BVhdZddlZddlZddlZddlZddlZddlmZddlmZddl m Z ddl Z ddl mZddlmZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZddlm Z ddl!m"Z"ddl#m$Z%ddl&m'Z'ddl&m(Z(ddl&m)Z)ddl&m*Z*ddl&m+Z+ddl,m-Z-ddl,m.Z.ddl/m0Z0ddl1m2Z2dZ3e4gdZ5ejldddZ7ejpd d!d"Z9ejld#dd$Z:ejld%dd&Z;ejpd'd!d(Z<ejld)d*d+Z=ejld,d*d-Z>ejld.d*d/Z?ejld0dd1Z@ejpd2d!d3ZAejpd4d!d5ZBejld6dd7ZCejpd8d!d9ZDejpd:d!d;ZEejlddd?ZGejd@dAdBZIejdCdDgdEdFGZKejdHdIdJZLejpdKd!dLZMejldMddNZNejldOe+jdPZPejldQddRZQejldSd*dTZRejdUk(rejldVd*dWZTnejldVdXdYZTejldZd*d[ZUejld\dd]ZVejld^d_d`ZWdggdadggdbgdcd\gddZXdeZYdfZZdgZ[dhZ\diZ]djZ^dkZ_dlZ`ddmZadnZbddoZcddpZddqZedrZfdsZgdtZhduZi ddvZjdwZkddxZldyZmdzZnd{Zod|Zpd}Zqd~ZrdZsdZtdZudZvdZwdZxdZydZzdZ{dZ|dZ}e~dk(re}yy)zCommand-line interface to inspect and execute a graph in a SavedModel. For detailed usages and examples, please refer to: https://www.tensorflow.org/guide/saved_model#cli_to_inspect_and_execute_savedmodel N)app)flags)argparse_flags) example_pb2) types_pb2) config_pb2)session)local_cli_wrapper) def_function)function) meta_graph)ops) tensor_spec)file_io) tf_logging)load) load_options)loader)save)signature_constants)saved_model_aot_compile)saved_model_utils)tpu)collections_abczchttps://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/xla/debug_options_flags.cc) WriteFileReadFilePrintV2dirz$Directory containing the SavedModel.)namedefaulthelpallFzBIf set, outputs all available information in the given SavedModel.tag_setzKComma-separated set of tags that identify variant graphs in the SavedModel. signature_defz^Specifies a SignatureDef (by key) within the SavedModel to display input(s) and output(s) for.list_opszDIf set, will output ops used by a MetaGraphDef specified by tag_set.inputszSpecifies input data files to pass to numpy.load(). Format should be '=' or '=[]', separated by ';'. File formats are limited to .npy, .npz, or pickle. input_exprsaESpecifies Python literal expressions or numpy functions. Format should be "=''", separated by ';'. Numpy can be accessed with 'np'. Note that expressions are passed to literal_eval(), making this flag susceptible to code injection. Overrides duplicate input keys provided with the --inputs flag.input_exampleszSpecifies tf.train.Example objects as inputs. Format should be '=[{{feature0:value_list,feature1:value_list}}]', where input keys are separated by ';'. Overrides duplicate input keys provided with the --inputs and --input_exprs flags.outdirz7If specified, writes CLI output to the given directory. overwritez4If set, overwrites output file if it already exists.tf_debugz~If set, uses the Tensorflow Debugger (tfdbg) to watch intermediate Tensors and runtime GraphDefs while running the SavedModel.workerzFIf specified, runs the session on the given worker (bns or gRPC path).init_tpuznIf set, calls tpu.initialize_system() on the session. Should only be set if the specified worker is a TPU job.use_tfrtz6If set, runs a TFRT session, instead of a TF1 session. op_denylistzIf specified, detects and reports the given ops. List of ops should be comma-separated. If not specified, the default list of ops is [WriteFile, ReadFile, PrintV2]. To specify an empty list, pass in the empty string. output_dirz$Output directory for the SavedModel.max_workspace_size_bytesi zUThe maximum temporary GPU memory which the TensorRT engine can use at execution time.precision_modeFP32)r4FP16INT8z4TensorRT data precision. One of FP32, FP16, or INT8.)rr enum_valuesr!minimum_segment_sizezVThe minimum number of nodes required for a subgraph to be replaced in