(15, 15, 1) dtype: <dtype: 'float32'> INFO: onnx_op_type: CumSum onnx_op_name: /backbone/backbone.1/CumSum_1 INFO: input_name.1: /backbone/backbone.1/Cast_output_0 shape: [1, 15, 15] dtype: float32 INFO: input_name.2: /backbone/backbone.1/Constant_2_output_0 shape: []...
python/tvm/relay/frontend/onnx.py Original file line numberDiff line numberDiff line change @@ -1379,6 +1379,302 @@ def massage(tensor): return _expr.TupleWrapper(_expr.Tuple([output, present]), 2) class QAttention(OnnxOpConverter): """Operator converter for QAttention from Microsoft ...
…rib opset (apache#13797) * add type & shape checking * add base class for Attention converter * add support for 'past' input * add support for 'unidirectional' attribute * fix for 'huggingface implementation' * add common method for calculating Attention * expand test coverage for Attention...
modelconverter convert rvc3 --path configs/resnet18.yaml \ inputs.0.name input_1 \ inputs.0.shape "[1,3,256,256]" \ outputs.0.name output_0Specify all options via the command line without a config file:modelconverter convert rvc2 input_model models/yolov6n.onnx \ scale_values "[...
134 prog = frontend_converter(model, **kwargs) 135 common_pass(prog) 136 ~/opt/anaconda3/envs/torch/lib/python3.8/site-packages/coremltools/converters/mil/converter.py in __call__(self, *args, **kwargs) 82 from .frontend.torch import load 83 ---> 84 return load(*args, **kwargs...