ijS5 dZddlZddlZddlZddlZddlmZddlZddl m Z ejjejjejjejjejjejjeZejjejZdZdZdZdZd Zd Zd Zd Zd Z ddZ ddZ ddZy)zJClasses and functions that help to inspect Python source w.r.t. TF graphs.N)app) profilingz.py)z.pycz.pyocztjjtjj|SN)ospathnormpathabspath) file_paths }/var/www/html/emotional.easysim.app/public_html/venv/lib/python3.12/site-packages/tensorflow/python/debug/lib/source_utils.py_norm_abs_pathr 's$   "''//)4 55crtjj|\}}|jtvSr)rrsplitextlowerUNCOMPILED_SOURCE_SUFFIXESr _ extensions r %is_extension_uncompiled_python_sourcer+s-!!),,!Y  8 88rcrtjj|\}}|jtvSr)rrrrCOMPILED_SOURCE_SUFFIXESrs r #is_extension_compiled_python_sourcer0s-!!),,!Y  6 66rc*|d|jdS)N:)rfind) watch_keys r !_convert_watch_key_to_tensor_namer5s (IOOC( ))rcFt|s t|syt|}|jtxs|jt xrR|j d xr>tjjdtjj|vS)aGuess whether a Python source file is a part of the tensorflow library. Special cases: 1) Returns False for unit-test files in the library (*_test.py), 2) Returns False for files under python/debug/examples. Args: py_file_path: full path of the Python source file in question. Returns: (`bool`) Whether the file is inferred to be a part of the tensorflow library. Fz_test.pyz tensorflow/python/debug/examples) rrr startswith_TENSORFLOW_BASEDIR _ABSL_BASEDIRendswithrrr ) py_file_paths r guess_is_tensorflow_py_libraryr%9s 0 = -l ;  -,  " "#6 7 2  " "= 1 +##J/ / + 77  > ? 77  L ) *,rc tjj|rFt|d5}|j j d}dddj d}nt|}|td|zttjtjt|dz}||fS#1swYwxYw)aLoad the content of a Python source code file. This function covers the following case: 1. source_file_path points to an existing Python (.py) file on the file system. 2. source_file_path is a path within a .par file (i.e., a zip-compressed, self-contained Python executable). Args: source_file_path: Path to the Python source file to read. Returns: A length-2 tuple: - Lines of the source file, as a `list` of `str`s. - The width of the string needed to show the line number in the file. This is calculated based on the number of lines in the source file. Raises: IOError: if loading is unsuccessful. rbutf-8N z?Source path neither exists nor can be loaded as a .par file: %s)rrisfileopenreaddecodesplit_try_load_par_sourceIOErrorintnpceillog10len)source_file_pathf source_text source_linesline_num_widths r load_sourcer<Rs*WW^^$%  %-FFHOOG,k-$$T*L((89L  K   rwwrxxL(9:;KF#{(C ??; '+19:Fbgg&&t,F F * $vvajjl:#3#3K#@AB +b'')**73K$$T* + ++++ G + +++s6,E:?&E)%7E:0E. E:)E:.E7 3E::Fc |j}|s tdt|}i}|jD]}t |j |j D]\} } } } || |ks|| |k\rt| |k7r&|r>|j|j } tttt| } n |j g} | |vr|| j| n| || <|s|S)aAnnotate a Python source file with a list of ops created at each line. (The annotation doesn't change the source file itself.) Args: dump: (`DebugDumpDir`) A `DebugDumpDir` object of which the Python graph has been loaded. source_file_path: (`str`) Path to the source file being annotated. do_dumped_tensors: (`str`) Whether dumped Tensors, instead of ops are to be used to annotate the source file. file_stack_top: (`bool`) Whether only the top stack trace in the specified source file is to be annotated. min_line: (`None` or `int`) The 1-based line to start annotate the source file from (inclusive). max_line: (`None` or `int`) The 1-based line number to end the annotation at (exclusive). Returns: A `dict` mapping 1-based line number to a list of op name(s) created at that line, or tensor names if `do_dumped_tensors` is True. Raises: ValueError: If the dump object does not have a Python graph set. zUCannot perform source annotation due to a lack of set Python graph in the dump object) python_graph ValueErrorr get_operationsreversednode_tracebackrHdebug_watch_keyslistsetmaprextend)dumpr7do_dumped_tensorsfile_stack_topmin_linemax_linepy_graphline_to_op_namesopr line_numberr watch_keysitems_to_appends r