


'''simple docstring'''





import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List

import torch
from tqdm import tqdm

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, parse_numeric_n_bool_cl_kwargs, use_task_specific_params


__lowerCamelCase       				=	getLogger(__name__)


__lowerCamelCase       				=	"cuda" if torch.cuda.is_available() else "cpu"


def 					a__    (				UpperCamelCase_	:			Tuple,      UpperCamelCase_	:			str,      UpperCamelCase_	:			int,      UpperCamelCase_	:			Optional[Any] = 8,      UpperCamelCase_	:			str = DEFAULT_DEVICE,      UpperCamelCase_	:			Any=False,      UpperCamelCase_	:			List[str]="summarization",      UpperCamelCase_	:			List[Any]=None,      **UpperCamelCase_	:			List[str],      ):
   UpperCAmelCase__  :Tuple            =			Path(snake_case_	).open('''w''',      encoding='''utf-8'''	)
   UpperCAmelCase__  :List[str]            =			str(snake_case_	)
   UpperCAmelCase__  :Tuple            =			AutoModelForSeqaSeqLM.from_pretrained(snake_case_	).to(snake_case_	)
   if fpaa:
      UpperCAmelCase__  :Union[str, Any]            =			model.half()

   UpperCAmelCase__  :List[str]            =			AutoTokenizer.from_pretrained(snake_case_	)
   logger.info(F'''Inferred tokenizer type: {tokenizer.__class__}'''	)  # if this is wrong, check config.model_type.

   UpperCAmelCase__  :int            =			time.time()
   # update config with task specific params
   use_task_specific_params(snake_case_,      snake_case_	)
   if prefix is None:
      UpperCAmelCase__  :Optional[Any]            =			prefix or getattr(model.config,      '''prefix''',      ''''''	) or ''''''
   for examples_chunk in tqdm(list(chunks(snake_case_,      snake_case_	)	)	):
      UpperCAmelCase__  :List[Any]            =			[prefix + text for text in examples_chunk]
      UpperCAmelCase__  :Dict            =			tokenizer(snake_case_,      return_tensors='''pt''',      truncation=snake_case_,      padding='''longest'''	).to(snake_case_	)
      UpperCAmelCase__  :Dict            =			model.generate(
          input_ids=batch.input_ids,      attention_mask=batch.attention_mask,      **snake_case_,      )
      UpperCAmelCase__  :int            =			tokenizer.batch_decode(snake_case_,      skip_special_tokens=snake_case_,      clean_up_tokenization_spaces=snake_case_	)
      for hypothesis in dec:
         fout.write(hypothesis + '''\n'''	)
         fout.flush()
   fout.close()
   UpperCAmelCase__  :str            =			int(time.time() - start_time	)  # seconds
   UpperCAmelCase__  :Any            =			len(snake_case_	)
   return {"n_obs": n_obs, "runtime": runtime, "seconds_per_sample": round(runtime / n_obs,      4	)}


def 					a__    (				):
   return datetime.datetime.now().strftime('''%Y-%m-%d %H:%M:%S'''	)


