o ;ήc~@sddlZddlZddlZddlmZddlZddlZddlmZddl m Z e e Z          dd ed ed ed ededededededededededdfddZdS)N)Path)SymbolicShapeInference)add_pre_process_metadataF./input_model_pathoutput_model_pathskip_optimizationskip_onnx_shapeskip_symbolic_shape auto_mergeint_maxguess_output_rankverbosesave_as_external_dataall_tensors_to_one_fileexternal_data_locationexternal_data_size_thresholdreturnc  Cstjdd} t| }d}|s tdtt|||||}|sp|s2t |d}t ||d}t |d}zt }||_ t jj|_t j||dgd}Wntym}ztd ttWYd}~nd}~ww|}|s|durt |d}| rtj||d | | d d nt ||d}t |d }tj||t|}Wdn1swY|durt|}t|| rtj||d | | | d ddSt ||dS)aShape inference and model optimization, in preparation for quantization. Args: input_model_path: Path to the input model file") output_model_path: Path to the output model file skip_optimization: Skip model optimization step if true. This may result in ONNX shape inference failure for some models. skip_onnx_shape: Skip ONNX shape inference. Symbolic shape inference is most effective with transformer based models. Skipping all shape inferences may reduce the effectiveness of quantization, as a tensor with unknown shape can not be quantized. skip_symbolic_shape: Skip symbolic shape inference. Symbolic shape inference is most effective with transformer based models. Skipping all shape inferences may reduce the effectiveness of quantization, as a tensor with unknown shape can not be quantized. auto_merge: For symbolic shape inference, automatically merge symbolic dims when conflict happens. int_max: For symbolic shape inference, specify the maximum value for integer to be treated as boundless for ops like slice guess_output_rank: Guess output rank to be the same as input 0 for unknown ops verbose: Logs detailed info of inference, 0: turn off, 1: warnings, 3: detailed save_as_external_data: Saving an ONNX model to external data all_tensors_to_one_file: Saving all the external data to one file external_data_location: The file location to save the external file external_data_size_threshold: The size threshold for external data z pre.quant.)prefixNz&Performing symbolic shape inference...zsymbolic_shape_inferred.onnxzoptimized.onnxCPUExecutionProvider) providerszYONNX Runtime Model Optimization Failed! Consider rerun with option `--skip_optimization'.TF)rrsize_thresholdconvert_attributezonnx_shape_inferred.onnx)rrlocationrr)tempfileTemporaryDirectoryrloggerinfor infer_shapesonnxloadstrsave onnxruntimeSessionOptionsoptimized_model_filepathGraphOptimizationLevelORT_ENABLE_BASICgraph_optimization_levelInferenceSession Exceptionerror traceback format_exc save_modelshape_inferenceinfer_shapes_pathr)r r r r r rrrrrrrr quant_tmp_dir temp_pathmodelopt_model_path sess_option_einferred_model_pathr<O/tmp/pip-target-vg8gfxp4/lib/python/onnxruntime/quantization/shape_inference.pyquant_pre_processs)         <   r>) FFFFrFrFFrr)loggingrr/pathlibrr"r&&onnxruntime.tools.symbolic_shape_inferr quant_utilsr getLogger__name__rr$boolintr>r<r<r<r=sb