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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import numpy as np
class ScaledDotProductAttention(nn.Module):
"""Scaled Dot-Product Attention"""
def __init__(self, temperature):
super().__init__()
self.temperature = temperature
self.softmax = nn.Softmax(dim=2)
def forward(self, q, k, v, mask=None):
attn = torch.bmm(q, k.transpose(1, 2))
attn = attn / self.temperature
if mask is not None:
attn = attn.masked_fill(mask, -np.inf)
attn = self.softmax(attn)
output = torch.bmm(attn, v)
return output, attn
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