def 					a__    (				UpperCamelCase_	:			str=True	):
   UpperCAmelCase__  :Optional[Any]            =			argparse.ArgumentParser()
   parser.add_argument('''model_name''',      type=snake_case_,      help='''like facebook/bart-large-cnn,t5-base, etc.'''	)
   parser.add_argument('''input_path''',      type=snake_case_,      help='''like cnn_dm/test.source'''	)
   parser.add_argument('''save_path''',      type=snake_case_,      help='''where to save summaries'''	)
   parser.add_argument('''--reference_path''',      type=snake_case_,      required=snake_case_,      help='''like cnn_dm/test.target'''	)
   parser.add_argument('''--score_path''',      type=snake_case_,      required=snake_case_,      default='''metrics.json''',      help='''where to save metrics'''	)
   parser.add_argument('''--device''',      type=snake_case_,      required=snake_case_,      default=snake_case_,      help='''cuda, cuda:1, cpu etc.'''	)
   parser.add_argument(
       '''--prefix''',      type=snake_case_,      required=snake_case_,      default=snake_case_,      help='''will be added to the begininng of src examples'''	)
   parser.add_argument('''--task''',      type=snake_case_,      default='''summarization''',      help='''used for task_specific_params + metrics'''	)
   parser.add_argument('''--bs''',      type=snake_case_,      default=8,      required=snake_case_,      help='''batch size'''	)
   parser.add_argument(
       '''--n_obs''',      type=snake_case_,      default=-1,      required=snake_case_,      help='''How many observations. Defaults to all.'''	)
   parser.add_argument('''--fp16''',      action='''store_true'''	)
   parser.add_argument('''--dump-args''',      action='''store_true''',      help='''print the custom hparams with the results'''	)
   parser.add_argument(
       '''--info''',      nargs='''?''',      type=snake_case_,      const=datetime_now(),      help=(
           '''use in conjunction w/ --dump-args to print with the results whatever other info you\'d like, e.g.'''
           ''' lang=en-ru. If no value is passed, the current datetime string will be used.'''
       ),      )
   # Unspecified args like --num_beams=2 --decoder_start_token_id=4 are passed to model.generate
   UpperCAmelCase__  :Tuple            =			parser.parse_known_args()
   UpperCAmelCase__  :List[str]            =			parse_numeric_n_bool_cl_kwargs(snake_case_	)
   if parsed_args and verbose:
      print(F'''parsed the following generate kwargs: {parsed_args}'''	)
   with open(args.input_path	) as f:
      UpperCAmelCase__  :Optional[int]            =			[''' ''' + x.rstrip() if '''t5''' in args.model_name else x.rstrip() for x in f.readlines()]
   if args.n_obs > 0:
      UpperCAmelCase__  :Tuple            =			examples[: args.n_obs]
   Path(args.save_path	).parent.mkdir(exist_ok=snake_case_	)
   if args.reference_path is None and Path(args.score_path	).exists():
      warnings.warn(F'''score_path {args.score_path} will be overwritten unless you type ctrl-c.'''	)
   UpperCAmelCase__  :List[Any]            =			generate_summaries_or_translations(
       snake_case_,      args.save_path,      args.model_name,      batch_size=args.bs,      device=args.device,      fpaa=args.fpaa,      task=args.task,      prefix=args.prefix,      **snake_case_,      )

   if args.reference_path is None:
      return {}

   # Compute scores
   UpperCAmelCase__  :List[Any]            =			calculate_bleu if '''translation''' in args.task else calculate_rouge
   UpperCAmelCase__  :Optional[int]            =			[x.rstrip() for x in open(args.save_path	).readlines()]
   UpperCAmelCase__  :Any            =			[x.rstrip() for x in open(args.reference_path	).readlines()][: len(snake_case_	)]
   UpperCAmelCase__  :dict            =			score_fn(snake_case_,      snake_case_	)
   scores.update(snake_case_	)

   if args.dump_args:
      scores.update(snake_case_	)
   if args.info:
      UpperCAmelCase__  :int            =			args.info

   if verbose:
      print(snake_case_	)

   if args.score_path is not None:
      json.dump(snake_case_,      open(args.score_path,      '''w'''	)	)

   return scores


if __name__ == "__main__":
    # Usage for MT:
    # python run_eval.py MODEL_NAME $DATA_DIR/test.source $save_dir/test_translations.txt --reference_path $DATA_DIR/test.target --score_path $save_dir/test_bleu.json  --task translation $@
    run_generate(verbose=True)






'''simple docstring'''





