tf.gradients
tf.gradients
tf.gradients
gradients( ys, xs, grad_ys=None, name='gradients', colocate_gradients_with_ops=False, gate_gradients=False, aggregation_method=None )
Defined in tensorflow/python/ops/gradients_impl.py
.
See the guide: Training > Gradient Computation
Constructs symbolic partial derivatives of sum of ys
w.r.t. x in xs
.
ys
and xs
are each a Tensor
or a list of tensors. grad_ys
is a list of Tensor
, holding the gradients received by the ys
. The list must be the same length as ys
.
gradients()
adds ops to the graph to output the partial derivatives of ys
with respect to xs
. It returns a list of Tensor
of length len(xs)
where each tensor is the sum(dy/dx)
for y in ys
.
grad_ys
is a list of tensors of the same length as ys
that holds the initial gradients for each y in ys
. When grad_ys
is None, we fill in a tensor of '1's of the shape of y for each y in ys
. A user can provide their own initial grad_ys
to compute the derivatives using a different initial gradient for each y (e.g., if one wanted to weight the gradient differently for each value in each y).
Args:
-
ys
: ATensor
or list of tensors to be differentiated. -
xs
: ATensor
or list of tensors to be used for differentiation. -
grad_ys
: Optional. ATensor
or list of tensors the same size asys
and holding the gradients computed for each y inys
. -
name
: Optional name to use for grouping all the gradient ops together. defaults to 'gradients'. -
colocate_gradients_with_ops
: If True, try colocating gradients with the corresponding op. -
gate_gradients
: If True, add a tuple around the gradients returned for an operations. This avoids some race conditions. -
aggregation_method
: Specifies the method used to combine gradient terms. Accepted values are constants defined in the classAggregationMethod
.
Returns:
A list of sum(dy/dx)
for each x in xs
.
Raises:
-
LookupError
: if one of the operations betweenx
andy
does not have a registered gradient function. -
ValueError
: if the arguments are invalid.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/gradients