Stay organized with collections
Save and categorize content based on your preferences.
tensorflow::ops::QuantizedConcat
#include <array_ops.h>
Concatenates quantized tensors along one dimension.
Summary
Args:
- scope: A Scope object
- concat_dim: 0-D. The dimension along which to concatenate. Must be in the range [0, rank(values)).
- values: The
N
Tensors to concatenate. Their ranks and types must match, and their sizes must match in all dimensions except concat_dim
.
- input_mins: The minimum scalar values for each of the input tensors.
- input_maxes: The maximum scalar values for each of the input tensors.
Returns:
Output
output: A Tensor
with the concatenation of values stacked along the concat_dim
dimension. This tensor's shape matches that of values
except in concat_dim
where it has the sum of the sizes.
Output
output_min: The float value that the minimum quantized output value represents.
Output
output_max: The float value that the maximum quantized output value represents.
Public attributes
Public functions
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::QuantizedConcat Class Reference\n\ntensorflow::ops::QuantizedConcat\n================================\n\n`#include \u003carray_ops.h\u003e`\n\nConcatenates quantized tensors along one dimension.\n\nSummary\n-------\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- concat_dim: 0-D. The dimension along which to concatenate. Must be in the range \\[0, rank(values)).\n- values: The `N` Tensors to concatenate. Their ranks and types must match, and their sizes must match in all dimensions except `concat_dim`.\n- input_mins: The minimum scalar values for each of the input tensors.\n- input_maxes: The maximum scalar values for each of the input tensors.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output: A [Tensor](/versions/r2.14/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with the concatenation of values stacked along the `concat_dim` dimension. This tensor's shape matches that of `values` except in `concat_dim` where it has the sum of the sizes.\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_min: The float value that the minimum quantized output value represents.\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_max: The float value that the maximum quantized output value represents.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [QuantizedConcat](#classtensorflow_1_1ops_1_1_quantized_concat_1a6ebd37038b8fed1e45c560d7e7fcbc2b)`(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)` concat_dim, ::`[tensorflow::InputList](/versions/r2.14/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` values, ::`[tensorflow::InputList](/versions/r2.14/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` input_mins, ::`[tensorflow::InputList](/versions/r2.14/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` input_maxes)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_quantized_concat_1af047989041a8b8eba230e0651d46c9e8) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_quantized_concat_1a7b1bfd305adec2548519a7de10e9381f) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_max](#classtensorflow_1_1ops_1_1_quantized_concat_1a34abcaca945d5e8b09df9e778b96983f) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_min](#classtensorflow_1_1ops_1_1_quantized_concat_1ac7e70b4452898593c806e108bc1daff0) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\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\n### output_max\n\n```scdoc\n::tensorflow::Output output_max\n``` \n\n### output_min\n\n```scdoc\n::tensorflow::Output output_min\n``` \n\nPublic functions\n----------------\n\n### QuantizedConcat\n\n```gdscript\n QuantizedConcat(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input concat_dim,\n ::tensorflow::InputList values,\n ::tensorflow::InputList input_mins,\n ::tensorflow::InputList input_maxes\n)\n```"]]