__lowerCamelCase       				=	[
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''bh-e12''', '''cd-e2''', '''ce-e4''',
     '''de-e1''', '''df-e8''', '''dg-e5''', '''dh-e10''', '''ef-e3''', '''eg-e2''', '''fg-e6''', '''gh-e6''', '''hi-e3'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''cd-e2''', '''de-e1''', '''df-e8''',
     '''ef-e3''', '''eg-e2''', '''fg-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''de-e1''', '''df-e8''', '''dg-e5''', '''ef-e3''', '''eg-e2''',
     '''eh-e12''', '''fg-e6''', '''fh-e10''', '''gh-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''bh-e12''', '''cd-e2''', '''df-e8''', '''dh-e10'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''cd-e2''', '''ce-e4''', '''de-e1''', '''df-e8''',
     '''dg-e5''', '''ef-e3''', '''eg-e2''', '''fg-e6''']
]


def 					a__    (				UpperCamelCase_	:			List[str]	):
   UpperCAmelCase__  :str            =			set()
   for row in edge_array:
      for item in row:
         distinct_edge.add(item[0]	)
   return list(UpperCamelCase_	)


def 					a__    (				UpperCamelCase_	:			Tuple,      UpperCamelCase_	:			List[Any]	):
   UpperCAmelCase__  :int            =			['''0'''] * len(UpperCamelCase_	)
   for i, row in enumerate(UpperCamelCase_	):
      for item in row:
         if distinct_edge in item[0]:
            UpperCAmelCase__  :List[Any]            =			'''1'''
            break
   return "".join(UpperCamelCase_	)


def 					a__    (				UpperCamelCase_	:			Optional[int]	):
   UpperCAmelCase__  :Any            =			get_distinct_edge(UpperCamelCase_	)
   UpperCAmelCase__  :Dict            =			{}

   for item in distinct_edge:
      UpperCAmelCase__  :List[str]            =			get_bitcode(UpperCamelCase_,      UpperCamelCase_	)
      # print('bit',bit)
      # bt=''.join(bit)
      UpperCAmelCase__  :int            =			bit.count('''1'''	)
      UpperCAmelCase__  :Tuple            =			[s, bit]
   # Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
   UpperCAmelCase__  :str            =			[
       [k, v[0], v[1]]
       for k, v in sorted(frequency_table.items(),      key=lambda UpperCamelCase_	: v[1][0],      reverse=UpperCamelCase_	)
   ]
   return sorted_frequency_table


def 					a__    (				UpperCamelCase_	:			Optional[int]	):
   UpperCAmelCase__  :int            =			{}
   for _, item in enumerate(UpperCamelCase_	):
      nodes.setdefault(item[2],      []	).append(item[0]	)
   return nodes


def 					a__    (				UpperCamelCase_	:			Any	):
   UpperCAmelCase__  :Any            =			{}
   for key, value in nodes.items():
      UpperCAmelCase__  :Optional[int]            =			value
   return cluster


def 					a__    (				UpperCamelCase_	:			Tuple	):
   return [i * 100 / len(UpperCamelCase_	) for i in cluster]


def 					a__    (				):
   print('''\nNodes\n'''	)
   for key, value in nodes.items():
      print(UpperCamelCase_,      UpperCamelCase_	)
   print('''\nSupport\n'''	)
   print(UpperCamelCase_	)
   print('''\n Cluster \n'''	)
   for key, value in sorted(cluster.items(),      reverse=UpperCamelCase_	):
      print(UpperCamelCase_,      UpperCamelCase_	)
   print('''\n Graph\n'''	)
   for key, value in graph.items():
      print(UpperCamelCase_,      UpperCamelCase_	)
   print('''\n Edge List of Frequent subgraphs \n'''	)
   for edge_list in freq_subgraph_edge_list:
      print(UpperCamelCase_	)


