


import unittest
from typing import Dict, List, Optional, Union

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
	import torch

if is_vision_available():
	from PIL import Image

	from transformers import BridgeTowerImageProcessor




class       lowercase_					(unittest.TestCase   ):





				def __init__(				self       ,  lowercase_       ,  lowercase_ = True       ,  lowercase_ = None       ,  lowercase_ = 32       ,  lowercase_ = True       ,  lowercase_ = 1 / 255       ,  lowercase_ = True       ,  lowercase_ = True       ,  lowercase_ = [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73]       ,  lowercase_ = [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11]       ,  lowercase_ = True       ,  lowercase_=7       ,  lowercase_=30       ,  lowercase_=400       ,  lowercase_=3       ,  )  -> List[str]:
											a__      =parent
											a__      =do_resize
											a__      =size if size is not None else {'shortest_edge': 288}
											a__      =size_divisor
											a__      =do_rescale
											a__      =rescale_factor
											a__      =do_normalize
											a__      =do_center_crop
											a__      =image_mean
											a__      =image_std
											a__      =do_pad
											a__      =batch_size
											a__      =num_channels
											a__      =min_resolution
											a__      =max_resolution





				def 						__UpperCamelCase    (				self)  -> int:
											return {
											    "image_mean": self.image_mean,
											    "image_std": self.image_std,
											    "do_normalize": self.do_normalize,
											    "do_resize": self.do_resize,
											    "size": self.size,
											    "size_divisor": self.size_divisor,
											}





				def 						__UpperCamelCase    (				self       ,  lowercase_       ,  lowercase_=False)  -> Optional[Any]:





											if not batched:
																		a__      =self.size['shortest_edge']
																		a__      =image_inputs[0]
																		if isinstance(__snake_case       ,  Image.Image):
																									a__    ,     a__      =image.size
																		else:
																									a__    ,     a__      =image.shape[1], image.shape[2]
																		a__      =size / min(__snake_case       ,  __snake_case)
																		if h < w:
																									a__    ,     a__      =size, scale * w
																		else:
																									a__    ,     a__      =scale * h, size

																		a__      =int((1333 / 800) * size)
																		if max(__snake_case       ,  __snake_case) > max_size:
																									a__      =max_size / max(__snake_case       ,  __snake_case)
																									a__      =newh * scale
																									a__      =neww * scale

																		a__    ,     a__      =int(newh + 0.5), int(neww + 0.5)
																		a__    ,     a__      =(
																		    newh // self.size_divisor * self.size_divisor,
																		    neww // self.size_divisor * self.size_divisor,
																		)

											else:
																		a__      =[]
																		for image in image_inputs:
																									a__    ,     a__      =self.get_expected_values([image])
																									expected_values.append((expected_height, expected_width))
																		a__      =max(__snake_case       ,  key=lambda lowercase_: item[0])[0]
																		a__      =max(__snake_case       ,  key=lambda lowercase_: item[1])[1]

											return expected_height, expected_width







@require_torch
@require_vision
class       lowercase_					(_SCREAMING_SNAKE_CASE      ,					unittest.TestCase   ):
				snake_case	    =BridgeTowerImageProcessor if is_vision_available() else None





				def 						__UpperCamelCase    (				self)  -> int:
											a__      =BridgeTowerImageProcessingTester(self)





				@property
				def 						__UpperCamelCase    (				self)  -> Tuple:
											return self.image_processor_tester.prepare_image_processor_dict()





				def 						__UpperCamelCase    (				self)  -> Union[str, Any]:
											a__      =self.image_processing_class(**self.image_processor_dict)
											self.assertTrue(hasattr(__snake_case       ,  'image_mean'))
											self.assertTrue(hasattr(__snake_case       ,  'image_std'))
											self.assertTrue(hasattr(__snake_case       ,  'do_normalize'))
											self.assertTrue(hasattr(__snake_case       ,  'do_resize'))
											self.assertTrue(hasattr(__snake_case       ,  'size'))
											self.assertTrue(hasattr(__snake_case       ,  'size_divisor'))





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											pass





				def 						__UpperCamelCase    (				self)  -> Tuple:
											a__      =self.image_processing_class(**self.image_processor_dict)
											# create random PIL images
											a__      =prepare_image_inputs(self.image_processor_tester       ,  equal_resolution=__snake_case)
											for image in image_inputs:
																		self.assertIsInstance(__snake_case       ,  Image.Image)

											# Test not batched input
											a__      =image_processing(image_inputs[0]       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (1, self.image_processor_tester.num_channels, expected_height, expected_width)       ,  )

											# Test batched
											a__      =image_processing(__snake_case       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case       ,  batched=__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (
											        self.image_processor_tester.batch_size,
											        self.image_processor_tester.num_channels,
											        expected_height,
											        expected_width,
											    )       ,  )





				def 						__UpperCamelCase    (				self)  -> Optional[Any]:
											a__      =self.image_processing_class(**self.image_processor_dict)
											# create random numpy tensors
											a__      =prepare_image_inputs(self.image_processor_tester       ,  equal_resolution=__snake_case       ,  numpify=__snake_case)
											for image in image_inputs:
																		self.assertIsInstance(__snake_case       ,  np.ndarray)

