PyTorch: Difference between revisions

Revision as of 07:31, 10 June 2025

Revision as of 11:41, 10 June 2025

Line 78:

# Output: tensor(-2.1540)

print(a[1, 2]) # Output of the element in the third column of the second row (zero -based)

# Output: tensor(0.5847)

print(a.max())

# Output: tensor(0.8498)

</syntaxhighlight>

The following code-block defines a neural network with linear layers using the <code>nn</code> module.
<syntaxhighlight lang="python3" line="1">

from torch import nn # Import the nn sub-module from PyTorch

Line 91 ⟶ 94:

self.flatten = nn.Flatten() # Construct a flattening layer.

self.linear_relu_stack = nn.Sequential( # Construct a stack of layers.

nn.Linear(28 * 28, 512), # Linear Layers have an input and output shape

nn.ReLU(), # ReLU is one of many activation functions provided by nn

nn.Linear(512, 512),