tensorflow:: ops:: IdentityN
#include <array_ops.h>
Returns a list of tensors with the same shapes and contents as the input.
Summary
tensors.
This op can be used to override the gradient for complicated functions. For example, suppose y = f(x) and we wish to apply a custom function g for backprop such that dx = g(dy). In Python,
with tf.get_default_graph().gradient_override_map( {'IdentityN': 'OverrideGradientWithG'}): y, _ = identity_n([f(x), x])
.RegisterGradient('OverrideGradientWithG') def ApplyG(op, dy, _): return [None, g(dy)] # Do not backprop to f(x).
Args:
- scope: A Scope object
Returns:
OutputList
: The output tensor.
Constructors and Destructors |
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IdentityN(const ::tensorflow::Scope & scope, ::tensorflow::InputList input)
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Public attributes |
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operation
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output
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Public functions |
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operator[](size_t index) const
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Public attributes
operation
Operation operation
output
::tensorflow::OutputList output
Public functions
IdentityN
IdentityN( const ::tensorflow::Scope & scope, ::tensorflow::InputList input )
operator[]
::tensorflow::Output operator[]( size_t index ) const