Aliases:
tf.math.reduce_sum
tf.reduce_sum
tf.math.reduce_sum(
input_tensor,
axis=None,
keepdims=None,
name=None,
reduction_indices=None,
keep_dims=None
)
Defined in tensorflow/python/ops/math_ops.py
.
Computes the sum of elements across dimensions of a tensor. (deprecated arguments)
Reduces input_tensor
along the dimensions given in axis
.
Unless keepdims
is true, the rank of the tensor is reduced by 1 for each
entry in axis
. If keepdims
is true, the reduced dimensions
are retained with length 1.
If axis
is None, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
x = tf.constant([[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, keepdims=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. Must be in the range[-rank(input_tensor), rank(input_tensor))
.keepdims
: If true, retains reduced dimensions with length 1.name
: A name for the operation (optional).reduction_indices
: The old (deprecated) name for axis.keep_dims
: Deprecated alias forkeepdims
.
Returns:
The reduced tensor, of the same dtype as the input_tensor.
Numpy Compatibility
Equivalent to np.sum apart the fact that numpy upcast uint8 and int32 to int64 while tensorflow returns the same dtype as the input.