import torch as t
import torch.nn as nn


class Embedding(nn.Module):

    def __init__(self, input_dim, output_dim):
        super(Embedding, self).__init__()
        self.embedding = nn.Embedding(input_dim, output_dim)

    def forward(self, src):
        word_emb = self.embedding(src)
        return word_emb

b1fee0240d2eca1b16764ba06d3a5e19a06662d9
<mask token>


class Embedding(nn.Module):
    <mask token>
    <mask token>

<mask token>


class Embedding(nn.Module):
    <mask token>

    def forward(self, src):
        word_emb = self.embedding(src)
        return word_emb

<mask token>


class Embedding(nn.Module):

    def __init__(self, input_dim, output_dim):
        super(Embedding, self).__init__()
        self.embedding = nn.Embedding(input_dim, output_dim)

    def forward(self, src):
        word_emb = self.embedding(src)
        return word_emb

import torch as t
import torch.nn as nn


class Embedding(nn.Module):

    def __init__(self, input_dim, output_dim):
        super(Embedding, self).__init__()
        self.embedding = nn.Embedding(input_dim, output_dim)

    def forward(self, src):
        word_emb = self.embedding(src)
        return word_emb