											# Test not batched input
											a__      =image_processing(image_inputs[0]       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (1, self.image_processor_tester.num_channels, expected_height, expected_width)       ,  )

											# Test batched
											a__      =image_processing(__snake_case       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case       ,  batched=__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (
											        self.image_processor_tester.batch_size,
											        self.image_processor_tester.num_channels,
											        expected_height,
											        expected_width,
											    )       ,  )





				def 						__UpperCamelCase    (				self)  -> Optional[Any]:
											a__      =self.image_processing_class(**self.image_processor_dict)
											# create random PyTorch tensors
											a__      =prepare_image_inputs(self.image_processor_tester       ,  equal_resolution=__snake_case       ,  torchify=__snake_case)
											for image in image_inputs:
																		self.assertIsInstance(__snake_case       ,  torch.Tensor)

											# Test not batched input
											a__      =image_processing(image_inputs[0]       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (1, self.image_processor_tester.num_channels, expected_height, expected_width)       ,  )

											# Test batched
											a__      =image_processing(__snake_case       ,  return_tensors='pt').pixel_values

											a__    ,     a__      =self.image_processor_tester.get_expected_values(__snake_case       ,  batched=__snake_case)
											self.assertEqual(
											    encoded_images.shape       ,  (
											        self.image_processor_tester.batch_size,
											        self.image_processor_tester.num_channels,
											        expected_height,
											        expected_width,
											    )       ,  )








import logging
import os
import threading
import time


try:
      import warnings
except ImportError:
      a__      :     Optional[Any]         =		None

try:
      import msvcrt
except ImportError:
      a__      :     List[str]         =		None

try:
      import fcntl
except ImportError:
      a__      :     Optional[int]         =		None


# Backward compatibility
# ------------------------------------------------
try:
      TimeoutError
except NameError:
      a__      :     List[str]         =		OSError


# Data
# ------------------------------------------------
a__      :     Union[str, Any]         =		[
    'Timeout',
    'BaseFileLock',
    'WindowsFileLock',
    'UnixFileLock',
    'SoftFileLock',
    'FileLock',
]

a__      :     str         =		'3.0.12'


a__      :     Optional[int]         =		None

def      UpperCAmelCase_    (    )	->				Tuple:
     '''simple docstring'''


     global _logger
     A_          =       _logger or logging.getLogger(__name__				)
     return _logger





class UpperCAmelCase_				( _SCREAMING_SNAKE_CASE ):


  def __init__(							self ,__snake_case ):



       """simple docstring"""





       A_          =       lock_file
       return None




  def __str__(							self ):



       """simple docstring"""





       A_          =       f'The file lock \'{self.lock_file}\' could not be acquired.'
       return temp





class UpperCAmelCase_				:


  def __init__(							self ,__snake_case ):



       """simple docstring"""





       A_          =       lock
       return None


  def __enter__(							self ):



       """simple docstring"""





       return self.lock




  def __exit__(							self ,__snake_case ,__snake_case ,__snake_case ):



       """simple docstring"""





       self.lock.release()
       return None





class UpperCAmelCase_				:


  def __init__(							self ,__snake_case ,__snake_case=-1 ,__snake_case=None ):



       """simple docstring"""





       A_          =       max_filename_length if max_filename_length is not None else 2_5_5
       # Hash the filename if it's too long
       A_          =       self.hash_filename_if_too_long(__snake_case ,__snake_case )
       # The path to the lock file.
       A_          =       lock_file

       # The file descriptor for the *_lock_file* as it is returned by the
       # os.open() function.
       # This file lock is only NOT None, if the object currently holds the
       # lock.
       A_          =       None

       # The default timeout value.
       A_          =       timeout

       # We use this lock primarily for the lock counter.
       A_          =       threading.Lock()

       # The lock counter is used for implementing the nested locking
       # mechanism. Whenever the lock is acquired, the counter is increased and
       # the lock is only released, when this value is 0 again.
       A_          =       0
       return None


  @property
  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       return self._lock_file


  @property
  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       return self._timeout


  @timeout.setter
  def 						__UpperCAmelCase     (							self ,__snake_case ):



       """simple docstring"""





       A_          =       float(__snake_case )
       return None


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       raise NotImplementedError()


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       raise NotImplementedError()


  @property
  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       return self._lock_file_fd is not None


  def 						__UpperCAmelCase     (							self ,__snake_case=None ,__snake_case=0.05 ):



       """simple docstring"""





       if timeout is None:
            A_          =       self.timeout

       # Increment the number right at the beginning.
       # We can still undo it, if something fails.
       with self._thread_lock:
            self._lock_counter += 1

