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7.4. Multiple Input and Multiple Output Channels — Dive into Deep Learning 1.0.3 documentation
d2l.ai
construct a convolution kernel with the same number of input channels as the input data adding the results together (summing over the channels) to yield a two-dimensional tensor. increase the channel dimension as we go deeper in the neural network ownsampling to trade off spatial resolution for grea
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construct a convolution kernel with the same number of input channels as the input data
adding the
results together (summing over the channels) to yield a two-dimensional tensor.
increase the channel dimension as we go deeper in the neural network
ownsampling to trade off spatial resolution for greater channel depth.
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d2l.ai
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