Research/py2onnx.py
def export_onnx_model(model,
                      input_shape,
                      onnx_path,
                      input_names=None,
                      output_names=None,
                      dynamic_axes=None):
    """Export Pytorch model to ONNX

    Helps in creating the ONNX file from the pytorch model.
    Actual code by zong fan
    https://medium.com/@fanzongshaoxing/accelerate-pytorch-model-with-tensorrt-via-onnx-d5b5164b369

    Args:
        model: The pytorch model
        input_shape: Dummy input shape for the model
        onnx_path: The path where the ONNX file needs to be saved
        input_names: Optional, List containing input labels
        output_names: Optional,  List containing output labels
        dynamic_axis: Optional, Dictionary for variable batch_size
    """
    inputs = torch.ones(*input_shape)
    model(inputs)
    torch.onnx.export(model,
                      inputs,
                      onnx_path,
                      input_names=input_names,
                      output_names=output_names,
                      dynamic_axes=dynamic_axes,
                      opset_version=11)
    return
Export Pytorch model to ONNX

    Helps in creating the ONNX file from the pytorch model.
    Actual code by zong fan
    https://medium.com/@fanzongshaoxing/accelerate-pytorch-model-with-tensorrt-via-onnx-d5b5164b369

    Args:
        model: The pytorch model
        input_shape: Dummy input shape for the model
        onnx_path: The path where the ONNX file needs to be saved
        input_names: Optional, List containing input labels
        output_names: Optional,  List containing output labels
        dynamic_axis: Optional, Dictionary for variable batch_size
    
Export Pytorch model to ONNX
Helps in creating the ONNX file from the pytorch model.
Export Pytorch model to ONNX Helps in creating the ONNX file from the pytorch model .
def export_onnx_model(model,
                      input_shape,
                      onnx_path,
                      input_names=None,
                      output_names=None,
                      dynamic_axes=None):
    inputs = torch.ones(*input_shape)
    model(inputs)
    torch.onnx.export(model,
                      inputs,
                      onnx_path,
                      input_names=input_names,
                      output_names=output_names,
                      dynamic_axes=dynamic_axes,
                      opset_version=11)
    return
def export_onnx_model ( model , input_shape , onnx_path , input_names = None , output_names = None , dynamic_axes = None ) : inputs = torch . ones ( * input_shape ) model ( inputs ) torch . onnx . export ( model , inputs , onnx_path , input_names = input_names , output_names = output_names , dynamic_axes = dynamic_axes , opset_version = 11 ) return
Export Pytorch model to ONNX
Helps in creating the ONNX file from the pytorch model.
Export Pytorch model to ONNX Helps in creating the ONNX file from the pytorch model .
"""Export Pytorch model to ONNX

    Helps in creating the ONNX file from the pytorch model.
    Actual code by zong fan
    https://medium.com/@fanzongshaoxing/accelerate-pytorch-model-with-tensorrt-via-onnx-d5b5164b369

    Args:
        model: The pytorch model
        input_shape: Dummy input shape for the model
        onnx_path: The path where the ONNX file needs to be saved
        input_names: Optional, List containing input labels
        output_names: Optional,  List containing output labels
        dynamic_axis: Optional, Dictionary for variable batch_size
    """
model
The pytorch model
The pytorch model
input_shape
Dummy input shape for the model
Dummy input shape for the model
onnx_path
The path where the ONNX file needs to be saved
The path where the ONNX file needs to be saved
input_names
Optional, List containing input labels
Optional List containing input labels
output_names
Optional,  List containing output labels
Optional List containing output labels
dynamic_axes
dynamic_axis
Optional, Dictionary for variable batch_size
Optional Dictionary for variable batch_size