Closed enzoferrari1 closed 3 months ago
need_simplify
is recommended to be enabled as it will optimize the compute graph without affecting accuracy.
`from onnx2tflite import onnx_converter
res = onnx_converter( onnx_model_path = "/content/parseq.onnx", need_simplify = True, output_path = "/content/", target_formats = ['tflite'], )`
IndexError Traceback (most recent call last)
1 frames /content/onnx2tflite/onnx2tflite/components/builder.py in keras_builder(onnx_model, native_groupconv) 49 # init layout 50 for index in range(len(node_outputs)): ---> 51 layout_dict[node_outputs[index]] = layout_dict.get(node_inputs[0], Layout.Default) 52 53 res = tf_operator(tf_tensor, onnx_weights, node_inputs, op_attr, node_outputs, layout_dict)(_inputs)
IndexError: list index (0) out of range`
When doing conversion of my YOLOv10 n model, an error occurs while using the converter with need_simplify = False. I don't want to quantize the model because it loses too much accuracy in the case of YOLO.
shows error