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Supported Deep Learning Frameworks

Framework

Checkpoint File requirements

Framework Type

ONNX

Your ONNX model should be saved as a .onnx file, and must support inference with dynamic batch size.

"onnx"

TensorFlow

Infery supports TF2 saved-model format. zip the file's directory before uploading (zipped directory).

"tf2"

TensorFlow Lite

Infery can load .tflite models using TensorFlow's API.

"tflite"

CoreML

Infery can load .coreml models using the coreml-tools package.

"coreml"

TorchScript

Make sure to save your traced TorchScript module as a .pth file.

"torchscript"

Keras

Save your Keras model in .h5 format. Make sure to save both the architecture and the weights.

"keras"

OpenVino

A CPU optimized checkpoint that was optimized by the Deci Platform.

"openvino"

Nvidia TensorRT

A GPU optimized checkpoint that was optimized by the Deci Platform.

Infery can also load TensorRT checkpoints, when saving them as described Here.

Please note that TensorRT is version sensitive, so the current supported version is 8.0.1.6

"trt"


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