annotate_sourceras>  (  7 88$$45  # # %b(01D1DRWW1M(N$ ;1  ;#9  ;(#:  "&6 6 **2773  5zB CE77) ( (%,,_=(7%  -2 rc X|j}|s tdtjt}tjt}i}i|rt j |nd}|rt j |nd}t } |jD]l} |r|j| js"|j| jD],\} } } } t| } | | vs2|r|j| rtjj| s| j| \|| j| j| |vr|| | kDr | || <n| || <| j D]"}|j}|| j|$|j#| j}|D]K}|j%d\}}}|d|}|vs$t'|j)|t+|||<M/oi}|D]}t-fd||D||<g}|D]g} |j/| t1| t'|j3| it'|j3| i|j3| d|| fit5|dS)a@Generate a list of source files with information regarding ops and tensors. Args: dump: (`DebugDumpDir`) A `DebugDumpDir` object of which the Python graph has been loaded. path_regex_allowlist: A regular-expression filter for source file path. node_name_regex_allowlist: A regular-expression filter for node names. Returns: A list of tuples regarding the Python source files involved in constructing the ops and tensors contained in `dump`. Each tuple is: (source_file_path, is_tf_library, num_nodes, num_tensors, num_dumps, first_line) is_tf_library: (`bool`) A guess of whether the file belongs to the TensorFlow Python library. num_nodes: How many nodes were created by lines of this source file. These include nodes with dumps and those without. num_tensors: How many Tensors were created by lines of this source file. These include Tensors with dumps and those without. num_dumps: How many debug Tensor dumps were from nodes (and Tensors) that were created by this source file. first_line: The first line number (1-based) that created any nodes or Tensors in this source file. The list is sorted by ascending order of source_file_path. Raises: ValueError: If the dump object does not have a Python graph set. zPCannot generate source list due to a lack of set Python graph in the dump objectNrc3BK|]}j|dyw)rN)get).0 tensor_nametensor_name_to_num_dumpss r z1list_source_files_against_dump../s&"7  !$$[!4"7src |dS)Nr)xs r z0list_source_files_against_dump..=s adr)key)rLrM collections defaultdictrSrecompilerNmatchrHrPr rrr+addoutputsrQr/r6 get_tensorsr2sumappendr%rdsorted)rVpath_regex_allowlistnode_name_regex_allowlistr[path_to_node_namespath_to_tensor_namespath_to_first_line path_regexnode_name_regexto_skip_file_pathsr]r r^r output_tensorrfr_r node_name output_slotdebug_oppath_to_num_dumpsroutputrgs @r list_source_files_against_dumprsD  (  7 88#..s3$005+?bjj%&D  # jj*+(,u  # # %Gb44RWW=(,(;(;BGG(DG$ ;1 +i ) ) Z--i8ggnnY'y)#''0 ( ( i (; 6*5 Y '(39%::9-#(( Y'++K89((1j!G)+4??3+?( ;!*K8 6 625y#k*:HE3G "; / G)G G>"7d!"7/5"77d7 &%(i MM&y1  " "9b 12 $ $Y 34i+9% '(( N ++rcNt|}|rtj|nd}|rtj|nd}i}|D]} | jst| j|k7r)|| j|ks|| j|k\rL|r&|j | j jst|r|j | js| j|vr#tj| || j<|| jj| |S)aAnnotate a Python source file with profiling information at each line. (The annotation doesn't change the source file itself.) Args: profile_data: (`list` of `ProfileDatum`) A list of `ProfileDatum`. source_file_path: (`str`) Path to the source file being annotated. node_name_filter: Regular expression to filter by node name. op_type_filter: Regular expression to filter by op type. min_line: (`None` or `int`) The 1-based line to start annotate the source file from (inclusive). max_line: (`None` or `int`) The 1-based line number to end the annotation at (exclusive). Returns: A `dict` mapping 1-based line number to a the namedtuple `profiling.LineOrFuncProfileSummary`. N) r rprqr r^rrnode_exec_statsrop_typerAggregateProfilers) profile_datar7node_name_filterop_type_filterrYrZr op_type_regexline_to_profile_summary profile_datums r annotate_source_against_profiler@s!2$$454DBJJ/0$/0>"**^,D-#Lm  " "m--.2BB!:!:X!E!:!:h!F  ! !-"?"?"I"I J]001F1FG  (??  $ $] 3m778m778<<]K-L0 ! r)FFNN)NN)NNNN)__doc__rnrrpr@abslrnumpyr3tensorflow.python.debug.librrdirnamer r __file__r!r"rrr rrrr%r<r0rarrrjrr rsQ 1ggooGGOOBGGOOBGGOO 23%5678 - $+69 7 *,2"&J+F',#(!! @H9==Ab,N6:37-1-1 7!r