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57e11c5 | 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 | from __future__ import annotations
import torch
from torch import nn
class LinearCodec(nn.Module):
def __init__(self) -> None:
super().__init__()
self.encoder = nn.Linear(2, 2)
self.decoder = nn.Linear(2, 2)
def encode(self, observations: torch.Tensor) -> torch.Tensor:
return self.encoder(observations)
def forward(self, observations: torch.Tensor) -> torch.Tensor:
return self.decoder(self.encode(observations))
class CoordinatePredictor(nn.Module):
def __init__(self) -> None:
super().__init__()
self.network = nn.Sequential(
nn.Linear(1, 24),
nn.Tanh(),
nn.Linear(24, 24),
nn.Tanh(),
nn.Linear(24, 1),
)
def forward(self, coordinate: torch.Tensor) -> torch.Tensor:
return self.network(coordinate)
def parameter_count(module: nn.Module) -> int:
return sum(parameter.numel() for parameter in module.parameters())
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