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).
Arguments:
- 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