Sparse Ops

Add an N -minibatch SparseTensor to a SparseTensorsMap , return N handles.

Add a SparseTensor to a SparseTensorsMap return its handle.

Deserialize and concatenate SparseTensors from a serialized minibatch.

Deserialize SparseTensor objects.

Serialize an N -minibatch SparseTensor into an [N, 3] Tensor object.

Serialize a SparseTensor into a [3] Tensor object.

Adds two SparseTensor objects to produce another SparseTensor .

The gradient operator for the SparseAdd op.

Concatenates a list of SparseTensor along the specified dimension.

Generates sparse cross from a list of sparse and dense tensors.

Generates sparse cross from a list of sparse and dense tensors.

Generates sparse cross from a list of sparse and dense tensors.

Adds up a SparseTensor and a dense Tensor , using these special rules:

Component-wise divides a SparseTensor by a dense Tensor .

Component-wise multiplies a SparseTensor by a dense Tensor .

Fills empty rows in the input 2-D SparseTensor with a default value.

The gradient of SparseFillEmptyRows .

Computes the max of elements across dimensions of a SparseTensor.

Computes the max of elements across dimensions of a SparseTensor.

Computes the sum of elements across dimensions of a SparseTensor.

Computes the sum of elements across dimensions of a SparseTensor.

Reorders a SparseTensor into the canonical, row-major ordering.

Reshapes a SparseTensor to represent values in a new dense shape.

Slice a SparseTensor based on the start and size .

The gradient operator for the SparseSlice op.

Applies softmax to a batched N-D SparseTensor .

Returns the element-wise max of two SparseTensors.

Returns the element-wise min of two SparseTensors.

Split a SparseTensor into num_split tensors along one dimension.

Adds up a SparseTensor and a dense Tensor , producing a dense Tensor .

Multiply SparseTensor (of rank 2) "A" by dense matrix "B".

Converts a sparse representation into a dense tensor.