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tensorflow::ops::Where3
#include <math_ops.h>
Selects elements from x or y, depending on condition.
Summary
The x, and y tensors must all have the same shape, and the output will also have that shape.
The condition tensor must be a scalar if x and y are scalars. If x and y are vectors or higher rank, then condition must be either a scalar, a vector with size matching the first dimension of x, or must have the same shape as x.
The condition tensor acts as a mask that chooses, based on the value at each element, whether the corresponding element / row in the output should be taken from x (if true) or y (if false).
If condition is a vector and x and y are higher rank matrices, then it chooses which row (outer dimension) to copy from x and y. If condition has the same shape as x and y, then it chooses which element to copy from x and y.
For example:
# 'condition' tensor is [[True, False]
# [False, True]]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) # => [[1, 6], [7, 4]]
# 'condition' tensor is [True, False]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) ==> [[1, 2],
[7, 8]]
Args:
- scope: A Scope object
- x: = A
Tensor which may have the same shape as condition. If condition is rank 1, x may have higher rank, but its first dimension must match the size of condition.
- y: = A
Tensor with the same type and shape as x.
Returns:
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::Where3 Class Reference\n\ntensorflow::ops::Where3\n=======================\n\n`#include \u003cmath_ops.h\u003e`\n\nSelects elements from `x` or `y`, depending on `condition`.\n\nSummary\n-------\n\nThe `x`, and `y` tensors must all have the same shape, and the output will also have that shape.\n\nThe `condition` tensor must be a scalar if `x` and `y` are scalars. If `x` and `y` are vectors or higher rank, then `condition` must be either a scalar, a vector with size matching the first dimension of `x`, or must have the same shape as `x`.\n\nThe `condition` tensor acts as a mask that chooses, based on the value at each element, whether the corresponding element / row in the output should be taken from `x` (if true) or `y` (if false).\n\nIf `condition` is a vector and `x` and `y` are higher rank matrices, then it chooses which row (outer dimension) to copy from `x` and `y`. If `condition` has the same shape as `x` and `y`, then it chooses which element to copy from `x` and `y`.\n\nFor example:\n\n\n```text\n# 'condition' tensor is [[True, False]\n# [False, True]]\n# 't' is [[1, 2],\n# [3, 4]]\n# 'e' is [[5, 6],\n# [7, 8]]\nselect(condition, t, e) # =\u003e [[1, 6], [7, 4]]\n```\n\n\u003cbr /\u003e\n\n\n```text\n# 'condition' tensor is [True, False]\n# 't' is [[1, 2],\n# [3, 4]]\n# 'e' is [[5, 6],\n# [7, 8]]\nselect(condition, t, e) ==\u003e [[1, 2],\n [7, 8]]\n```\n\n\u003cbr /\u003e\n\n\n```text\n\n```\n\n\u003cbr /\u003e\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- x: = A [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) which may have the same shape as `condition`. If `condition` is rank 1, `x` may have higher rank, but its first dimension must match the size of `condition`.\n- y: = A [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with the same type and shape as `x`.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): = A [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with the same type and shape as `x` and `y`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Where3](#classtensorflow_1_1ops_1_1_where3_1a1e043e7f8493b555a94d106084a64a32)`(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)` condition, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` x, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_where3_1a9b749e1046fbe4c39075a2b037391cf2) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_where3_1a07742c7ad2705b0fa9b9cc9e59eca41b) | `::`[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_where3_1aacfd2a5bd041b46bc2179d3e9ac5c0c6)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_where3_1a7fcabeeb211b239288d028b587a88e54)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_where3_1aedd6e529c7127af0c5af333ded627ab3)`() 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### Where3\n\n```gdscript\n Where3(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input condition,\n ::tensorflow::Input x,\n ::tensorflow::Input y\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```"]]
