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Update
author
François Fleuret
<francois@fleuret.org>
Sun, 19 Mar 2023 08:05:09 +0000
(09:05 +0100)
committer
François Fleuret
<francois@fleuret.org>
Sun, 19 Mar 2023 08:05:09 +0000
(09:05 +0100)
beaver.py
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diff --git
a/beaver.py
b/beaver.py
index
e22fc7b
..
afec61d
100755
(executable)
--- a/
beaver.py
+++ b/
beaver.py
@@
-191,12
+191,11
@@
def one_shot(gpt, task):
output = model(output_gpt)
targets = targets * (input.unsqueeze(-1) == maze.v_empty)
output = output * (input.unsqueeze(-1) == maze.v_empty)
output = model(output_gpt)
targets = targets * (input.unsqueeze(-1) == maze.v_empty)
output = output * (input.unsqueeze(-1) == maze.v_empty)
- loss = (output.softmax(-1) - targets).abs().max(-1).values.mean()
- # loss = (
- # -(output.log_softmax(-1) * targets).sum()
- # / (input == maze.v_empty).sum()
- # + targets.xlogy(targets).sum() / (input == maze.v_empty).sum()
- # )
+ # loss = (output.softmax(-1) - targets).abs().max(-1).values.mean()
+ loss = (
+ -(output.log_softmax(-1) * targets).sum()
+ / (input == maze.v_empty).sum()
+ )
acc_train_loss += loss.item() * input.size(0)
nb_train_samples += input.size(0)
acc_train_loss += loss.item() * input.size(0)
nb_train_samples += input.size(0)
@@
-210,12
+209,11
@@
def one_shot(gpt, task):
output = model(output_gpt)
targets = targets * (input.unsqueeze(-1) == maze.v_empty)
output = output * (input.unsqueeze(-1) == maze.v_empty)
output = model(output_gpt)
targets = targets * (input.unsqueeze(-1) == maze.v_empty)
output = output * (input.unsqueeze(-1) == maze.v_empty)
- loss = (output.softmax(-1) - targets).abs().max(-1).values.mean()
- # loss = (
- # -(output.log_softmax(-1) * targets).sum()
- # / (input == maze.v_empty).sum()
- # + targets.xlogy(targets).sum() / (input == maze.v_empty).sum()
- # )
+ # loss = (output.softmax(-1) - targets).abs().max(-1).values.mean()
+ loss = (
+ -(output.log_softmax(-1) * targets).sum()
+ / (input == maze.v_empty).sum()
+ )
acc_test_loss += loss.item() * input.size(0)
nb_test_samples += input.size(0)
acc_test_loss += loss.item() * input.size(0)
nb_test_samples += input.size(0)
@@
-231,8
+229,11
@@
def one_shot(gpt, task):
# losses = (-output.log_softmax(-1) * targets + targets.xlogy(targets)).sum(-1)
# losses = losses * (input == maze.v_empty)
# losses = losses / losses.max()
# losses = (-output.log_softmax(-1) * targets + targets.xlogy(targets)).sum(-1)
# losses = losses * (input == maze.v_empty)
# losses = losses / losses.max()
- losses = (output.softmax(-1) - targets).abs().max(-1).values
- losses = (losses >= 0.05).float()
+ # losses = (output.softmax(-1) - targets).abs().max(-1).values
+ # losses = (losses >= 0.05).float()
+ losses = (
+ (F.one_hot(output.argmax(-1), num_classes=4) * targets).sum(-1) == 0
+ ).float()
losses = losses.reshape(-1, args.maze_height, args.maze_width)
input = input.reshape(-1, args.maze_height, args.maze_width)
maze.save_image(
losses = losses.reshape(-1, args.maze_height, args.maze_width)
input = input.reshape(-1, args.maze_height, args.maze_width)
maze.save_image(