a TensorRT node.convert_tf1_modelz+Support TensorRT conversion for TF1 models. output_prefixzROutput directory + filename prefix for the resulting header(s) and object file(s).signature_def_keyz#SavedModel SignatureDef key to use.checkpoint_pathz?Custom checkpoint to use. Uses SavedModel variables by default.variables_to_feedajNames of the variables that will be fed into the SavedModel graph. Pass in '' to feed no variables, 'all' to feed all variables, or a comma-separated list of variable names. Variables not fed will be frozen. *NOTE* Variables passed here must be set *by the user*. These variables will NOT be frozen, and their values will be uninitialized in the compiled object.s390x target_triplezTriple identifying a target variation, containing information suchas processor architecture, vendor, operating system, and environment. Defaults to ''.zx86_64-pc-linuxzTriple identifying a target variation, containing information such as processor architecture, vendor, operating system, and environment. Defaults to 'x86_64-pc-linux'. target_cpuz{Target CPU name for LLVM during AOT compilation. Examples include 'x86_64', 'skylake', 'haswell', 'westmere', '' (unknown). cpp_classaThe name of the generated C++ class, wrapping the generated function. Format should be [[::],...], i.e. the same syntax as C++ for specifying a class. This class will be generated in the given namespace(s), or, if none are specified, the global namespace.multithreadingFalsezEnable multithreading in the compiled computation. Note that with this flag enabled, the resulting object files may have external dependencies on multithreading libraries, such as 'Abseil'.)rr#r$)rr1r#)rr;r#)showrunscanconvert freeze_modelaot_compile_cpuc tj|}tdt|D](}tddj t|z*y)zPrints the tag-sets stored in SavedModel directory. Prints all the tag-sets for MetaGraphs stored in SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect. z5The given SavedModel contains the following tag-sets:z%r, N)rget_saved_model_tag_setsprintsortedjoin)saved_model_dirtag_setsr#s W/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/tools/saved_model_cli.py_show_tag_setsrTsK 7 7 H(?@!-g $6'?+ +,-cRttj|jS)zReturns a set of the ops in the MetaGraph. Returns the set of all the ops used in the MetaGraphDef indicated by the tag_set stored in SavedModel directory. Args: meta_graph_def: MetaGraphDef to list the ops of. Returns: A set of ops. )setmeta_graph_libops_used_by_graph_def graph_defmeta_graph_defs rS_get_ops_in_metagraphr]s  ^ 1 1.2J2J K LLrUc`t|}td|jjz|y)Nz9The MetaGraph with tag set %s contains the following ops:)r]rN meta_info_deftags)r\ all_ops_sets rS_show_ops_in_metagraph_mgdrb s.%n5+A$$))*rUcFtj||}t|y)avPrints the ops in the MetaGraph. Prints all the ops used in the MetaGraphDef indicated by the tag_set stored in SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect. tag_set: Group of tag(s) of the MetaGraphDef in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. N)rget_meta_graph_defrb)rQr#r\s rS_show_ops_in_metagraphres"%778?A.