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tensorflow::ops::Cumsum
#include <math_ops.h>
Compute the cumulative sum of the tensor x along axis.
Summary
By default, this op performs an inclusive cumsum, which means that the first element of the input is identical to the first element of the output:
tf.cumsum([a, b, c]) # => [a, a + b, a + b + c]
By setting the exclusive kwarg to True, an exclusive cumsum is performed instead:
tf.cumsum([a, b, c], exclusive=True) # => [0, a, a + b]
By setting the reverse kwarg to True, the cumsum is performed in the opposite direction:
tf.cumsum([a, b, c], reverse=True) # => [a + b + c, b + c, c]
This is more efficient than using separate tf.reverse ops.
The reverse and exclusive kwargs can also be combined:
tf.cumsum([a, b, c], exclusive=True, reverse=True) # => [b + c, c, 0]
Args:
- scope: A Scope object
- x: A
Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half.
- axis: A
Tensor of type int32 (default: 0). Must be in the range [-rank(x), rank(x)).
Optional attributes (see Attrs):
- exclusive: If
True, perform exclusive cumsum.
- reverse: A
bool (default: False).
Returns:
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
Exclusive
Attrs Exclusive(
bool x
)
Reverse
Attrs Reverse(
bool x
)
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::Cumsum Class Reference\n\ntensorflow::ops::Cumsum\n=======================\n\n`#include \u003cmath_ops.h\u003e`\n\nCompute the cumulative sum of the tensor `x` along `axis`.\n\nSummary\n-------\n\nBy default, this op performs an inclusive cumsum, which means that the first element of the input is identical to the first element of the output:\n\n\n```text\ntf.cumsum([a, b, c]) # =\u003e [a, a + b, a + b + c]\n```\n\n\u003cbr /\u003e\n\nBy setting the `exclusive` kwarg to `True`, an exclusive cumsum is performed instead:\n\n\n```text\ntf.cumsum([a, b, c], exclusive=True) # =\u003e [0, a, a + b]\n```\n\n\u003cbr /\u003e\n\nBy setting the `reverse` kwarg to `True`, the cumsum is performed in the opposite direction:\n\n\n```text\ntf.cumsum([a, b, c], reverse=True) # =\u003e [a + b + c, b + c, c]\n```\n\n\u003cbr /\u003e\n\nThis is more efficient than using separate `tf.reverse` ops.\n\nThe `reverse` and `exclusive` kwargs can also be combined:\n\n\n```text\ntf.cumsum([a, b, c], exclusive=True, reverse=True) # =\u003e [b + c, c, 0]\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). Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`.\n- axis: A [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) of type `int32` (default: 0). Must be in the range `[-rank(x), rank(x))`.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/cumsum/attrs#structtensorflow_1_1ops_1_1_cumsum_1_1_attrs)):\n\n- exclusive: If `True`, perform exclusive cumsum.\n- reverse: A `bool` (default: False).\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The out tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Cumsum](#classtensorflow_1_1ops_1_1_cumsum_1ac4bff34c1fffc1a64355bd97e38887d2)`(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)` x, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` axis)` ||\n| [Cumsum](#classtensorflow_1_1ops_1_1_cumsum_1afe84204de0e7a885385374174240fcc3)`(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)` x, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` axis, const `[Cumsum::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/cumsum/attrs#structtensorflow_1_1ops_1_1_cumsum_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_cumsum_1abe2a855b0b89aedaadef5b1ab2d495f6) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_cumsum_1aa1249678696c8bec40fc3737ff3af4b0) | `::`[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_cumsum_1a638d380af05abb4f7dbdafb4d578e5c4)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_cumsum_1a433ea12bc76c446dca36009246b62bb4)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_cumsum_1a273a98f7b496769e405300dc1b76addd)`() const ` | |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|\n| [Exclusive](#classtensorflow_1_1ops_1_1_cumsum_1a405094be636726578ca6715ceeb29637)`(bool x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/cumsum/attrs#structtensorflow_1_1ops_1_1_cumsum_1_1_attrs) |\n| [Reverse](#classtensorflow_1_1ops_1_1_cumsum_1affad4b03f430a883b021c21fafd4ddbf)`(bool x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/cumsum/attrs#structtensorflow_1_1ops_1_1_cumsum_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::Cumsum::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/cumsum/attrs) | Optional attribute setters for [Cumsum](/versions/r2.14/api_docs/cc/class/tensorflow/ops/cumsum#classtensorflow_1_1ops_1_1_cumsum). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### out\n\n```text\n::tensorflow::Output out\n``` \n\nPublic functions\n----------------\n\n### Cumsum\n\n```gdscript\n Cumsum(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input axis\n)\n``` \n\n### Cumsum\n\n```gdscript\n Cumsum(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input axis,\n const Cumsum::Attrs & attrs\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``` \n\nPublic static functions\n-----------------------\n\n### Exclusive\n\n```text\nAttrs Exclusive(\n bool x\n)\n``` \n\n### Reverse\n\n```text\nAttrs Reverse(\n bool x\n)\n```"]]