def 					a__    (				UpperCamelCase_	:			Optional[int],      UpperCamelCase_	:			Any,      UpperCamelCase_	:			int,      UpperCamelCase_	:			Dict	):
   for i in cluster[ca]:
      UpperCAmelCase__  :int            =			0
      UpperCAmelCase__  :int            =			ca + 1
      while ca < max(cluster.keys()	):
         for j in cluster[ca]:
            if int(UpperCamelCase_,      2	) & int(UpperCamelCase_,      2	) == int(UpperCamelCase_,      2	):
               if tuple(nodes[i]	) in graph:
                  graph[tuple(nodes[i]	)].append(nodes[j]	)
               else:
                  UpperCAmelCase__  :int            =			[nodes[j]]
               count += 1
         if count == 0:
            UpperCAmelCase__  :List[Any]            =			ca + 1
         else:
            break


def 					a__    (				UpperCamelCase_	:			Optional[int],      UpperCamelCase_	:			List[str]	):
   UpperCAmelCase__  :List[Any]            =			cluster[max(cluster.keys()	)]
   UpperCAmelCase__  :Union[str, Any]            =			'''Header'''
   UpperCAmelCase__  :Optional[int]            =			{}
   for i in x:
      if (["Header"],) in graph:
         graph[(["Header"],)].append(x[i]	)
      else:
         UpperCAmelCase__  :Tuple            =			[x[i]]
   for i in x:
      UpperCAmelCase__  :Dict            =			[['''Header''']]
   UpperCAmelCase__  :Any            =			1
   while i < max(UpperCamelCase_	) - 1:
      create_edge(UpperCamelCase_,      UpperCamelCase_,      UpperCamelCase_,      UpperCamelCase_	)
      UpperCAmelCase__  :Union[str, Any]            =			i + 1
   return graph


def 					a__    (				UpperCamelCase_	:			Optional[Any],      UpperCamelCase_	:			int,      UpperCamelCase_	:			Any,      UpperCamelCase_	:			Dict=None	):
   UpperCAmelCase__  :Tuple            =			(path or []) + [start]
   if start == end:
      paths.append(UpperCamelCase_	)
   for node in graph[start]:
      if tuple(UpperCamelCase_	) not in path:
         my_dfs(UpperCamelCase_,      tuple(UpperCamelCase_	),      UpperCamelCase_,      UpperCamelCase_	)


def 					a__    (				UpperCamelCase_	:			Dict,      UpperCamelCase_	:			int,      UpperCamelCase_	:			List[Any]	):
   UpperCAmelCase__  :List[str]            =			int(s / 100 * (len(UpperCamelCase_	) - 1)	)
   for i in cluster[k]:
      my_dfs(UpperCamelCase_,      tuple(cluster[k][i]	),      (['''Header'''],)	)


def 					a__    (				UpperCamelCase_	:			List[Any]	):
   UpperCAmelCase__  :int            =			[]
   for edges in paths:
      UpperCAmelCase__  :List[Any]            =			[]
      for j in range(len(UpperCamelCase_	) - 1	):
         UpperCAmelCase__  :Any            =			list(edges[j]	)
         for e in temp:
            UpperCAmelCase__  :str            =			(e[0], e[1])
            el.append(UpperCamelCase_	)
      freq_sub_el.append(UpperCamelCase_	)
   return freq_sub_el


def 					a__    (				UpperCamelCase_	:			Dict	):
   for i in range(len(UpperCamelCase_	)	):
      for j in range(len(edge_array[i]	)	):
         UpperCAmelCase__  :Dict            =			edge_array[i][j].split('''-'''	)
         UpperCAmelCase__  :Optional[Any]            =			t


if __name__ == "__main__":
    preprocess(edge_array)
    __lowerCamelCase       				=	get_frequency_table(edge_array)
    __lowerCamelCase       				=	get_nodes(frequency_table)
    __lowerCamelCase       				=	get_cluster(nodes)
    __lowerCamelCase       				=	get_support(cluster)
    __lowerCamelCase       				=	construct_graph(cluster, nodes)
    find_freq_subgraph_given_support(60, cluster, graph)
    __lowerCamelCase       				=	[]
    __lowerCamelCase       				=	freq_subgraphs_edge_list(paths)
    print_all()



