Defined in generated file: python/ops/gen_array_ops.py
Returns a list of tensors with the same shapes and contents as the input
Aliases:
tf.compat.v1.identity_n
tf.compat.v2.identity_n
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 ofTensor
objects.name
: Aname
for the operation (optional).
Returns:
A list of Tensor
objects. Has the same type as input
.