


'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
		import torch

if is_soundfile_availble():
		import soundfile as sf

if is_vision_available():
		from PIL import Image


def 			a      (			__a=""   )  ->	str:



					'''simple docstring'''






					UpperCamelCase__   :Dict												= tempfile.mkdtemp()
					return os.path.join(__a ,					str(uuid.uuida()   ) + suffix   )
@require_soundfile
@require_torch
class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= torch.rand(12    ,   dtype=torch.floataa							) - 0.5
							UpperCamelCase__   :str												= AgentAudio(UpperCamelCase_							)
							UpperCamelCase__   :Tuple												= str(agent_type.to_string()							)

							# Ensure that the tensor and the agent_type's tensor are the same
							self.assertTrue(torch.allclose(UpperCamelCase_    ,   agent_type.to_raw()    ,   atol=1e-4							)							)

							del agent_type

							# Ensure the path remains even after the object deletion
							self.assertTrue(os.path.exists(UpperCamelCase_							)							)

							# Ensure that the file contains the same value as the original tensor
							UpperCamelCase__					,				UpperCamelCase__   :Union[str, Any]												= sf.read(UpperCamelCase_							)
							self.assertTrue(torch.allclose(UpperCamelCase_    ,   torch.tensor(UpperCamelCase_							)    ,   atol=1e-4							)							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[int]												= torch.rand(12    ,   dtype=torch.floataa							) - 0.5
							UpperCamelCase__   :Optional[Any]												= get_new_path(suffix='''.wav'''							)
							sf.write(UpperCamelCase_    ,   UpperCamelCase_    ,   16000							)

							UpperCamelCase__   :List[Any]												= AgentAudio(UpperCamelCase_							)

							self.assertTrue(torch.allclose(UpperCamelCase_    ,   agent_type.to_raw()    ,   atol=1e-4							)							)
							self.assertEqual(agent_type.to_string()    ,   UpperCamelCase_							)



@require_vision
@require_torch
class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[int]												= torch.randint(0    ,   256    ,   (64, 64, 3)							)
							UpperCamelCase__   :List[str]												= AgentImage(UpperCamelCase_							)
							UpperCamelCase__   :List[Any]												= str(agent_type.to_string()							)

							# Ensure that the tensor and the agent_type's tensor are the same
							self.assertTrue(torch.allclose(UpperCamelCase_    ,   agent_type._tensor    ,   atol=1e-4							)							)

							self.assertIsInstance(agent_type.to_raw()    ,   Image.Image							)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(UpperCamelCase_							)							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= Path(get_tests_dir('''fixtures/tests_samples/COCO'''							)							) / '''000000039769.png'''
							UpperCamelCase__   :str												= Image.open(UpperCamelCase_							)
							UpperCamelCase__   :int												= AgentImage(UpperCamelCase_							)

							self.assertTrue(path.samefile(agent_type.to_string()							)							)
							self.assertTrue(image == agent_type.to_raw()							)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(UpperCamelCase_							)							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[Any]												= Path(get_tests_dir('''fixtures/tests_samples/COCO'''							)							) / '''000000039769.png'''
							UpperCamelCase__   :List[Any]												= Image.open(UpperCamelCase_							)
							UpperCamelCase__   :Optional[Any]												= AgentImage(UpperCamelCase_							)

							self.assertFalse(path.samefile(agent_type.to_string()							)							)
							self.assertTrue(image == agent_type.to_raw()							)

							# Ensure the path remains even after the object deletion
							del agent_type
							self.assertTrue(os.path.exists(UpperCamelCase_							)							)



class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[str]												= '''Hey!'''
							UpperCamelCase__   :str												= AgentText(UpperCamelCase_							)

							self.assertEqual(UpperCamelCase_    ,   agent_type.to_string()							)
							self.assertEqual(UpperCamelCase_    ,   agent_type.to_raw()							)
							self.assertEqual(UpperCamelCase_    ,   UpperCamelCase_							)





import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[Any] ,     UpperCamelCase__				:      Optional[int] ,     UpperCamelCase__				:      str ,     UpperCamelCase__				:      Any=1024      )     ->       Dict:





				"""simple docstring"""


				__lowerCamelCase       ,						__lowerCamelCase		       =    [], []

				__lowerCamelCase		       =    list(zip(UpperCamelCase__ ,     UpperCamelCase__      )      )
				__lowerCamelCase       ,						__lowerCamelCase		       =    sorted_examples[0]

				def is_too_big(UpperCamelCase__				:      List[str]      ):
								return tok(UpperCamelCase__ ,     return_tensors='pt'      ).input_ids.shape[1] > max_tokens

				for src, tgt in tqdm(sorted_examples[1:]      ):
								__lowerCamelCase		       =    new_src + ' ' + src
								__lowerCamelCase		       =    new_tgt + ' ' + tgt
								if is_too_big(UpperCamelCase__      ) or is_too_big(UpperCamelCase__      ):  # cant fit, finalize example
												finished_src.append(UpperCamelCase__      )
												finished_tgt.append(UpperCamelCase__      )
												__lowerCamelCase       ,						__lowerCamelCase		       =    src, tgt
								else:  # can fit, keep adding
												__lowerCamelCase       ,						__lowerCamelCase		       =    cand_src, cand_tgt

    # cleanup
				if new_src:
								assert new_tgt
								finished_src.append(UpperCamelCase__      )
								finished_tgt.append(UpperCamelCase__      )
				return finished_src, finished_tgt







def 			lowerCamelCase_		(       UpperCamelCase__				:      str ,     UpperCamelCase__				:      Path ,     UpperCamelCase__				:      Optional[int] ,     UpperCamelCase__				:      str      )     ->       Optional[int]:





				"""simple docstring"""


				__lowerCamelCase		       =    Path(UpperCamelCase__      )
				save_path.mkdir(exist_ok=UpperCamelCase__      )
				for split in ["train"]:
								__lowerCamelCase       ,						__lowerCamelCase		       =    data_dir / F"""{split}.source""", data_dir / F"""{split}.target"""
								__lowerCamelCase		       =    [x.rstrip() for x in Path(UpperCamelCase__      ).open().readlines()]
								__lowerCamelCase		       =    [x.rstrip() for x in Path(UpperCamelCase__      ).open().readlines()]
								__lowerCamelCase       ,						__lowerCamelCase		       =    pack_examples(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								print(F"""packed {split} split from {len(UpperCamelCase__      )} examples -> {len(UpperCamelCase__      )}."""      )
								Path(save_path / F"""{split}.source"""      ).open('w'      ).write('\n'.join(UpperCamelCase__      )      )
								Path(save_path / F"""{split}.target"""      ).open('w'      ).write('\n'.join(UpperCamelCase__      )      )
				for split in ["val", "test"]:
								__lowerCamelCase       ,						__lowerCamelCase		       =    data_dir / F"""{split}.source""", data_dir / F"""{split}.target"""
								shutil.copyfile(UpperCamelCase__ ,     save_path / F"""{split}.source"""      )
								shutil.copyfile(UpperCamelCase__ ,     save_path / F"""{split}.target"""      )







def 			lowerCamelCase_		(       )     ->       List[str]:





				"""simple docstring"""


				__lowerCamelCase		       =    argparse.ArgumentParser()
				parser.add_argument('--tok_name' ,     type=UpperCamelCase__ ,     help='like facebook/bart-large-cnn,t5-base, etc.'      )
				parser.add_argument('--max_seq_len' ,     type=UpperCamelCase__ ,     default=128      )
				parser.add_argument('--data_dir' ,     type=UpperCamelCase__      )
				parser.add_argument('--save_path' ,     type=UpperCamelCase__      )
				__lowerCamelCase		       =    parser.parse_args()
				__lowerCamelCase		       =    AutoTokenizer.from_pretrained(args.tok_name      )
				return pack_data_dir(UpperCamelCase__ ,     Path(args.data_dir      ) ,     args.max_seq_len ,     args.save_path      )


if __name__ == "__main__":
					packer_cli()


