update pretrain progress bar tutorial

ML/Pytorch/Basics/pytorch_progress_bar.py

@@ -3,9 +3,7 @@ import torch.nn as nn
 from tqdm import tqdm
 from torch.utils.data import TensorDataset, DataLoader
 
-# Create a simple toy dataset example, normally this
-# would be doing custom class with __getitem__ etc,
-# which we have done in custom dataset tutorials
+# Create a simple toy dataset
 x = torch.randn((1000, 3, 224, 224))
 y = torch.randint(low=0, high=10, size=(1000, 1))
 ds = TensorDataset(x, y)
@@ -13,12 +11,12 @@ loader = DataLoader(ds, batch_size=8)
 
 
 model = nn.Sequential(
-    nn.Conv2d(3, 10, kernel_size=3, padding=1, stride=1),
+    nn.Conv2d(in_channels=3, out_channels=10, kernel_size=3, padding=1, stride=1),
     nn.Flatten(),
-    nn.Linear(10*224*224, 10),
+    nn.Linear(10 * 224 * 224, 10),
 )
 
-NUM_EPOCHS = 100
+NUM_EPOCHS = 10
 for epoch in range(NUM_EPOCHS):
     loop = tqdm(loader)
     for idx, (x, y) in enumerate(loop):
@@ -35,7 +33,3 @@ for epoch in range(NUM_EPOCHS):
         loop.set_postfix(loss=torch.rand(1).item(), acc=torch.rand(1).item())
 
 # There you go. Hope it was useful :)
-
-
-
-