Spaces:
Runtime error
Runtime error
File size: 1,152 Bytes
607ecc1 |
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 34 35 36 37 38 39 40 41 |
import gin
import torch.nn as nn
import torch.nn.functional as F
class FiLM(nn.Module):
def forward(self, x, gamma, beta):
return gamma * x + beta
class TimeDistributedLayerNorm(nn.Module):
def __init__(self, size: int):
super().__init__()
self.layer_norm = nn.LayerNorm(size)
def forward(self, x):
return self.layer_norm(x.transpose(1, 2)).transpose(1, 2)
@gin.configurable
class TimeDistributedMLP(nn.Module):
def __init__(self, in_size: int, hidden_size: int, out_size: int, depth: int = 3):
super().__init__()
assert depth >= 3, "Depth must be at least 3"
layers = []
for i in range(depth):
layers.append(
nn.Conv1d(
in_size if i == 0 else hidden_size,
hidden_size if i < depth - 1 else out_size,
1,
)
)
if i < depth - 1:
layers.append(TimeDistributedLayerNorm(hidden_size))
layers.append(nn.LeakyReLU())
self.net = nn.Sequential(*layers)
def forward(self, x):
return self.net(x)
|