tf.raw_ops.SparseDenseCwiseAdd
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Adds up a SparseTensor and a dense Tensor, using these special rules:
tf.raw_ops.SparseDenseCwiseAdd(
sp_indices, sp_values, sp_shape, dense, name=None
)
(1) Broadcasts the dense side to have the same shape as the sparse side, if
eligible;
(2) Then, only the dense values pointed to by the indices of the SparseTensor
participate in the cwise addition.
By these rules, the result is a logical SparseTensor with exactly the same
indices and shape, but possibly with different non-zero values. The output of
this Op is the resultant non-zero values.
Args |
|---|
sp_indices
|
A Tensor of type int64.
2-D. N x R matrix with the indices of non-empty values in a
SparseTensor, possibly not in canonical ordering.
|
sp_values
|
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, qint16, quint16, uint16, complex128, half, uint32, uint64.
1-D. N non-empty values corresponding to sp_indices.
|
sp_shape
|
A Tensor of type int64.
1-D. Shape of the input SparseTensor.
|
dense
|
A Tensor. Must have the same type as sp_values.
R-D. The dense Tensor operand.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor. Has the same type as sp_values.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.SparseDenseCwiseAdd\n\n\u003cbr /\u003e\n\nAdds up a SparseTensor and a dense Tensor, using these special rules:\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.SparseDenseCwiseAdd`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseDenseCwiseAdd)\n\n\u003cbr /\u003e\n\n tf.raw_ops.SparseDenseCwiseAdd(\n sp_indices, sp_values, sp_shape, dense, name=None\n )\n\n(1) Broadcasts the dense side to have the same shape as the sparse side, if\neligible;\n(2) Then, only the dense values pointed to by the indices of the SparseTensor\nparticipate in the cwise addition.\n\nBy these rules, the result is a logical SparseTensor with exactly the same\nindices and shape, but possibly with different non-zero values. The output of\nthis Op is the resultant non-zero values.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `sp_indices` | A `Tensor` of type `int64`. 2-D. `N x R` matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering. |\n| `sp_values` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `qint16`, `quint16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. 1-D. `N` non-empty values corresponding to `sp_indices`. |\n| `sp_shape` | A `Tensor` of type `int64`. 1-D. Shape of the input SparseTensor. |\n| `dense` | A `Tensor`. Must have the same type as `sp_values`. `R`-D. The dense Tensor operand. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `sp_values`. ||\n\n\u003cbr /\u003e"]]
