Microsoft CNTK Automatic Differentiation
According to Microsoft, CNTK includes automatic differentiation. For better understanding the source (which I've successfully built) I'd like to know which C++ classes implement AD and how it is implemented in CNTK?
cntk autodiff
asked Nov 14 '18 at 16:54
RodRod
63
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According to Microsoft, CNTK includes automatic differentiation. For better understanding the source (which I've successfully built) I'd like to know which C++ classes implement AD and how it is implemented in CNTK?
cntk autodiff
asked Nov 14 '18 at 16:54
RodRod
63
add a comment |
According to Microsoft, CNTK includes automatic differentiation. For better understanding the source (which I've successfully built) I'd like to know which C++ classes implement AD and how it is implemented in CNTK?
cntk autodiff
asked Nov 14 '18 at 16:54
RodRod
63
According to Microsoft, CNTK includes automatic differentiation. For better understanding the source (which I've successfully built) I'd like to know which C++ classes implement AD and how it is implemented in CNTK?
cntk autodiff
cntk autodiff
asked Nov 14 '18 at 16:54
RodRod
63
asked Nov 14 '18 at 16:54
RodRod
63
asked Nov 14 '18 at 16:54
RodRod
63
asked Nov 14 '18 at 16:54
RodRod
63
asked Nov 14 '18 at 16:54
RodRod
63
63
add a comment |
add a comment |
1 Answer
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CNTK class Function implements the AD (via Gradients method, to be precise). Neural networks are represented as multiple Function compositions like g(f(x)). Then derivative of function g is computed with respect to f like this:
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
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1 Answer
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1 Answer
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CNTK class Function implements the AD (via Gradients method, to be precise). Neural networks are represented as multiple Function compositions like g(f(x)). Then derivative of function g is computed with respect to f like this:
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
add a comment |
CNTK class Function implements the AD (via Gradients method, to be precise). Neural networks are represented as multiple Function compositions like g(f(x)). Then derivative of function g is computed with respect to f like this:
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
add a comment |
CNTK class Function implements the AD (via Gradients method, to be precise). Neural networks are represented as multiple Function compositions like g(f(x)). Then derivative of function g is computed with respect to f like this:
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
CNTK class Function implements the AD (via Gradients method, to be precise). Neural networks are represented as multiple Function compositions like g(f(x)). Then derivative of function g is computed with respect to f like this:
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
answered Nov 22 '18 at 17:05
papadoble151papadoble151
438413
438413
add a comment |
add a comment |
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