from torch import nn
from torch.nn import functional as F
-import mygpt, tasks, tensorstack
+import mygpt, tasks
######################################################################
train_examples = {}
for input in task.batches(split="train"):
- assert input.dim()==2 and input.dtype==torch.int64
+ assert input.dim() == 2 and input.dtype == torch.int64
for x in input:
- train_examples[x.sum().item()]=x
+ train_examples[x.sum().item()] = x
for input in task.batches(split="test"):
- assert input.dim()==2 and input.dtype==torch.int64
+ assert input.dim() == 2 and input.dtype == torch.int64
for x in input:
y = train_examples.get(x.sum().item())
if y is not None:
- assert x.size() != y.size() or (x-y).abs().sum() > 0
+ assert x.size() != y.size() or (x - y).abs().sum() > 0
del train_examples