^,rUct||}tdt|jD]}td|zy)aPrints the keys for each SignatureDef in the SignatureDef map. Prints the list of SignatureDef keys from the SignatureDef map specified by the given tag-set and SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect. tag_set: Group of tag(s) of the MetaGraphDef to get SignatureDef map from, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. zQThe given SavedModel MetaGraphDef contains SignatureDefs with the following keys:zSignatureDef key: "%s"N)get_signature_def_maprNrOkeys)rQr#signature_def_mapr<s rS_show_signature_def_map_keysrj#sL,OWE !"3"8"8":;: $'8 89:rUc ||jvr8td|ddj|jj|j|jS)aGets TensorInfo for all inputs of the SignatureDef. Returns a dictionary that maps each input key to its TensorInfo for the given signature_def_key in the meta_graph_def Args: meta_graph_def: MetaGraphDef protocol buffer with the SignatureDef map to look up SignatureDef key. signature_def_key: A SignatureDef key string. Returns: A dictionary that maps input tensor keys to TensorInfos. Raises: ValueError if `signature_def_key` is not found in the MetaGraphDef. zCould not find signature "z". Please choose from: rL)r$ ValueErrorrPrhr&r\r<s rS+_get_inputs_tensor_info_from_meta_graph_defrn6sh$n:::  $%6$77N 99^11668 9 : < ==  % %&7 8 ? ??rUc4|j|jS)aGets TensorInfos for all outputs of the SignatureDef. Returns a dictionary that maps each output key to its TensorInfo for the given signature_def_key in the meta_graph_def. Args: meta_graph_def: MetaGraphDef protocol buffer with the SignatureDefmap to look up signature_def_key. signature_def_key: A SignatureDef key string. Returns: A dictionary that maps output tensor keys to TensorInfos. )r$outputsrms rS,_get_outputs_tensor_info_from_meta_graph_defrqOs  % %&7 8 @ @@rUc t||}t||}d|z fd}|dt|jD]\}}|d|zt ||dz!|dt|jD]\}} |d|zt | |dz!|d|j |j zy ) aRPrints input and output TensorInfos. Prints the details of input and output TensorInfos for the SignatureDef mapped by the given signature_def_key. Args: meta_graph_def: MetaGraphDef to inspect. signature_def_key: A SignatureDef key string. indent: How far (in increments of 2 spaces) to indent each line of output.  c"t|zyNrNs indent_strs rSin_printz*_show_inputs_outputs_mgd..in_prints *q.rUzBThe given SavedModel SignatureDef contains the following input(s):z inputs['%s'] tensor_info:zCThe given SavedModel SignatureDef contains the following output(s):z outputs['%s'] tensor_info:zMethod name is: %sN)rnrqrOitems_print_tensor_infor$ method_name) r\r<indentinputs_tensor_infooutputs_tensor_inforz input_key input_tensor output_key output_tensorrys @rS_show_inputs_outputs_mgdrasC'E')f}* OP!'(:(@(@(B!C/i ,y 89|VAX./  #)*=*C*C*E#F0j- - :;}fQh/0   ' '(9 : F F GHrUcJtj||}t|||y)aPrints input and output TensorInfos. Prints the details of input and output TensorInfos for the SignatureDef mapped by the given signature_def_key. Args: saved_model_dir: Directory containing the SavedModel to inspect. tag_set: Group of tag(s) of the MetaGraphDef, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. signature_def_key: A SignatureDef key string. indent: How far (in increments of 2 spaces) to indent each line of output. N)rrdr)rQr#r<rr\s rS_show_inputs_outputsrs(%77w.>+z)_show_defined_functions..s AFFrUkeyz Function Name: '%s'c|jSrurrs rSrz)_show_defined_functions..s !&&rUr|)NNz Option #%dz Callable with:rzNamed Argument)HasFieldrNops_libGraph as_defaultrr LoadOptions Exceptionstrlistr_AugmentedGraphView list_childrenrO isinstancedefunConcreteFunctionappendr Functionextend._list_all_concrete_functions_for_serialization enumeratestructured_input_signature _arg_keywords _print_args)rQ meta_graphshas_object_graph_defr\trackable_objecteerrorchildrenrchildconcrete_functionsindexconcrete_functionargskwargss rS_show_defined_functionsrs#HnN334FGGH  R(   # # %O **MOO /0}%&((H"2 3(8kdE%//0& E<00 1  > > @B % ,- 28HI$-.@!$D 8  ldF  5 5(CC f  * *!..  &' $%D# F,Q7 88!OO  3q6)=ee -eWA 67  s/"G%,G=G%G"G%% H.!HHc  d|z d}d fd }t|dD]\}}|dk(r |d||fzt|tr |d|z5t|tjr-t |dzdz|j dt|z|t|tjrat|tsQ|d t|jz|d d |D]}t d ||zd t dt|tro|d t|jz|dd |jD]'\}}t dt|d||d )t dv|d t|jz|dt|zy)zFormats and prints the argument of the concrete functions defined in the model. Args: arguments: Arguments to format print. argument_type: Type of arguments. indent: How far (in increments of 2 spaces) to indent each line of output. rscJdt|tz}|t|z|zS)N')rr)value is_quotess rS_maybe_add_quotesz&_print_args.._maybe_add_quotess'z%--I s5z !I --rUc&t|z|y)Nrrv)rxrrys rSrzz_print_args..in_prints *q.c"rUr|rz%s #%dz %sz: z DType: %sz Value: [r'rz%srLz]z Value: {rz': z}z Value: %sN) )rrrr TensorSpecrNrreprrIterabledicttype__name__r}) arguments argument_typerrrzrelementrrrys @rSrrsf}*.#")Q/-neW {x=%001'3v G[33 4 VaZ4 gllDM"J JK Wo66 7$'}tG}5556|$9% d&u--489 Gn GT "}tG}5556|$!--/M,3 c#h(9%(@AtLM Gn}tG}5556}s7|+,--rUc d|zfd}|dtjjDcic]\}}|| c}}|jz|jj rd}nO|jj Dcgc]}t|j}}dj|}d|zdz}|d|z|d |jzy cc}}wcc}w) zPrints details of the given tensor_info. Args: tensor_info: TensorInfo object to be printed. indent: How far (in increments of 2 spaces) to indent each line output rsc"t|zyrurvrws rSrzz$_print_tensor_info..in_printr{rUz dtype: unknown_rankrL(rz shape: z name: N) rDataTyper}dtype tensor_shaperdimrsizerPr) tensor_inforrzrrshaperdimsrys @rSr~r~sf}* = ) 2 2 8 8 : <e 3J <."sn&B&B&G&G!HrUrzF MetaGraphDef with tag-set: '%s' contains the following SignatureDefs:rL,z signature_def['z']:r|rN) rread_saved_modelrOrr_r`rNrPr$rhrrbr)rQ saved_modelr\r#rir<s rS _show_allrs"22?C+ H /n**//G  248IIg4F GHhhwG&44#$5$:$:$<=L #4 4v =>~/@KL~. //;+B+BCrUc.tj||S)a\DEPRECATED: Use saved_model_utils.get_meta_graph_def instead. Gets MetaGraphDef from SavedModel. Returns the MetaGraphDef for the given tag-set and SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect or execute. tag_set: Group of tag(s) of the MetaGraphDef to load, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. Raises: RuntimeError: An error when the given tag-set does not exist in the SavedModel. Returns: A MetaGraphDef corresponding to the tag-set. )rrd)rQr#s rSrdrd1s&  - -ow GGrUcFtj||}|jS)aGets SignatureDef map from a MetaGraphDef in a SavedModel. Returns the SignatureDef map for the given tag-set in the SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect or execute. tag_set: Group of tag(s) of the MetaGraphDef with the SignatureDef map, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. Returns: A SignatureDef map that maps from string keys to SignatureDefs. )rrdr$)rQr#r s rSrgrgGs"!33OWM*  ! !!rUcft|jdDcgc]}|s| c}}|Scc}w)Nr)rWsplit)r0opset_of_denylisted_opss rS_get_op_denylist_setrZs1K,=,=c,BIbbrIJ Js..cttj|j}||z}|r$t d|j j z|yt d|j j z|y)zScans meta_graph_def and reports if there are ops on denylist. Print ops if they are on denylist, or print success if no denylisted ops found. Args: meta_graph_def: MetaGraphDef protocol buffer. op_denylist: set of ops to scan for. z@MetaGraph with tag set %s contains the following denylisted ops:zFMetaGraph with tag set %s does not contain the default denylisted ops:N)rWrXrYrZrNr_r`)r\r0ops_in_metagraphdenylisted_opss rSscan_meta_graph_defr`sx**>+C+CDF!11. J$$)) *+9; P  & & + + ,-8:rUc tj||} t| |} |jD];} | | vst d| dddj | jzdzd|j D cic]\} }| | j|}} }t| |}t|j}|Dcgc]}||j}}d}|rItjdtjtjjd }tj |t#j$| 5}|r.t'd |j)t+j,t/j0||j3d || rt5j6|}|j)|| }t9|D]\}}||}t'd|d||st:j<j?