       A_          =       id(self )
       A_          =       self._lock_file
       A_          =       time.time()
       try:
            while True:
                 with self._thread_lock:
                      if not self.is_locked:
                           logger().debug(f'Attempting to acquire lock {lock_id} on {lock_filename}' )
                           self._acquire()

                 if self.is_locked:
                      logger().debug(f'Lock {lock_id} acquired on {lock_filename}' )
                      break
                 elif timeout >= 0 and time.time() - start_time > timeout:
                      logger().debug(f'Timeout on acquiring lock {lock_id} on {lock_filename}' )
                      raise Timeout(self._lock_file )
                 else:
                      logger().debug(
                          f'Lock {lock_id} not acquired on {lock_filename}, waiting {poll_intervall} seconds ...' )
                      time.sleep(__snake_case )
       except:  # noqa
            # Something did go wrong, so decrement the counter.
            with self._thread_lock:
                 A_          =       max(0 ,self._lock_counter - 1 )

            raise
       return _Acquire_ReturnProxy(lock=self )


  def 						__UpperCAmelCase     (							self ,__snake_case=False ):



       """simple docstring"""





       with self._thread_lock:
            if self.is_locked:
                 self._lock_counter -= 1

                 if self._lock_counter == 0 or force:
                      A_          =       id(self )
                      A_          =       self._lock_file

                      logger().debug(f'Attempting to release lock {lock_id} on {lock_filename}' )
                      self._release()
                      A_          =       0
                      logger().debug(f'Lock {lock_id} released on {lock_filename}' )

       return None


  def __enter__(							self ):



       """simple docstring"""





       self.acquire()
       return self


  def __exit__(							self ,__snake_case ,__snake_case ,__snake_case ):



       """simple docstring"""





       self.release()
       return None


  def __del__(							self ):



       """simple docstring"""





       self.release(force=__snake_case )
       return None




  def 						__UpperCAmelCase     (							self ,__snake_case ,__snake_case ):



       """simple docstring"""





       A_          =       os.path.basename(__snake_case )
       if len(__snake_case ) > max_length and max_length > 0:
            A_          =       os.path.dirname(__snake_case )
            A_          =       str(hash(__snake_case ) )
            A_          =       filename[: max_length - len(__snake_case ) - 8] + '''...''' + hashed_filename + '''.lock'''
            return os.path.join(__snake_case ,__snake_case )
       else:
            return path





class UpperCAmelCase_				( _SCREAMING_SNAKE_CASE ):


  def __init__(							self ,__snake_case ,__snake_case=-1 ,__snake_case=None ):



       """simple docstring"""





       from .file_utils import relative_to_absolute_path

       super().__init__(__snake_case ,timeout=__snake_case ,max_filename_length=__snake_case )
       A_          =       '''\\\\?\\''' + relative_to_absolute_path(self.lock_file )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       os.O_RDWR | os.O_CREAT | os.O_TRUNC

       try:
            A_          =       os.open(self._lock_file ,__snake_case )
       except OSError:
            pass
       else:
            try:
                 msvcrt.locking(__snake_case ,msvcrt.LK_NBLCK ,1 )
            except OSError:
                 os.close(__snake_case )
            else:
                 A_          =       fd
       return None




  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self._lock_file_fd
       A_          =       None
       msvcrt.locking(__snake_case ,msvcrt.LK_UNLCK ,1 )
       os.close(__snake_case )

       try:
            os.remove(self._lock_file )
       # Probably another instance of the application
       # that acquired the file lock.
       except OSError:
            pass
       return None





class UpperCAmelCase_				( _SCREAMING_SNAKE_CASE ):


  def __init__(							self ,__snake_case ,__snake_case=-1 ,__snake_case=None ):



       """simple docstring"""





       A_          =       os.statvfs(os.path.dirname(__snake_case ) ).f_namemax
       super().__init__(__snake_case ,timeout=__snake_case ,max_filename_length=__snake_case )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       os.O_RDWR | os.O_CREAT | os.O_TRUNC
       A_          =       os.open(self._lock_file ,__snake_case )

       try:
            fcntl.flock(__snake_case ,fcntl.LOCK_EX | fcntl.LOCK_NB )
       except OSError:
            os.close(__snake_case )
       else:
            A_          =       fd
       return None




  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self._lock_file_fd
       A_          =       None
       fcntl.flock(__snake_case ,fcntl.LOCK_UN )
       os.close(__snake_case )
       return None





class UpperCAmelCase_				( _SCREAMING_SNAKE_CASE ):


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       os.O_WRONLY | os.O_CREAT | os.O_EXCL | os.O_TRUNC
       try:
            A_          =       os.open(self._lock_file ,__snake_case )
       except OSError:
            pass
       else:
            A_          =       fd
       return None




  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       os.close(self._lock_file_fd )
       A_          =       None

       try:
            os.remove(self._lock_file )
       # The file is already deleted and that's what we want.
       except OSError:
            pass
       return None




a__      :     Union[str, Any]         =		None

if msvcrt:
      a__      :     Dict         =		WindowsFileLock
elif fcntl:
      a__      :     Dict         =		UnixFileLock
else:
      a__      :     Optional[int]         =		SoftFileLock

      if warnings is not None:
            warnings.warn('only soft file lock is available')



