channelsfirst
Channelsfirst is a data layout used for multi-dimensional arrays in neural networks, where the channel dimension comes before the spatial dimensions. For 2D data, the common shape is N, C, H, W (batch size N, channels C, height H, width W); for 3D data it is N, C, D, H, W. This arrangement is often referred to as NCHW and is contrasted with channels last layouts such as N, H, W, C (NHWC).
The term is used across different machine learning frameworks, with varying defaults. PyTorch commonly employs channels
Performance considerations play a role in the choice of channelsfirst. Memory layout can influence cache efficiency
Practical notes: ensure consistency of data format across the entire workflow, including data loading, model definition,