|st;j@|t:j<j ||dz}|s-t:j<jC|rtEd|ztGjH||t'd|d| dddycc}} wcc}w#1swYyxYw)aRuns SavedModel and fetch all outputs. Runs the input dictionary through the MetaGraphDef within a SavedModel specified by the given tag_set and SignatureDef. Also save the outputs to file if outdir is not None. Args: saved_model_dir: Directory containing the SavedModel to execute. tag_set: Group of tag(s) of the MetaGraphDef with the SignatureDef map, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. signature_def_key: A SignatureDef key string. input_tensor_key_feed_dict: A dictionary maps input keys to numpy ndarrays. outdir: A directory to save the outputs to. If the directory doesn't exist, it will be created. overwrite_flag: A boolean flag to allow overwrite output file if file with the same name exists. worker: If provided, the session will be run on the worker. Valid worker specification is a bns or gRPC path. init_tpu: If true, the TPU system will be initialized after the session is created. use_tfrt: If true, TFRT session will be used. tf_debug: A boolean flag to use TensorFlow Debugger (TFDBG) to observe the intermediate Tensor values and runtime GraphDefs while running the SavedModel. Raises: ValueError: When any of the input tensor keys is not valid. RuntimeError: An error when output file already exists and overwrite is not enabled. "z/" is not a valid input key. Please choose from z", "z, or use --show option.NzUsing TFRT session.T)r/) experimental)graphconfigzInitializing TPU System ...r) feed_dictzResult for output key z: z.npyzXOutput file %s already exists. Add "--overwrite" to overwrite the existing output files.zOutput z is saved to )%rrdrnrhrlrPr}rrqrOlogginginfor ConfigProto Experimentalr SessionrrrNrFrinitialize_systemrrrr LocalCLIDebugWrapperSessionrospathisdirmakedirsexists RuntimeErrornpr)rQr#r<input_tensor_key_feed_dictr*overwrite_flagr-r.r/r,r\rinput_key_namertensorinputs_feed_dictroutput_tensor_keys_sorted tensor_keyoutput_tensor_names_sortedrsessrpioutputoutput_tensor_keyoutput_full_paths rSrun_saved_model_with_feed_dictr xsT%778?A. C')3779Pn//  3-?-D-D-F!GG#M O PPP499; #v""F* E')%%8%=%=%?@2  *%**   &  LL&'  # #++88$8GIFvW]]_VD!? )* hhs$$&' KKgmmC(/:  : :4 @dhh1=MhNGw'? 63A6 /@& IJ ww}}V$ ++f 77<<0AF0JK"''..1A"B,.>?@ @  &) ,=,<> ?%?!?!?' !?!?s J= KB*KB/KKci}|jd}tt|D]}tjd|}|r5|j d|j df||j d<Ptjd|}|r&|j ddf||j d<t d|z|S) aiParses input arg into dictionary that maps input to file/variable tuple. Parses input string in the format of, for example, "input1=filename1[variable_name1],input2=filename2" into a dictionary looks like {'input_key1': (filename1, variable_name1), 'input_key2': (file2, None)} , which maps input keys to a tuple of file name and variable name(None if empty). Args: inputs_str: A string that specified where to load inputs. Inputs are separated by semicolons. * For each input key: '=' or '=[]' * The optional 'variable_name' key will be set to None if not specified. Returns: A dictionary that maps input keys to a tuple of file name and variable name. Raises: RuntimeError: An error when the given input string is in a bad format. ;z!([^=]+)=([^\[\]]+)\[([^\[\]]+)\]$r9r|z([^=]+)=([^\[\]]+)$Nzu--inputs "%s" format is incorrect. Please follow"=", or"=[]")rfilterboolrematchgroupr) inputs_str input_dict inputs_raw input_rawrs rSpreprocess_inputs_arg_stringrs2*$*$ +Ei HH99 EE #(;;q>5;;q>#AjQ hh-y9e %*[[^T%9 5;;q>" 8:C DE EE" rUc6i}tt|jdD]S}d|vrtd|z|jdd\}}|r t j |||<Ft|||<U|S#t $r}td|d|d}~wwxYw)aParses input arg into dictionary that maps input key to python expression. Parses input string in the format of 'input_key=' into a dictionary that maps each input_key to its python expression. Args: input_exprs_str: A string that specifies python expression for input keys. Each input is separated by semicolon. For each input key: 'input_key=' safe: Whether to evaluate the python expression as literals or allow arbitrary calls (e.g. numpy usage). Returns: A dictionary that maps input keys to their values. Raises: RuntimeError: An error when the given input string is in a bad format. r=zV--input_exprs "%s" format is incorrect. Please follow"="r|z Expression "z " is not a valid python literal.N)rrrrast literal_evalreval)input_exprs_strsaferrrexprexcs rS!preprocess_input_exprs_arg_stringr#s&*$ 5 5c :; )i /! =?NO PPooc1-OIt L # 0 0 6 9 #4jj )  L4& @ ACHK LLsA:: BBBc t|}|jD]K\}}t|tst d|dt ||Dcgc] }t |c}||<M|Scc}w)aParses input into dict that maps input keys to lists of tf.Example. Parses input string in the format of 'input_key1=[{feature_name: feature_list}];input_key2=[{feature_name:feature_list}];' into a dictionary that maps each input_key to its list of serialized tf.Example. Args: input_examples_str: A string that specifies a list of dictionaries of feature_names and their feature_lists for each input. Each input is separated by semicolon. For each input key: 'input=[{feature_name1: feature_list1, feature_name2:feature_list2}]' items in feature_list can be the type of float, int, long or str. Returns: A dictionary that maps input keys to lists of serialized tf.Example. Raises: ValueError: An error when the given tf.Example is not a list. z6tf.Example input must be a list of dictionaries, but "" is )r#r}rrrlr_create_example_string)input_examples_strrr example_listexamples rS$preprocess_input_examples_arg_stringr*>s(11CD*!+!1!1!3i lD )  l+ - ..8D,3w'Jy  sA,c tj}|jD]\}}t|tst d|d|dt |t|dtr=|jj|jjj|t|dtrZ|jj|jjj|Dcgc]}|jdc}t|dt r>|jj|jjj|Bt|dt"r>|jj|j$jj|t dt |dd|dd|j'Scc}w) z7Create a serialized tf.example from feature dictionary.z"feature value must be a list, but z: "r%rutf8zType z for value z' is not supported for tf.train.Feature.)rExampler}rrrlrfloatfeaturesfeature float_listrrr bytes_listencodebytesint int64_listSerializeToString) example_dictr) feature_name feature_listfs rSr&r&^s    !'$0$6$6$84 lL lD ) $lD4FH II,q/5) |,77==DD  LOS ) |,77==DD%1 2188F  24 LOU + |,77==DD  LOS ) |,77==DD    Q ,q/ 3 44#4(  " " $$ 3s6G* cFi}t|}t|}t|}|jD]\}\}} t j t j|dd} | r[t| tjr"tjd|d| d| ||<s| | vr | | ||<td|d| d t| tjjjr4| j } t#| d k7rtd |z| | d ||<| ||<|jD]&\}} ||vrtjd |z| ||<(|jD]&\}} ||vrtjd|z| ||<(|S)a Parses input arg strings and create inputs feed_dict. Parses '--inputs' string for inputs to be loaded from file, and parses '--input_exprs' string for inputs to be evaluated from python expression. '--input_examples' string for inputs to be created from tf.example feature dictionary list. Args: inputs_str: A string that specified where to load inputs. Each input is separated by semicolon. * For each input key: '=' or '=[]' * The optional 'variable_name' key will be set to None if not specified. * File specified by 'filename' will be loaded using numpy.load. Inputs can be loaded from only .npy, .npz or pickle files. * The "[variable_name]" key is optional depending on the input file type as descripted in more details below. When loading from a npy file, which always contains a numpy ndarray, the content will be directly assigned to the specified input tensor. If a variable_name is specified, it will be ignored and a warning will be issued. When loading from a npz zip file, user can specify which variable within the zip file to load for the input tensor inside the square brackets. If nothing is specified, this function will check that only