o Xi@s|dZddlmZddgZddlZddlZddlZddlm Z e e Z dd dZ GdddejjZdddddddZdS)z0Shape inference pass using onnx.shape_inference.) annotationsShapeInferencePass infer_shapesN) _c_api_utilsmodelir.Modelinferred_protoonnx.ModelProtoreturnboolc Cstj|}d}t||D]L\}}tj|}tj|}|D]7\}} ||vrT||} | j| jkrB| jdurB| j| _d}| j | j krS| j durS| j | _ d}q%t d||j q%q|S)a)Merge the shape inferred model with the original model. Args: model: The original IR model. inferred_proto: The ONNX model with shapes and types inferred. Returns: A tuple containing the modified model and a boolean indicating whether the model was modified. FNTz'Value %s not found in inferred graph %s) irserdedeserialize_modelzipgraphs conveniencecreate_value_mappingitemsshapedtypeloggerwarningname) rrinferred_modelmodifiedoriginal_graphinferred_graphoriginal_valuesinferred_valuesrvalueinferred_valuer!Y/home/ubuntu/.local/lib/python3.10/site-packages/onnx_ir/passes/common/shape_inference.py _merge_funcs(    r#cs0eZdZdZ ddfd d ZdddZZS)rz0This pass performs shape inference on the graph.T check_typer strict_mode data_propr Nonecs t||_||_||_dS)aSInitialize the shape inference pass. If inference fails, the model is left unchanged. Args: check_type: If True, check the types of the inputs and outputs. strict_mode: If True, use strict mode for shape inference. data_prop: If True, use data propagation for shape inference. N)super__init__r$r%r&)selfr$r%r& __class__r!r"r)8s  zShapeInferencePass.__init__rrir.passes.PassResultc szd fdd }zt||}Wn ty/}ztjd|dtj|dWYd}~Sd}~wwt||}tjj||d S) Nprotor r cstjj|jjjdS)Nr$r%r&)onnxshape_inferencerr$r%r&)r.r*r!r"partial_infer_shapesJs z5ShapeInferencePass.call..partial_infer_shapesz3Shape inference failed: %s. Model is left unchanged)exc_infoF)r)r.r r r ) r call_onnx_api Exceptionrrr passes PassResultr#)r*rr3inferred_model_protoerr!r2r"callIs zShapeInferencePass.call)TTT)r$r r%r r&r r r')rrr r-)__name__ __module__ __qualname____doc__r)r; __classcell__r!r!r+r"r5s Tr/r$r%r&cCst|||d|jS)a|Perform shape inference on the model. Args: model: The model to perform shape inference on. check_type: If True, check the types of the inputs and outputs. strict_mode: If True, use strict mode for shape inference. data_prop: If True, use data propagation for shape inference. Returns: The model with shape inference applied. r/)rr)rr$r%r&r!r!r"r\s)rrrr r r ) rrr$r r%r r&r r r)r? __future__r__all__loggingr0onnx_irr onnx_ir.passes.commonr getLoggerr<rr#r7 InPlacePassrrr!r!r!r"s     *