

"""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   __SCREAMING_SNAKE_CASE  (      A_="" ):
	lowerCAmelCase__	:						Dict  				=	tempfile.mkdtemp()
	return os.path.join(A_						,     str(uuid.uuida() ) + suffix )







@require_soundfile
@require_torch
class 				SCREAMING_SNAKE_CASE					(		unittest.TestCase       ):






					"""simple docstring"""



					def        __lowerCAmelCase (       self			:				Optional[int]		):
						lowerCAmelCase__	:						Dict  				=	torch.rand(1_2   ,dtype=torch.floataa		) - 0.5
						lowerCAmelCase__	:						Optional[Any]  				=	AgentAudio(lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	str(agent_type.to_string()		)

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

						del agent_type

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

						# Ensure that the file contains the same value as the original tensor
						lowerCAmelCase__				,lowerCAmelCase__	:						Tuple  				=	sf.read(lowercase_		)
						self.assertTrue(torch.allclose(lowercase_   ,torch.tensor(lowercase_		)   ,atol=1E-4		)		)







					def        __lowerCAmelCase (       self			:				List[str]		):
						lowerCAmelCase__	:						Optional[Any]  				=	torch.rand(1_2   ,dtype=torch.floataa		) - 0.5
						lowerCAmelCase__	:						Tuple  				=	get_new_path(suffix='''.wav'''		)
						sf.write(lowercase_   ,lowercase_   ,1_6_0_0_0		)

						lowerCAmelCase__	:						int  				=	AgentAudio(lowercase_		)

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







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






					"""simple docstring"""



					def        __lowerCAmelCase (       self			:				Optional[int]		):
						lowerCAmelCase__	:						int  				=	torch.randint(0   ,2_5_6   ,(6_4, 6_4, 3)		)
						lowerCAmelCase__	:						List[str]  				=	AgentImage(lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	str(agent_type.to_string()		)

						# Ensure that the tensor and the agent_type's tensor are the same
						self.assertTrue(torch.allclose(lowercase_   ,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(lowercase_		)		)







					def        __lowerCAmelCase (       self			:				Any		):
						lowerCAmelCase__	:						List[Any]  				=	Path(get_tests_dir('''fixtures/tests_samples/COCO'''		)		) / '''000000039769.png'''
						lowerCAmelCase__	:						Optional[int]  				=	Image.open(lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	AgentImage(lowercase_		)

						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(lowercase_		)		)







					def        __lowerCAmelCase (       self			:				Any		):
						lowerCAmelCase__	:						List[str]  				=	Path(get_tests_dir('''fixtures/tests_samples/COCO'''		)		) / '''000000039769.png'''
						lowerCAmelCase__	:						List[Any]  				=	Image.open(lowercase_		)
						lowerCAmelCase__	:						List[Any]  				=	AgentImage(lowercase_		)

						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(lowercase_		)		)







class 				SCREAMING_SNAKE_CASE					(		unittest.TestCase       ):






					"""simple docstring"""



					def        __lowerCAmelCase (       self			:				int		):
						lowerCAmelCase__	:						Union[str, Any]  				=	'''Hey!'''
						lowerCAmelCase__	:						List[Any]  				=	AgentText(lowercase_		)

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







"""simple docstring"""





import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__UpperCamelCase  :      Any							      =		logging.getLogger(__name__)

if __name__ == "__main__":
							__UpperCamelCase  :      Union[str, Any]							      =		argparse.ArgumentParser(
							    description='''Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'''
							)
							parser.add_argument(
							    '''--data_file''', type=str, default='''data/dump.bert-base-uncased.pickle''', help='''The binarized dataset.'''
							)
							parser.add_argument(
							    '''--token_counts_dump''', type=str, default='''data/token_counts.bert-base-uncased.pickle''', help='''The dump file.'''
							)
							parser.add_argument('''--vocab_size''', default=3_0_5_2_2, type=int)
							__UpperCamelCase  :      Any							      =		parser.parse_args()

							logger.info(F'''Loading data from {args.data_file}''')
							with open(args.data_file, '''rb''') as fp:
														__UpperCamelCase  :      List[Any]							      =		pickle.load(fp)

							logger.info('''Counting occurrences for MLM.''')
							__UpperCamelCase  :      Dict							      =		Counter()
							for tk_ids in data:
														counter.update(tk_ids)
							__UpperCamelCase  :      Optional[Any]							      =		[0] * args.vocab_size
							for k, v in counter.items():
														__UpperCamelCase  :      Dict							      =		v

							logger.info(F'''Dump to {args.token_counts_dump}''')
							with open(args.token_counts_dump, '''wb''') as handle:
														pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)




