func_backward: Propogate Function Backward
In joeddav/CNTK-R: R Interface to the Microsoft Cognitive Toolkit (CNTK)
Description
Backpropagates supplied root_gradients for one or more of the output
variables of the Function, to calculate gradients with respect to variables.
Formally, multiplies the values of root_gradients by the Jacobian of the
Function and returns the subset of the output that corresponds to variables.
Usage
1
func_backward(func, state, root_gradients, variables, as_matrix = TRUE)
Arguments
func
- The CNTK 'Function' instance on which to apply the operation
as_matrix
- whether to return as an R matrix. Defualt TRUE. Otherwise
returns as Python CNTK value which avoids costly conversions
joeddav/CNTK-R documentation built on May 6, 2019, 7:28 a.m.
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Description
Backpropagates supplied root_gradients for one or more of the output variables of the Function, to calculate gradients with respect to variables. Formally, multiplies the values of root_gradients by the Jacobian of the Function and returns the subset of the output that corresponds to variables.
Usage
1 | func_backward(func, state, root_gradients, variables, as_matrix = TRUE)
|
Arguments
func |
- The CNTK 'Function' instance on which to apply the operation |
as_matrix |
- whether to return as an R matrix. Defualt TRUE. Otherwise returns as Python CNTK value which avoids costly conversions |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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