<ul><li>In PyTorch, calling a model triggers the forward() method due to Python's method lookup.</li><li>The forward() method defines the forward pass of the model, processing input to produce output.</li><li>The train() and eval() methods set the model mode for training with specific behaviors like dropout and batch normalization adjustments.</li><li>It is essential to understand and utilize train() and eval() along with forward() for effective model training and evaluation in PyTorch.</li></ul>

Why Use train() in nn.Module When forward() is Called?

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