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tensorflow::ops::QuantizedConv2D
#include <nn_ops.h>
Computes a 2D convolution given quantized 4D input and filter tensors.
Summary
The inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.
Args:
- scope: A Scope object
- filter: filter's input_depth dimension must match input's depth dimensions.
- min_input: The float value that the lowest quantized input value represents.
- max_input: The float value that the highest quantized input value represents.
- min_filter: The float value that the lowest quantized filter value represents.
- max_filter: The float value that the highest quantized filter value represents.
- strides: The stride of the sliding window for each dimension of the input tensor.
- padding: The type of padding algorithm to use.
Optional attributes (see Attrs):
- dilations: 1-D tensor of length 4. The dilation factor for each dimension of
input. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format, see above for details. Dilations in the batch and depth dimensions must be 1.
Returns:
Output outputOutput min_output: The float value that the lowest quantized output value represents.Output max_output: The float value that the highest quantized output value represents.
Constructors and Destructors
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QuantizedConv2D(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input min_input, ::tensorflow::Input max_input, ::tensorflow::Input min_filter, ::tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding)
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QuantizedConv2D(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input min_input, ::tensorflow::Input max_input, ::tensorflow::Input min_filter, ::tensorflow::Input max_filter, const gtl::ArraySlice< int > & strides, StringPiece padding, const QuantizedConv2D::Attrs & attrs)
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Public static functions
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Dilations(const gtl::ArraySlice< int > & x)
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OutType(DataType x)
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Public attributes
Public functions
Public static functions
Dilations
Attrs Dilations(
const gtl::ArraySlice< int > & x
)
OutType
Attrs OutType(
DataType x
)
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::QuantizedConv2D Class Reference\n\ntensorflow::ops::QuantizedConv2D\n================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes a 2D convolution given quantized 4D input and filter tensors.\n\nSummary\n-------\n\nThe inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- filter: filter's input_depth dimension must match input's depth dimensions.\n- min_input: The float value that the lowest quantized input value represents.\n- max_input: The float value that the highest quantized input value represents.\n- min_filter: The float value that the lowest quantized filter value represents.\n- max_filter: The float value that the highest quantized filter value represents.\n- strides: The stride of the sliding window for each dimension of the input tensor.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs)):\n\n- dilations: 1-D tensor of length 4. The dilation factor for each dimension of `input`. If set to k \\\u003e 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) min_output: The float value that the lowest quantized output value represents.\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) max_output: The float value that the highest quantized output value represents.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [QuantizedConv2D](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a8376b9a3557650a011f9c6edb484ec8b)`(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)` input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [QuantizedConv2D](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1aa852757615972228954f6d67b3bb8d59)`(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)` input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[QuantizedConv2D::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [max_output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a66d14c5a2888abbc7ae9e711a2fdced8) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [min_output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1aac559559eda7e4da378605b1b88d3320) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1a36cc12c83f91d1503e6cdeadc7e43272) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1af1401fc53bb8d0556a50807c662bbd61) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public static functions ||\n|-----------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [Dilations](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1ae5e27c80b00ace7bafa06479bc01ac5e)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs) |\n| [OutType](#classtensorflow_1_1ops_1_1_quantized_conv2_d_1ad52eb17c8042ea7f90ded915f9f2aa53)`(DataType x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs#structtensorflow_1_1ops_1_1_quantized_conv2_d_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::QuantizedConv2D::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/quantized-conv2-d/attrs) | Optional attribute setters for [QuantizedConv2D](/versions/r2.14/api_docs/cc/class/tensorflow/ops/quantized-conv2-d#classtensorflow_1_1ops_1_1_quantized_conv2_d). |\n\nPublic attributes\n-----------------\n\n### max_output\n\n```scdoc\n::tensorflow::Output max_output\n``` \n\n### min_output\n\n```scdoc\n::tensorflow::Output min_output\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### QuantizedConv2D\n\n```gdscript\n QuantizedConv2D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n ::tensorflow::Input min_input,\n ::tensorflow::Input max_input,\n ::tensorflow::Input min_filter,\n ::tensorflow::Input max_filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### QuantizedConv2D\n\n```gdscript\n QuantizedConv2D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n ::tensorflow::Input min_input,\n ::tensorflow::Input max_input,\n ::tensorflow::Input min_filter,\n ::tensorflow::Input max_filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const QuantizedConv2D::Attrs & attrs\n)\n``` \n\nPublic static functions\n-----------------------\n\n### Dilations\n\n```gdscript\nAttrs Dilations(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \n\n### OutType\n\n```text\nAttrs OutType(\n DataType x\n)\n```"]]
