OpenVINO Toolkit
Converting and Preparing Models
Model Optimizer Developer Guide
Model Optimizer Developer Guide
Preparing and Optimizing Your Trained Model
Preparing and Optimizing Your Trained Model
Configuring the Model Optimizer
Converting a Model to Intermediate Representation (IR)
Converting a Model to Intermediate Representation (IR)
Converting a Model Using General Conversion Parameters
Converting a Caffe* Model
Converting a TensorFlow* Model
Converting a TensorFlow* Model
Converting YOLO* Models from DarkNet to the Intermediate Representation
Converting FaceNet Models from TensorFlow
Converting Neural Collaborative Filtering Model from TensorFlow
Converting DeepSpeech Model from TensorFlow
Converting Language Model on One Billion Word Benchmark from TensorFlow
Converting TensorFlow* Object Detection API Models
Converting TensorFlow*-Slim Image Classification Model Library Models
Converting CRNN Model from TensorFlow
Converting GNMT from TensorFlow
Converting BERT from TensorFlow
Convert TensorFlow* XLNet Model to the Intermediate Representation
Converting TensorFlow* Wide and Deep Models from TensorFlow
Converting EfficientDet Models from TensorFlow
Converting a MXNet* Model
Converting a MXNet* Model
Converting a Style Transfer Model from MXNet
Converting GluonCV* Models
Converting Your Kaldi* Model
Converting Your Kaldi* Model
Convert Kaldi* ASpIRE Chain Time Delay Neural Network (TDNN) Model to the Intermediate Representation
Converting Your ONNX* Model
Converting Your ONNX* Model
Convert ONNX* Faster R-CNN Model to the Intermediate Representation
Convert ONNX* Mask R-CNN Model to the Intermediate Representation
Convert ONNX* GPT-2 Model to the Intermediate Representation
Convert DLRM ONNX* Model to the Intermediate Representation
Converting Your PyTorch* Model
Converting Your PyTorch* Model
Convert PyTorch* QuartzNet Model
Convert PyTorch* YOLACT Model
Convert PyTorch* F3Net Model
Model Optimizations Techniques
Cutting off Parts of a Model
Sub-graph Replacement in Model Optimizer
Supported Framework Layers
[DEPRECATED] IR Notation Reference
IR suitable for INT8 inference
Model Optimizer Extensibility
Model Optimizer Extensibility
Extending Model Optimizer with New Primitives
Extending Model Optimizer with Caffe* Python Layers
Extending Model Optimizer for Custom MXNet* Operations
Legacy Mode for Caffe* Custom Layers
[DEPRECATED] Offloading Sub-Graph Inference
Model Optimizer Frequently Asked Questions
Known Issues
Model Downloader
Custom Operations Guide
Custom Operations Guide
Intermediate Representation and Operations Sets
Intermediate Representation and Operations Sets
Available Operations Sets
Available Operations Sets
opset7 Specification
opset6 Specification
opset5 Specification
opset4 Specification
opset3 Specification
opset2 Specification
opset1 Specification
Operations Specifications
Abs-1
Acos-1
Acosh-3
Add-1
Asin-1
Asinh-3
Assign-3
Atan-1
Atanh-3
AvgPool-1
BatchNormInference-1
BatchNormInference-5
BatchToSpace-2
BinaryConvolution-1
Broadcast-1
Broadcast-3
Bucketize-3
CTCGreedyDecoder-1
CTCGreedyDecoderSeqLen-6
Ceiling-1
Clamp-1
Concat-1
Constant-1
ConvertLike-1
Convert-1
ConvolutionBackpropData-1
Convolution-1
Cos-1
Cosh-1
CTCLoss-4
CumSum
DeformableConvolution-1
DeformablePSROIPooling-1
DepthToSpace-1
DetectionOutput-1
DFT-7
Divide-1
Einsum-7
Elu-1
EmbeddingBagOffsetsSum-3
EmbeddingBagPackedSum-3
EmbeddingSegmentsSum-3
Equal-1
Erf-1
Exp-1
ExperimentalDetectronDetectionOutput-6
ExperimentalDetectronGenerateProposalsSingleImage-6
