o
    vik                     @   s  d Z ddlZddlZddlZddlmZ dd Z										ddeejB ej	B d	eejB d
e
de
de
dedB dede
dee dB dee dB deeeef  dB de
de
fddZedkre Zeejejejejejejejejejejejejd dS dS )z@Provide entry point to preprocess ONNX model especially for QNN.    N)qnnc                  C   s   t jdd} | jddddd | jdd	dd
d | jdddd | jdddd | jddd | jddtdd | jdddd | jdddd | jddddd  | jd!ddd"d  | jd#d$d%tdd&d' | jd(dd)d |  S )*zParse cmdline arguments.z#Arguments for QNN model preprocess.)descriptionz--input_model_pathz-iTzPath to the input ONNX model.)requiredhelpz--output_model_pathz-ozPath to the output ONNX model.z--save_as_external_data
store_truez;Whether the output model would be saved with external data.)actionr   z--all_tensors_to_one_filezgWhether to save all external data in one file or save each tensor to a file named with the tensor name.z--external_data_locationzbFilename of the external file where all tensors are saved. The path is relative to the model path.)r   z--external_data_size_threshold   zQTensors with data size larger than this threshold are converted to external data.)defaulttyper   z!--external_data_convert_attributezKWhether to save all tensors, including attribute tensors, to external data.z--fuse_layernormzLWhether to fuse matched sequences into LayerNormalization nodes if possible.z--inputs_to_make_channel_last+Nz=List of graph input names to be transposed into channel-last.)nargsr	   r   z--outputs_to_make_channel_lastz>List of graph output names to be transposed into channel-last.z--dynamic_input_shapes   appendzdModel input name and desired static shape in comma seprated format, for example: 'input' 1,3,256,256)r   r   r
   r	   r   z --exclude_initializer_from_inputzBWhether to exclude initializer from input if model.ir_version >= 4)argparseArgumentParseradd_argumentintstr
parse_args)parser r   _/home/air/biblejyuku/back/venv/lib/python3.10/site-packages/onnxruntime/tools/qnn/preprocess.py_parse_arguments   sv   
r   Fr   model_inputmodel_outputfuse_layernormsave_as_external_dataall_tensors_to_one_fileexternal_data_locationexternal_data_size_thresholdexternal_data_convert_attributeinputs_to_make_channel_lastoutputs_to_make_channel_lastdynamic_input_shapesexclude_initializer_from_inputreturnc                 C   s"   t j| |||||||||	|
|dS )a<  Preprocess ONNX model for QNN.

    Args:
        model_input: A path or ONNX ModelProto specifiying the model to be preprocessed.
        model_output: A path specifying where the preprocessed model to be saved.
        fuse_layernorm: A bool specifying whether to fuse the matched sequence into a single LayerNormalization node.
            Defaults to False.
        save_as_external_data: A bool specifying whether to save model with external data. Defaults to False.
        all_tensors_to_one_file: A bool specifying whether to save all external data in one file or save each tensor to
            a file named with the tensor name. This argument is effective only when `save_as_external_data` is True.
            Defaults to False.
        external_data_location: A str specifying where to save the external data. The path is relative to the model
            path. This argument is effective only when `save_as_external_data` is True. Defaults to the model name.
        external_data_size_threshold: An int specifying the threshold of data size for tensors be saved as external
            data. This argument is effective only when `save_as_external_data` is True. Defaults to 1024.
        external_data_convert_attribute: A bool specifying whether to save all tensors including attributes as external
            data. This argument is effective only when `save_as_external_data` is True. Defaults to False.
        inputs_to_make_channel_last: A list of strs specifying graph input names to be transposed into channel-last.
            Defaults to None.
        outputs_to_make_channel_last: A list of strs specifying graph output names to be transposed into channel-last.
            Defaults to None.
        dynamic_input_shapes: A list of tuples specifying model input name to and its static shape in comma seprated
            format, for example: [('input', '1,3,256,256')]. Defaults to None.
        exclude_initializer_from_input: A bool specifying whether to exclude initializer from input. Defaults to False.

    Returns:
        A bool indicating whether the model is modified.
    
r   r   r   r   r   r    r!   r"   r#   r$   )r   qnn_preprocess_model)r   r   r   r   r   r   r   r    r!   r"   r#   r$   r   r   r   r'   \   s   *r'   __main__r&   )
FFFNr   FNNNF)__doc__r   pathlibonnx,onnxruntime.quantization.execution_providersr   r   r   Path
ModelProtoboolr   listtupler'   __name__argsinput_model_pathoutput_model_pathr   r   r   r   r   r    r!   r"   r#   r$   r   r   r   r   <module>   sx   O
	


:
