o i e@#@sdZddlZddlZddlZddlmZddlmZddlm Z ddl m Z ddZ d d Z d d Zd#d dZd#ddZddZddZddZddZddZddZddZGdd d eZd!d"ZdS)$z3Exposes the Python wrapper conversion to trt_graph.N)version)_pywrap_py_utils)rewriter_config_pb2)dtypescCs~tjj}||_||_d|j_||_||_||_ d|_ d|_ ||_ ||_ ||_||_tjj|_d|_||_||_||_||_dS)z>Modifies rewriter_config to disable all non-TRT optimizations.FTN)rRewriterConfigOFFarithmetic_optimizationauto_mixed_precision auto_parallelenableconstant_foldingdebug_stripperdependency_optimizationdisable_meta_optimizerdisable_model_pruningfunction_optimizationimplementation_selectorlayout_optimizerloop_optimization NO_MEM_OPTmemory_optimizationmin_graph_nodespin_to_host_optimization remappingscoped_allocator_optimizationshape_optimization)rewriter_configoffrX/var/www/myenv/lib/python3.10/site-packages/tensorflow/python/compiler/tensorrt/utils.py-disable_non_trt_optimizers_in_rewriter_configs( r!cCs6t|tsJt|dksJdd|D}d|S)NcSsg|]}t|qSr)str).0xrrr :sz+version_tuple_to_string...) isinstancetuplelenjoin) ver_tuplerrr version_tuple_to_string6s r-cCs$tt|}tt|}||kSN)rVersionr-)trt_ver target_verrrr "_is_tensorrt_version_greater_equal>sr2cCt}t||||fSr.)rget_linked_tensorrt_versionr2majorminorpatchverrrr (is_linked_tensorrt_version_greater_equalEr:cCr3r.)rget_loaded_tensorrt_versionr2r5rrr (is_loaded_tensorrt_version_greater_equalJr;r=cCs|tjjddddvS)a!Determines if a TF-TRT experimental feature is enabled. This helper function checks if an experimental feature was enabled using the environment variable `TF_TRT_EXPERIMENTAL_FEATURES=feature_1,feature_2`. Args: feature_name: Name of the feature being tested for activation. TF_TRT_EXPERIMENTAL_FEATURES)default,)osenvirongetsplit) feature_namerrr !is_experimental_feature_activatedOs  rGcCs"t|tr tj|Sdd|DS)zEHelper function to convert a dtype id to a corresponding string name.cSsg|]}tj|qSr)r_TYPE_TO_STRING)r$drrr r&csz,_convert_dtype_id_to_str..)r(intrrH)dtyperrr _convert_dtype_id_to_str^s  rLc CsdD]M}z9|j|}|dkr6|jd}|dkrWq|dkr"WdS|dkr*WdS|d kr2Wd SWd St|jWStyO}zWYd }~qd }~wwd S) z-Returns the compute DType of a GraphDef Node.)precision_modeDstTrKTrMzutf-8r?FP32float32FP16float16INT8int8unknownN)attrsdecoderLtype Exception)nodetype_key precision_valerrr get_node_compute_dtypefs(   r`cCs2g}|j|jjD] }|dd|jDq |S)z3Returns the input/output shapes of a GraphDef Node.cSsg|]}|jqSr)size)r$dimrrr r&sz&get_node_io_shapes..)rWlistshapeappendrb)r\key out_shaperdrrr get_node_io_shapessrhcCt|j|jjS)z1Returns the input/output dtypes of a TRTEngineOp.)rLrWrcrZr\rfrrr get_trtengineop_io_dtypesrkcCri)z:Returns the number of input/output nodes of a TRTEngineOp.)r*rWrcrZrjrrr get_trtengineop_io_nodes_countrlrmcCsdtt}|jjD]$}|d|jjkr-t|j}|jD] }||j d7<q||fSq ||fS)z?Counts the number of nodes and OP types of a given TRTEngineOp._native_segment) collections defaultdictrJlibraryfunction signaturenamer*node_defop)graphdef node_name ops_in_enginefunc node_countr\rrr get_trtengineop_node_op_counts    r}c@seZdZdZddZdS) DTypeIndexzBHelper class to create an index of dtypes with incremental values.cCs ||vr t|d||<||S)Nro)r*)selfrKrrr get_dtype_indexszDTypeIndex.get_dtype_indexN)__name__ __module__ __qualname____doc__rrrrr r~s r~c Cstt}t|d}td|dtd|dtd|dtd|dtd|dg}|jD]x}|j}t|}||}|jdd } | sGd } |j d kr\t ||\} } |d | d } n|j } d| d| d} td|d| d|d|dt |j r|j D]} | d}t dd|d}td|d|d|dqq-||q-td|dtd|dtd|dtd|dtd |d|D]\}}td!|d"|d#|d$|dqtd|dtd%|d|D]}|D]}td|d|d&|dqqtd'|dWd(n 1swYtd)td*|d+td,td-td.td/td0d(S)1a9Exports a GraphDef to GraphViz format. - Step 1: Drawing Each Node of the compute GraphDef. - Step 2: Create nodes for each collected dtype in the graph. - Step 3: Creating invisible links to align properly the legend. Each node consequently mentions: - Op Type - Compute Dtype - Compute Device wzdigraph tftrt_converted_graph {)filez) graph [fontsize=10 fontname="Verdana"];z? node [style=filled height=0.55 colorscheme=set312 shape=box];z subgraph tensorflow_graph {z node [width=1.35];/rzdevice:Unspecified TRTEngineOpz []zz
zz "z " [label= fillcolor=z];:z^\^r?rz "z" -> "z";z }z subgraph cluster_legend {z! label="Compute Dtype Legend";z margin="30";z node [width=2];z z [fillcolor=z label=<z>];z' edge[style="invisible", dir="none"];"}NzD ===================================================================z"Graph Visualization Exported to: `z`.zBWe recommend using https://edotor.net/ to visualize the .dot file.zBYou can also use `graphviz` utility to convert them to PNG format:z" - `sudo apt install -y graphviz`z= - `dot -Tpng .dot -o .png`zD=================================================================== )r~openprintr\rur`rdevicerErwr}r*inputresubreitemskeys)rxdot_output_filename dtype_indexfnodes_with_no_inputsr\ output_namenode_precision color_idx device_keyr|_ node_labelinput_full_nameparts input_namerKryrrr draw_graphdef_as_graphvizsz                    C r)rr)rrprBr packagingrtensorflow.compiler.tf2tensorrtrtensorflow.core.protobufrtensorflow.python.frameworkrr!r-r2r:r=rGrLr`rhrkrmr}dictr~rrrrr s,