Module transforms

Module transforms 

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Transforms - Data Augmentation and Preprocessing

Provides composable transformations for data preprocessing and augmentation.

@version 0.1.0 @author AutomataNexus Development Team

Structs§

Clamp
Clamps tensor values to a specified range.
Compose
Composes multiple transforms into a single transform.
DropoutTransform
Applies dropout by randomly zeroing elements during training.
Flatten
Flattens the tensor to 1D.
Lambda
Applies a custom function as a transform.
Normalize
Normalizes a tensor with mean and standard deviation.
RandomCrop
Randomly crops a portion of the input.
RandomFlip
Randomly flips the input along a specified dimension.
RandomNoise
Adds random Gaussian noise to the input.
Reshape
Reshapes the tensor to a specified shape.
Scale
Scales tensor values by a constant factor.
ToTensor
Converts input to a tensor (identity for already-tensor inputs).

Traits§

Transform
Trait for data transformations.