TensorFlow 2 version
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Returns a list of tensors with the same shapes and contents as the input
tf.identity_n(
input, name=None
)
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])
@tf.RegisterGradient('OverrideGradientWithG')
def ApplyG(op, dy, _):
return [None, g(dy)] # Do not backprop to f(x).
Args | |
|---|---|
input
|
A list of Tensor objects.
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name
|
A name for the operation (optional). |
Returns | |
|---|---|
A list of Tensor objects. Has the same type as input.
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