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Implement operations commonly found in standard neural network frameworks/libraries. This would allow for benchmarking and comparison testing against other frameworks.
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Basic arithmetic
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2D Convolution
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2D Max pooling
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Element-wise nonlinearities (
tanh,sin,cos,softplus,log,exp, etc.) -
Basic linear algebra (matrix multiplication, transpose, determinant, trace, inverse)
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Basic reductions (sum, product, etc.)
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Basic logical operators (
and,or,not,<=,>=, etc.) -
Logical reductions (all true, any true...)
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Basic shape operators (reorder, reshape, etc.)
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Broadcasting as an explicit operation
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