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feat/res-block #5

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27f25c9
feat: implementing res blocks
DemyCode Feb 18, 2024
ed72460
fix: correct output
DemyCode Feb 18, 2024
0f296b9
fix: using correct pipes
DemyCode Feb 18, 2024
5b5f5ac
fix: adding parentheses at the end because if FORGOR
DemyCode Feb 18, 2024
eeaee1b
fix: adding gh token
DemyCode Feb 18, 2024
27f8b7b
fix: adding body in gh pr create
DemyCode Feb 18, 2024
bb69c24
fix: using fill non interactive
DemyCode Feb 18, 2024
f86ec9f
fix: idk
DemyCode Feb 18, 2024
782eebe
fix: idk
DemyCode Feb 18, 2024
994c7eb
fix: removing checkout for nothing
DemyCode Feb 18, 2024
66970e8
fix: removing fill
DemyCode Feb 18, 2024
9e45502
Merge branch 'master' of github.com:DemyCode/minecraft-copilot-ml int…
DemyCode Feb 18, 2024
c9ec92a
fix: reseting changed on git pull request
DemyCode Feb 18, 2024
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121 changes: 62 additions & 59 deletions minecraft_copilot_ml/metrics_graph.ipynb
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50 changes: 23 additions & 27 deletions minecraft_copilot_ml/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,20 @@
import torch.nn.functional as F


class ResBlock(nn.Module):
def __init__(self, channels_count: int):
super(ResBlock, self).__init__()
self.channels_count = channels_count
self.block = nn.Sequential(
nn.Conv3d(channels_count, channels_count, kernel_size=3, padding=1),
nn.BatchNorm3d(channels_count),
nn.SiLU(),
)

def forward(self, x: torch.Tensor) -> torch.Tensor:
return x + self.block(x)


class VAE(pl.LightningModule):
def __init__(self, unique_blocks_dict, unique_counts_coefficients=None, latent_dim=64):
super(VAE, self).__init__()
Expand All @@ -25,18 +39,10 @@ def __init__(self, unique_blocks_dict, unique_counts_coefficients=None, latent_d
nn.Conv3d(1, len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
# lets go
nn.Flatten(),
Expand All @@ -53,21 +59,11 @@ def __init__(self, unique_blocks_dict, unique_counts_coefficients=None, latent_d
nn.LeakyReLU(),
nn.Unflatten(1, (len(unique_blocks_dict), 16, 16, 16)),
# lets go
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
nn.BatchNorm3d(len(unique_blocks_dict)),
nn.LeakyReLU(),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
ResBlock(len(unique_blocks_dict)),
nn.Conv3d(len(unique_blocks_dict), len(unique_blocks_dict), kernel_size=3, padding=1),
)

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