Supported Framework Types

Table 1 lists the supported original framework types, input data types, and model files.

**Table 1** Supported framework types
Original Framework Type	Input Data Type	Model File Description
Caffe	FP32 FP16: implemented by setting the input option --input_fp16_nodes. UINT8: implemented by configuring data preprocessing. NOTE: The input can be up to 4-dimensional. Operators involving dimension changes (such as reshape and expanddim) cannot output five dimensions.	Model file: **xxx.prototxt Weight file: xxx.caffemodel The op_name and op_type** in the model file must be the same as those in the weight file (case sensitive).
TensorFlow	FP16 FP32 UINT8 INT32 INT64 BOOL NOTE: The output data type cannot be INT64. You need to change the data type from INT64 to INT32.	Model file: **xxx.pb** Only .pb models in FrozenGraphDef format can be converted.
ONNX	FP32 FP16: implemented by setting the input option --input_fp16_nodes. UINT8: implemented by configuring data preprocessing.	Model file: **xxx.onnx**
MindSpore	FP32 UINT8: implemented by configuring data preprocessing.	Model file: **xxx.air**

Parent topic: Model Conversion