Stay organized with collections
Save and categorize content based on your preferences.
tensorflow::ops::SparseDenseCwiseMul
#include <sparse_ops.h>
Component-wise multiplies a SparseTensor by a dense Tensor.
Summary
The output locations corresponding to the implicitly zero elements in the sparse tensor will be zero (i.e., will not take up storage space), regardless of the contents of the dense tensor (even if it's +/-INF and that INF*0 == NaN).
Limitation: this Op only broadcasts the dense side to the sparse side, but not the other direction.
Args:
- scope: A Scope object
- sp_indices: 2-D.
N x R matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.
- sp_values: 1-D.
N non-empty values corresponding to sp_indices.
- sp_shape: 1-D. Shape of the input SparseTensor.
- dense:
R-D. The dense Tensor operand.
Returns:
Output: 1-D. The N values that are operated on.
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::SparseDenseCwiseMul Class Reference\n\ntensorflow::ops::SparseDenseCwiseMul\n====================================\n\n`#include \u003csparse_ops.h\u003e`\n\nComponent-wise multiplies a SparseTensor by a dense [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n\nSummary\n-------\n\nThe output locations corresponding to the implicitly zero elements in the sparse tensor will be zero (i.e., will not take up storage space), regardless of the contents of the dense tensor (even if it's +/-INF and that INF\\*0 == NaN).\n\n*Limitation*: this Op only broadcasts the dense side to the sparse side, but not the other direction.\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- sp_indices: 2-D. `N x R` matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.\n- sp_values: 1-D. `N` non-empty values corresponding to `sp_indices`.\n- sp_shape: 1-D. Shape of the input SparseTensor.\n- dense: `R`-D. The dense [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) operand.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 1-D. The `N` values that are operated on.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseDenseCwiseMul](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1a884270b76fd3fbf6b5db27dbb284b825)`(const ::`[tensorflow::Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` sp_indices, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` sp_values, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` sp_shape, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` dense)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1a1cbb106ceb29f4d80fa5618ac7a0391f) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1a90d4c55f83816dd179b83fb561a3d14a) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1a129f0f5944cd5528658cb2fe913a8e88)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1af40c98d474b6d10da285068a5865bbcb)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_dense_cwise_mul_1a820cf17bf53dea855ae65c6afa1bf5e8)`() const ` | |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### SparseDenseCwiseMul\n\n```gdscript\n SparseDenseCwiseMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input sp_indices,\n ::tensorflow::Input sp_values,\n ::tensorflow::Input sp_shape,\n ::tensorflow::Input dense\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
