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# Sparse Tensors
Note: Functions taking `Tensor` arguments can also take anything accepted by
`tf.convert_to_tensor`.
[TOC]
## Sparse Tensor Representation
TensorFlow supports a `SparseTensor` representation for data that is sparse
in multiple dimensions. Contrast this representation with `IndexedSlices`,
which is efficient for representing tensors that are sparse in their first
dimension, and dense along all other dimensions.
* `tf.SparseTensor`
* `tf.SparseTensorValue`
## Conversion
* `tf.sparse_to_dense`
* `tf.sparse_tensor_to_dense`
* `tf.sparse_to_indicator`
* `tf.sparse_merge`
## Manipulation
* `tf.sparse_concat`
* `tf.sparse_reorder`
* `tf.sparse_reshape`
* `tf.sparse_split`
* `tf.sparse_retain`
* `tf.sparse_reset_shape`
* `tf.sparse_fill_empty_rows`
* `tf.sparse_transpose`
## Reduction
* `tf.sparse_reduce_sum`
* `tf.sparse_reduce_sum_sparse`
## Math Operations
* `tf.sparse_add`
* `tf.sparse_softmax`
* `tf.sparse_tensor_dense_matmul`
* `tf.sparse_maximum`
* `tf.sparse_minimum`
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