






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


a__       =     getLogger(__name__)


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

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

							snake_case__	  =       AutoTokenizer.from_pretrained(a )
							logger.info(F'''Inferred tokenizer type: {tokenizer.__class__}''' )  # if this is wrong, check config.model_type.

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

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

def _UpperCAmelCase   (	a						:	List[str]=True ):
							snake_case__	  =       argparse.ArgumentParser()
							parser.add_argument("""model_name"""  ,					type=a  ,					help="""like facebook/bart-large-cnn,t5-base, etc.""" )
							parser.add_argument("""input_path"""  ,					type=a  ,					help="""like cnn_dm/test.source""" )
							parser.add_argument("""save_path"""  ,					type=a  ,					help="""where to save summaries""" )
							parser.add_argument("""--reference_path"""  ,					type=a  ,					required=a  ,					help="""like cnn_dm/test.target""" )
							parser.add_argument("""--score_path"""  ,					type=a  ,					required=a  ,					default="""metrics.json"""  ,					help="""where to save metrics""" )
							parser.add_argument("""--device"""  ,					type=a  ,					required=a  ,					default=a  ,					help="""cuda, cuda:1, cpu etc.""" )
							parser.add_argument(
							    """--prefix"""  ,					type=a  ,					required=a  ,					default=a  ,					help="""will be added to the begininng of src examples""" )
							parser.add_argument("""--task"""  ,					type=a  ,					default="""summarization"""  ,					help="""used for task_specific_params + metrics""" )
							parser.add_argument("""--bs"""  ,					type=a  ,					default=8  ,					required=a  ,					help="""batch size""" )
							parser.add_argument(
							    """--n_obs"""  ,					type=a  ,					default=-1  ,					required=a  ,					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=a  ,					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
							snake_case__  , snake_case__	  =       parser.parse_known_args()
							snake_case__	  =       parse_numeric_n_bool_cl_kwargs(a )
							if parsed_args and verbose:
														print(F'''parsed the following generate kwargs: {parsed_args}''' )
							snake_case__	  =       [""" """ + x.rstrip() if """t5""" in args.model_name else x.rstrip() for x in open(args.input_path ).readlines()]
							if args.n_obs > 0:
														snake_case__	  =       examples[: args.n_obs]
							Path(args.save_path ).parent.mkdir(exist_ok=a )

							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.''' )

							if args.device == "cpu" and args.fpaa:
														# this mix leads to RuntimeError: "threshold_cpu" not implemented for 'Half'
														raise ValueError("""Can't mix --fp16 and --device cpu""" )

							snake_case__	  =       generate_summaries_or_translations(
							    a  ,					args.save_path  ,					args.model_name  ,					batch_size=args.bs  ,					device=args.device  ,					fpaa=args.fpaa  ,					task=args.task  ,					prefix=args.prefix  ,					**a  ,					)

							if args.reference_path is None:
														return {}

							# Compute scores
							snake_case__	  =       calculate_bleu if """translation""" in args.task else calculate_rouge
							snake_case__	  =       [x.rstrip() for x in open(args.save_path ).readlines()]
							snake_case__	  =       [x.rstrip() for x in open(args.reference_path ).readlines()][: len(a )]
							snake_case__	  =       score_fn(a  ,					a )
							scores.update(a )

							if args.dump_args:
														scores.update(a )
							if args.info:
														snake_case__	  =       args.info

							if verbose:
														print(a )

							if args.score_path is not None:
														json.dump(a  ,					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)








from __future__ import annotations

import time

a__       =     list[tuple[int, int]]

a__       =     [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

a__       =     [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Dict			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    Node | None):






											'''simple docstring'''







											snake_case__	  =       pos_x
											snake_case__	  =       pos_y
											snake_case__	  =       (pos_y, pos_x)
											snake_case__	  =       goal_x
											snake_case__	  =       goal_y
											snake_case__	  =       parent


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Optional[int]			,		UpperCamelCase__    :    tuple[int, int]			,		UpperCamelCase__    :    tuple[int, int]):






											'''simple docstring'''







											snake_case__	  =       Node(start[1]			,		start[0]			,		goal[1]			,		goal[0]			,		UpperCamelCase__)
											snake_case__	  =       Node(goal[1]			,		goal[0]			,		goal[1]			,		goal[0]			,		UpperCamelCase__)

											snake_case__	  =       [self.start]
											snake_case__	  =       False



				def 					__magic_name__							(      self    :    List[Any]):






											'''simple docstring'''







											while self.node_queue:
																		snake_case__	  =       self.node_queue.pop(0)

																		if current_node.pos == self.target.pos:
																									snake_case__	  =       True
																									return self.retrace_path(UpperCamelCase__)

																		snake_case__	  =       self.get_successors(UpperCamelCase__)

																		for node in successors:
																									self.node_queue.append(UpperCamelCase__)

											if not self.reached:
																		return [self.start.pos]
											return None



				def 					__magic_name__							(      self    :    Any			,		UpperCamelCase__    :    Node):






											'''simple docstring'''







											snake_case__	  =       []
											for action in delta:
																		snake_case__	  =       parent.pos_x + action[1]
																		snake_case__	  =       parent.pos_y + action[0]
																		if not (0 <= pos_x <= len(grid[0]) - 1 and 0 <= pos_y <= len(UpperCamelCase__) - 1):
																									continue

																		if grid[pos_y][pos_x] != 0:
																									continue

																		successors.append(
																		    Node(UpperCamelCase__			,		UpperCamelCase__			,		self.target.pos_y			,		self.target.pos_x			,		UpperCamelCase__))
											return successors



				def 					__magic_name__							(      self    :    str			,		UpperCamelCase__    :    Node | None):






											'''simple docstring'''







											snake_case__	  =       node
											snake_case__	  =       []
											while current_node is not None:
																		path.append((current_node.pos_y, current_node.pos_x))
																		snake_case__	  =       current_node.parent
											path.reverse()
											return path


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    str			,		UpperCamelCase__    :    Optional[Any]			,		UpperCamelCase__    :    Any):






											'''simple docstring'''







											snake_case__	  =       BreadthFirstSearch(UpperCamelCase__			,		UpperCamelCase__)
											snake_case__	  =       BreadthFirstSearch(UpperCamelCase__			,		UpperCamelCase__)
											snake_case__	  =       False



				def 					__magic_name__							(      self    :    Any):






											'''simple docstring'''







											while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
																		snake_case__	  =       self.fwd_bfs.node_queue.pop(0)
																		snake_case__	  =       self.bwd_bfs.node_queue.pop(0)

																		if current_bwd_node.pos == current_fwd_node.pos:
																									snake_case__	  =       True
																									return self.retrace_bidirectional_path(
																									    UpperCamelCase__			,		UpperCamelCase__)

																		snake_case__	  =       current_bwd_node
																		snake_case__	  =       current_fwd_node

																		snake_case__	  =       {
																		    self.fwd_bfs: self.fwd_bfs.get_successors(UpperCamelCase__),
																		    self.bwd_bfs: self.bwd_bfs.get_successors(UpperCamelCase__),
																		}

																		for bfs in [self.fwd_bfs, self.bwd_bfs]:
																									for node in successors[bfs]:
																																bfs.node_queue.append(UpperCamelCase__)

											if not self.reached:
																		return [self.fwd_bfs.start.pos]
											return None



				def 					__magic_name__							(      self    :    Union[str, Any]			,		UpperCamelCase__    :    Node			,		UpperCamelCase__    :    Node):






											'''simple docstring'''







											snake_case__	  =       self.fwd_bfs.retrace_path(UpperCamelCase__)
											snake_case__	  =       self.bwd_bfs.retrace_path(UpperCamelCase__)
											bwd_path.pop()
											bwd_path.reverse()
											snake_case__	  =       fwd_path + bwd_path
											return path


if __name__ == "__main__":
	# all coordinates are given in format [y,x]
	import doctest

	doctest.testmod()
	a__       =     (0, 0)
	a__       =     (len(grid) - 1, len(grid[0]) - 1)
	for elem in grid:
		print(elem)

	a__       =     time.time()
	a__       =     BreadthFirstSearch(init, goal)
	a__       =     bfs.search()
	a__       =     time.time() - start_bfs_time

	print("""Unidirectional BFS computation time : """, bfs_time)

	a__       =     time.time()
	a__       =     BidirectionalBreadthFirstSearch(init, goal)
	a__       =     bd_bfs.search()
	a__       =     time.time() - start_bd_bfs_time

	print("""Bidirectional BFS computation time : """, bd_bfs_time)
