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AnimeRecBERT / models /bert_modules /embedding /position.py

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0edbb0d verified about 1 year ago

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import torch.nn as nn
import torch
import math


class PositionalEmbedding(nn.Module):

    def __init__(self, max_len, d_model):
        super().__init__()

        # Compute the positional encodings once in log space.
        self.pe = nn.Embedding(max_len, d_model)

    def forward(self, x):
        batch_size = x.size(0)
        return self.pe.weight.unsqueeze(0).repeat(batch_size, 1, 1)

	import torch.nn as nn
	import torch
	import math


	class PositionalEmbedding(nn.Module):

	def __init__(self, max_len, d_model):
	super().__init__()

	# Compute the positional encodings once in log space.
	self.pe = nn.Embedding(max_len, d_model)

	def forward(self, x):
	batch_size = x.size(0)
	return self.pe.weight.unsqueeze(0).repeat(batch_size, 1, 1)