tf.reduce_sum
tf.reduce_sum
tf.reduce_sum
reduce_sum( input_tensor, axis=None, keep_dims=False, name=None, reduction_indices=None )
Defined in tensorflow/python/ops/math_ops.py
.
See the guide: Math > Reduction
Computes the sum of elements across dimensions of a tensor.
Reduces input_tensor
along the dimensions given in axis
. Unless keep_dims
is true, the rank of the tensor is reduced by 1 for each entry in axis
. If keep_dims
is true, the reduced dimensions are retained with length 1.
If axis
has no entries, all dimensions are reduced, and a tensor with a single element is returned.
For example:
# 'x' is [[1, 1, 1] # [1, 1, 1]] tf.reduce_sum(x) ==> 6 tf.reduce_sum(x, 0) ==> [2, 2, 2] tf.reduce_sum(x, 1) ==> [3, 3] tf.reduce_sum(x, 1, keep_dims=True) ==> [[3], [3]] tf.reduce_sum(x, [0, 1]) ==> 6
Args:
-
input_tensor
: The tensor to reduce. Should have numeric type. -
axis
: The dimensions to reduce. IfNone
(the default), reduces all dimensions. -
keep_dims
: If true, retains reduced dimensions with length 1. -
name
: A name for the operation (optional). -
reduction_indices
: The old (deprecated) name for axis.
Returns:
The reduced tensor.
numpy compatibility
Equivalent to np.sum
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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/reduce_sum