one file is included in the zip and load it for the specified input tensor. When loading from a pickle file, if no variable_name is specified in the square brackets, whatever that is inside the pickle file will be passed to the specified input tensor, else SavedModel CLI will assume a dictionary is stored in the pickle file and the value corresponding to the variable_name will be used. input_exprs_str: A string that specifies python expressions for inputs. * In the format of: '='. * numpy module is available as np. input_examples_str: A string that specifies tf.Example with dictionary. * In the format of: '=<[{feature:value list}]>' Returns: A dictionary that maps input tensor keys to numpy ndarrays. Raises: RuntimeError: An error when a key is specified, but the input file contains multiple numpy ndarrays, none of which matches the given key. RuntimeError: An error when no key is specified, but the input file contains more than one numpy ndarrays. rb)modeT) allow_picklez Input file z& contains a single ndarray. Name key "z " ignored.z& does not contain variable with name "z".r|zYInput file %s contains more than one ndarrays. Please specify the name of ndarray to use.rzrinput_key %s has been specified with both --inputs and --input_exprs options. Value in --input_exprs will be used.z\input_key %s has been specified in multiple options. Value in --input_examples will be used.)rr#r*r}rrrFileIOrndarrayrwarnrlibnpyioNpzFilefileslen)rrr'tensor_key_feed_dictr&r(r)input_tensor_keyfilename variable_namedatavariable_name_listpy_expr_evaluatedr)s rS!load_inputs_from_input_arg_stringrOxs` ' 3&1/B+78JK.5;\\^611= 777>>(6T JD D"** %  ( )26-. D 37 3F / 0() ) D"&&,,.. /!ZZ ! "a ',.678 8266H6K1L-.15-.;6@.9->->-@?))// ll ;=M NO.?)* ?$2#7#7#95// ll +-= >?.5)* 5 rUc2tjrttjytj5t jr t dttjyt jr(ttjtjtj)ttjtjyttjtjtjy)z#Function triggered by show command.Nz7--list_ops must be paired with a tag-set or with --all.) _SMCLI_ALLrr _SMCLI_DIR_SMCLI_TAG_SET_SMCLI_LIST_OPSrNrTre_SMCLI_SIGNATURE_DEFrjrrUrSrErEs j#    GHZ%%&   z//1E1EF  # # +$Z%5%5~7K7KL   n224H4N4N PrUc tjs+tjstjs t dt tjtjtj}t tjtjtj|tjtjtjtjtjtj y)zFunction triggered by run command. 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' '  . . 7 7!@!F!F,228>>8@FN)#)) * 0 0!/!5!5!;!;C!@ NN iNN*;*A*ANB  !@!F!F,228>>(..-3399#>066 8 N  7 > >s C EJMNNs AE F'FFctjxs.tjj t jd}t jsg}nCt jjdk(rd}nt jjd}tj|tjt jtjtj|tjy)z+Function triggered by freeze_model command.variables/variablesr"Nr)r=r\r<r>r;)_SMCLI_CHECKPOINT_PATHrrrrPrR_SMCLI_VARIABLES_TO_FEEDlowerrrrIrrdrS_SMCLI_SIGNATURE_DEF_KEY_SMCLI_OUTPUT_PREFIXr=r>s rSrIrISs""? j&&(= > " ' '%%++-6066<r;r@rArBrC)r~rrrrPrRrrrraot_compile_cpu_meta_graph_defrrdrSrr_SMCLI_TARGET_TRIPLE_SMCLI_TARGET_CPU_SMCLI_CPP_CLASS_SMCLI_MULTITHREADINGrs rSrJrJhs""? j&&(= > " ' '%%++-6066<!>O33"?"5++1F+GrUcdjgd}|jd|tj}|j t y)zAdd parser for `freeze_model`.r)Usage example:z4To freeze a SavedModel in preparation for tfcompile:z$saved_model_cli freeze_model \ --dir /tmp/saved_model \ --tag_set serve \z+ --output_prefix /tmp/saved_model_xla_aotrIrrN)rPrrrrrIr compile_msgparser_compiles rSadd_freeze_model_subparserrsN  +((33)5.<0rUcdjddddddddd d d d jtdd ddddddddg}|jd|tj }|j ty)z!Add parser for `aot_compile_cpu`.rrz4To compile a SavedModel signature via (CPU) XLA AOT:z"$saved_model_cli aot_compile_cpu \rrz( --output_dir /tmp/saved_model_xla_aotr'zFNote: Additional XLA compilation options are available by setting the zEXLA_FLAGS environment variable. 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