tensorflow:: ops:: SparseSlice
#include <sparse_ops.h>
Slice a SparseTensor
based on the start
and size
.
Summary
For example, if the input is
input_tensor = shape = [2, 7] [ a d e ] [b c ]
Graphically the output tensors are:
sparse_slice([0, 0], [2, 4]) = shape = [2, 4] [ a ] [b c ] sparse_slice([0, 4], [2, 3]) = shape = [2, 3] [ d e ] [ ]
Args:
- scope: A Scope object
- indices: 2-D tensor represents the indices of the sparse tensor.
- values: 1-D tensor represents the values of the sparse tensor.
- shape: 1-D. tensor represents the shape of the sparse tensor.
- start: 1-D. tensor represents the start of the slice.
- size: 1-D. tensor represents the size of the slice. output indices: A list of 1-D tensors represents the indices of the output sparse tensors.
Returns:
Output
output_indicesOutput
output_values: A list of 1-D tensors represents the values of the output sparse tensors.Output
output_shape: A list of 1-D tensors represents the shape of the output sparse tensors.
Constructors and Destructors |
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SparseSlice(const ::tensorflow::Scope & scope, ::tensorflow::Input indices, ::tensorflow::Input values, ::tensorflow::Input shape, ::tensorflow::Input start, ::tensorflow::Input size)
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Public attributes |
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operation
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output_indices
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output_shape
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output_values
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Public attributes
operation
Operation operation
output_indices
::tensorflow::Output output_indices
output_shape
::tensorflow::Output output_shape
output_values
::tensorflow::Output output_values
Public functions
SparseSlice
SparseSlice( const ::tensorflow::Scope & scope, ::tensorflow::Input indices, ::tensorflow::Input values, ::tensorflow::Input shape, ::tensorflow::Input start, ::tensorflow::Input size )