Zero padding
Zero padding is the addition of borders filled with zero values around an array or input, often to control convolution output dimensions.
Math and Architectures of Deep Learning
A convolution setting that extends the input with zeros so the kernel can produce outputs near the boundary.
- How it is used
- Controls convolution boundaries and output dimensions when kernels approach the edges of input arrays.
- How deep it goes
- Derives padded input size and boundary positions, but stops short of implementation-specific padding configuration.
- Examples
- Uses a one-dimensional kernel of size three and a final window containing one input value followed by two zeros.
- What you can do after
- Apply it to reason about boundary outputs and calculate how padding changes the effective convolution input.
Read how Math and Architectures of Deep Learning explains zero padding →
Learn Generative AI with PyTorch
The addition of zero-valued borders around an input to control convolution output size.
- How it is used
- Controls convolution output dimensions while extracting spatial features in convolutional neural networks.
- How deep it goes
- Explains borders, output-size effects, tensor dimensions, and scan calculations, but does not derive general convolution formulas.
- Examples
- Uses a 3 × 3 input, a 2 × 2 filter, padding=1, stride=2, explicit scan arithmetic, and a 2 × 2 output tensor.
- What you can do after
- Apply it via nn.Conv2d by setting padding alongside kernel_size and stride to shape convolution outputs.
Read how Learn Generative AI with PyTorch explains zero padding →
Related concepts
- dimensionaddresses · A dimension is an independent coordinate, measurable axis, or descriptive attribute used to represent, locate, or analyze something.
- valid paddingcontrasts with · A convolution padding scheme that adds no extra border values around the input, so the kernel only applies where it fully fits inside the input.
- paddingkind of · Padding is the addition of extra space, values, or data around or within a structure to satisfy size, alignment, layout, or processing requirements.
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