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a726cc5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | import json
import torch
import torch.nn as nn
from components.simcodec.modules import Encoder, Quantizer, Generator
class AttrDict(dict):
def __init__(self, *args, **kwargs):
super(AttrDict, self).__init__(*args, **kwargs)
self.__dict__ = self
class SimCodec(nn.Module):
def __init__(self, config_path):
super(SimCodec, self).__init__()
self.config_path = config_path
with open(self.config_path) as f:
data = f.read()
json_config = json.loads(data)
self.h = AttrDict(json_config)
self.encoder = Encoder(self.h)
self.quantizer = Quantizer(self.h)
self.generator = Generator(self.h)
def forward(self, x):
batch_size = x.size(0)
if len(x.shape) == 3 and x.shape[-1] == 1:
x = x.squeeze(-1)
c = self.encoder(x)
_, _, c = self.quantizer(c)
c = [code.reshape(batch_size, -1) for code in c]
return torch.stack(c, -1)
def decode(self, x):
return self.generator(self.quantizer.embed(x)) |