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Training a deep CNN

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Ali Al-Saegh
Ali Al-Saegh on 13 Mar 2021
Answered: Krishna on 6 Jun 2024
Which data layout (NHWC, NCHW, or CHWN) is used in trainig a deep CNN? Is there a possibility to choose one of them for the training process?

Answers (1)

Krishna
Krishna on 6 Jun 2024
Hello Ali,
In deep Convolutional Neural Networks (CNNs) training, the NCHW and NHWC data formats are widely utilized, with the choice between them influenced by the deep learning framework, hardware (GPUs or CPUs), and model or optimization needs.
NCHW: Number of samples, Channels, Height, Width. Preferred for NVIDIA GPUs due to optimization for CUDA cores.
NHWC: Number of samples, Height, Width, Channels. Often the default in TensorFlow, this intuitive format is favored for CPU computations or with specific accelerators.
CHWN: Less common and rarely supported in major frameworks like TensorFlow or PyTorch.
Choosing a Data Layout involves considering framework support, hardware compatibility (with NVIDIA GPUs favoring NCHW), model requirements, and performance impacts.
Please go through the following article to learn more,
Hope this helps.

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