):
        super(MyModel, self).__init__()
        self.embedding = nn.Embedding.from_pretrained(initializer)
        # 其他层的定义
        
# 加载词向量
initializer = torch.FloatTensor(Word2Vec)

# 实例化模型和优化器
model = MyModel(initializer)
optimizer = Adam(model.parameters())

# 训练
for epoch in range(50):
    # 训练代码
    optimizer.step()