ExperimentalDetectronPriorGridGenerator-6
ExperimentalDetectronROIFeatureExtractor-6
ExperimentalDetectronTopKROIs-6
ExtractImagePatches-3
FakeQuantize-1
FloorMod-1
Floor_1
GRN-1
GRUCell-3
GRUSequence-5
GatherTree-1
Gather-1
Gather-7
GatherElements-6
GatherND-5
Gelu-2
Gelu-7
GreaterEqual-1
Greater-1
GroupConvolutionBackpropData-1
GroupConvolution-1
HardSigmoid-1
HSigmoid-5
HSwish-4
IDFT-7
Interpolate-1
Interpolate-4
LRN-1
LSTMCell-1
LSTMSequence-1
LessEqual-1
Less-1
Log-1
LogicalAnd-1
LogicalNot-1
LogicalOr-1
LogicalXor-1
LogSoftmax-5
Loop-5
MVN-1
MVN-6
MatMul-1
MaxPool-1
Maximum-1
Minimum-1
Mish-4
Mod-1
Multiply-1
Negative-1
NonMaxSuppression-1
NonMaxSuppression-3
NonMaxSuppression-4
NonMaxSuppression-5
NonZero-3
NormalizeL2-1
NotEqual-1
OneHot-1
PReLU-1
PSROIPooling-1
Pad-1
Parameter-1
Power-1
PriorBoxClustered-1
PriorBox-1
Proposal-1
Proposal-4
Range-1
Range-4
ReadValue-3
ReLU-1
ReduceL1-4
ReduceL2-4
ReduceLogicalAnd-1
ReduceLogicalOr-1
ReduceMax-1
ReduceMean-1
ReduceMin-1
ReduceProd-1
ReduceSum-1
RegionYolo-1
ReorgYolo-1
Reshape-1
Result-1
Reverse
ReverseSequence-1
RNNCell-3
RNNSequence-5
ROIAlign-3
ROIPooling-1
Roll-7
Round-5
ScatterElementsUpdate-3
ScatterNDUpdate
ScatterUpdate-3
Select-1
Selu-1
ShapeOf-1
ShapeOf-3
ShuffleChannels-1
Sigmoid-1
Sign-1
Sin-1
Sinh-1
SoftMax-1
SoftPlus-4
SpaceToBatch-2
SpaceToDepth-1
Split-1
Sqrt-1
SquaredDifference-1
Squeeze-1
StridedSlice-1
Subtract-1
Swish-4
Tan-1
Tanh-1
TensorIterator-1
Tile-1
TopK-1
TopK-3
Transpose-1
Unsqueeze-1
VariadicSplit-1
Deploying Inference
Deploying Inference
Inference Engine Developer Guide
Inference Engine Developer Guide
Inference Engine API Changes History
Inference Engine Memory primitives
Inference Engine Device Query API
Inference Engine Extensibility Mechanism
Inference Engine Extensibility Mechanism
Extension Library
Custom Operations
CPU Kernels Extensibility
GPU Kernels Extensibility
VPU Kernels Extensibility
Build Extension Library Using CMake
Custom ONNX operators
Integrate the Inference Engine with Your Application
[DEPRECATED] Migration from Inference Engine Plugin API to Core API
Introduction to Performance Topics
Inference Engine Python* API Overview
Read an ONNX model
[DEPRECATED] Import an ONNX model
Using Dynamic Batching Feature
Using Static Shape Infer Feature
Using GPU kernels tuning
Using Bfloat16 Inference
Using Bfloat16 Inference
Using Low-Precision 8-bit Integer Inference
Using Low-Precision 8-bit Integer Inference
Utilities to Validate Your Converted Model
Utilities to Validate Your Converted Model
Using Cross Check Tool for Per-Layer Comparison Between Plugins
Introduction to OpenVINO state API
Supported Devices
Supported Devices
GPU Plugin
GPU Plugin
RemoteBlob API of GPU Plugin
CPU Plugin
[DEPRECATED] FPGA Plugin
VPU Plugins
VPU Plugins
MYRIAD Plugin
HDDL Plugin
Heterogeneous Plugin
Multi-Device Plugin
GNA Plugin
Known Issues
Glossary
nGraph Developer Guide
nGraph Developer Guide
nGraph Developer Guide
Table of Contents
Introduction
Basic Concepts
Operation sets
Graph building
Transfomations
Debug capabilities
Python API
Deployment Manager Guide
Compile Tool
API References
Inference Engine C API Reference
Inference Engine Python API Reference
nGraph C++ API Reference
nGraph Python API Reference
Inference Engine Plugin Development Guide
OpenVINO Toolkit
Docs
»
nGraph Developer Guide »
Deploying Inference »
nGraph Developer Guide
nGraph Developer Guide
Table of Contents
Introduction to the nGraph
Basic Concepts
Operation Sets
Graph Constructing
Transformations
Debug Capabilities
Python API