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Chapter 5
MuseNet can produce up to 4-minute musical compositions with 10 different
instruments, and can combine styles from country, to Mozart, to the Beatles. For
instance, I generated a remake of Beethoven's "fur Elise" in the style of Lady Gaga
with Piano, Drums, Guitar, and Bass. You can try this for yourself at https://
openai.com/blog/musenet/, under the section Try MuseNet:
A summary of convolution operations
In this section we present a summary of different convolution operations.
A convolutional layer has I input channels and produces O output channels.
I × O × K parameters are used, where K is the number of values in the kernel.
Basic convolutional neural networks
(CNN or ConvNet)
Let's remind ourselves briefly what a CNN is. CNNs take in an input image (two
dimensions) or a text (two dimensions) or a video (three dimensions) and apply
multiple filters to the input. Each filter is a like a flashlight sliding across the areas
of the input and the areas that it is shining over is called the receptive field. Each
filter is a tensor of the same depth of the input (for instance if the image has a depth
of 3, then the filter must also have a depth of 3).
When the filter is sliding, or convolving, around the input image, the values
in the filter are multiplied by the values of the input. The multiplications are
then summarized into one single value. This process is repeated for each location
producing an activation map (also known as a feature map).
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