tf.accumulate_n(inputs, shape=None, tensor_dtype=None, name=None)
See the guide: Math > Reduction
Returns the element-wise sum of a list of tensors.
Optionally, pass shape
and tensor_dtype
for shape and type checking, otherwise, these are inferred.
NOTE: This operation is not differentiable and cannot be used if inputs depend on trainable variables. Please use tf.add_n
for such cases.
For example:
# tensor 'a' is [[1, 2], [3, 4]] # tensor `b` is [[5, 0], [0, 6]] tf.accumulate_n([a, b, a]) ==> [[7, 4], [6, 14]] # Explicitly pass shape and type tf.accumulate_n([a, b, a], shape=[2, 2], tensor_dtype=tf.int32) ==> [[7, 4], [6, 14]]
inputs
: A list of Tensor
objects, each with same shape and type.shape
: Shape of elements of inputs
.tensor_dtype
: The type of inputs
.name
: A name for the operation (optional).A Tensor
of same shape and type as the elements of inputs
.
ValueError
: If inputs
don't all have same shape and dtype or the shape cannot be inferred.Defined in tensorflow/python/ops/math_ops.py
.
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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/accumulate_n