edge-mdt-cl-dev 1.0.0.dev1

Edge MDT Custom Layers package

Edge MDT Custom Layers (EdgeMDT CL)

Edge MDT Custom Layers (EdgeMDT CL) is an open-source project implementing detection post process NN layers not supported by the TensorFlow Keras API or Torch's torch.nn for the easy integration of those layers into pretrained models.

Table of Contents

• Getting Started
  • Installation
  • Supported Versions
• API
  • TensorFlow API
  • PyTorch API
• License

Getting Started

This section provides an installation and a quick starting guide.

Installation

To install the latest stable release of SCL, run the following command:

pip install edge-mdt-cl

By default, no framework dependencies are installed. To install SCL including the latest tested dependencies (up to patch version) for TensorFlow:

pip install edge-mdt-cl[tf]

To install SCL including the latest tested dependencies (up to patch version) for PyTorch/ONNX/OnnxRuntime:

pip install edge-mdt-cl[torch]

Supported Versions

TensorFlow

Tested FW versions	Tested Python version	Serialization
2.10	3.9-3.10	.h5
2.11	3.9-3.10	.h5
2.12	3.9-3.11	.h5 .keras
2.13	3.9-3.11	.keras
2.14	3.9-3.11	.keras
2.15	3.9-3.11	.keras

PyTorch

Tested FW versions	Tested Python version	Serialization
torch 2.0-2.4 torchvision 0.15-0.19 onnxruntime 1.15-1.19 onnxruntime_extensions 0.8-0.12 onnx 1.14-1.16	3.9-3.12	.onnx (via torch.onnx.export)

API

For edge-mdt-cl API see https://sonysemiconductorsolutions.github.io/aitrios-edge-mdt-cl

TensorFlow API

For TensorFlow layers see KerasAPI

To load a model with custom layers in TensorFlow, see custom_layers_scope

PyTorch API

For PyTorch layers see PyTorchAPI

No special handling is required for torch.onnx.export and onnx.load.

For OnnxRuntime support see load_custom_ops

License

Apache License 2.0.