




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import CLIPImageProcessor, CLIPProcessor

@require_vision
class  _lowerCamelCase						(			unittest.TestCase   ):

						"""simple docstring"""

						def       snake_case	(     self					: Dict				):
										__UpperCamelCase  		=						tempfile.mkdtemp()

										# fmt: off
										__UpperCamelCase  		=						['''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
										# fmt: on
										__UpperCamelCase  		=						dict(zip(snake_case ,       range(len(snake_case				)				)				)				)
										__UpperCamelCase  		=						['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
										__UpperCamelCase  		=						{'''unk_token''': '''<unk>'''}

										__UpperCamelCase  		=						os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES['''vocab_file''']				)
										__UpperCamelCase  		=						os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES['''merges_file''']				)
										with open(self.vocab_file ,       '''w''' ,       encoding='''utf-8'''				) as fp:
														fp.write(json.dumps(snake_case				) + '''\n'''				)
										with open(self.merges_file ,       '''w''' ,       encoding='''utf-8'''				) as fp:
														fp.write('''\n'''.join(snake_case				)				)

										__UpperCamelCase  		=						{
										    '''do_resize''': True,
										    '''size''': 20,
										    '''do_center_crop''': True,
										    '''crop_size''': 18,
										    '''do_normalize''': True,
										    '''image_mean''': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
										    '''image_std''': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
										}
										__UpperCamelCase  		=						os.path.join(self.tmpdirname ,       snake_case				)
										with open(self.image_processor_file ,       '''w''' ,       encoding='''utf-8'''				) as fp:
														json.dump(snake_case ,       snake_case				)







						def       snake_case	(     self					: str ,       **snake_case					: Dict				):
										return CLIPTokenizer.from_pretrained(self.tmpdirname ,       **snake_case				)







						def       snake_case	(     self					: Union[str, Any] ,       **snake_case					: List[str]				):
										return CLIPTokenizerFast.from_pretrained(self.tmpdirname ,       **snake_case				)







						def       snake_case	(     self					: Tuple ,       **snake_case					: Optional[int]				):
										return CLIPImageProcessor.from_pretrained(self.tmpdirname ,       **snake_case				)







						def       snake_case	(     self					: int				):
										shutil.rmtree(self.tmpdirname				)







						def       snake_case	(     self					: Any				):
										__UpperCamelCase  		=						[np.random.randint(255 ,       size=(3, 30, 400) ,       dtype=np.uinta				)]

										__UpperCamelCase  		=						[Image.fromarray(np.moveaxis(snake_case ,       0 ,       -1				)				) for x in image_inputs]

										return image_inputs







						def       snake_case	(     self					: str				):
										__UpperCamelCase  		=						self.get_tokenizer()
										__UpperCamelCase  		=						self.get_rust_tokenizer()
										__UpperCamelCase  		=						self.get_image_processor()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)
										processor_slow.save_pretrained(self.tmpdirname				)
										__UpperCamelCase  		=						CLIPProcessor.from_pretrained(self.tmpdirname ,       use_fast=snake_case				)

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)
										processor_fast.save_pretrained(self.tmpdirname				)
										__UpperCamelCase  		=						CLIPProcessor.from_pretrained(self.tmpdirname				)

										self.assertEqual(processor_slow.tokenizer.get_vocab() ,       tokenizer_slow.get_vocab()				)
										self.assertEqual(processor_fast.tokenizer.get_vocab() ,       tokenizer_fast.get_vocab()				)
										self.assertEqual(tokenizer_slow.get_vocab() ,       tokenizer_fast.get_vocab()				)
										self.assertIsInstance(processor_slow.tokenizer ,       snake_case				)
										self.assertIsInstance(processor_fast.tokenizer ,       snake_case				)

										self.assertEqual(processor_slow.image_processor.to_json_string() ,       image_processor.to_json_string()				)
										self.assertEqual(processor_fast.image_processor.to_json_string() ,       image_processor.to_json_string()				)
										self.assertIsInstance(processor_slow.image_processor ,       snake_case				)
										self.assertIsInstance(processor_fast.image_processor ,       snake_case				)







						def       snake_case	(     self					: Any				):
										__UpperCamelCase  		=						CLIPProcessor(tokenizer=self.get_tokenizer() ,       image_processor=self.get_image_processor()				)
										processor.save_pretrained(self.tmpdirname				)

										__UpperCamelCase  		=						self.get_tokenizer(bos_token='''(BOS)''' ,       eos_token='''(EOS)'''				)
										__UpperCamelCase  		=						self.get_image_processor(do_normalize=snake_case ,       padding_value=1.0				)

										__UpperCamelCase  		=						CLIPProcessor.from_pretrained(
										    self.tmpdirname ,       bos_token='''(BOS)''' ,       eos_token='''(EOS)''' ,       do_normalize=snake_case ,       padding_value=1.0				)

										self.assertEqual(processor.tokenizer.get_vocab() ,       tokenizer_add_kwargs.get_vocab()				)
										self.assertIsInstance(processor.tokenizer ,       snake_case				)

										self.assertEqual(processor.image_processor.to_json_string() ,       image_processor_add_kwargs.to_json_string()				)
										self.assertIsInstance(processor.image_processor ,       snake_case				)







						def       snake_case	(     self					: List[str]				):
										__UpperCamelCase  		=						self.get_image_processor()
										__UpperCamelCase  		=						self.get_tokenizer()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)

										__UpperCamelCase  		=						self.prepare_image_inputs()

										__UpperCamelCase  		=						image_processor(snake_case ,       return_tensors='''np'''				)
										__UpperCamelCase  		=						processor(images=snake_case ,       return_tensors='''np'''				)

										for key in input_image_proc.keys():
														self.assertAlmostEqual(input_image_proc[key].sum() ,       input_processor[key].sum() ,       delta=1E-2				)







						def       snake_case	(     self					: str				):
										__UpperCamelCase  		=						self.get_image_processor()
										__UpperCamelCase  		=						self.get_tokenizer()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)

										__UpperCamelCase  		=						'''lower newer'''

										__UpperCamelCase  		=						processor(text=snake_case				)

										__UpperCamelCase  		=						tokenizer(snake_case				)

										for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key] ,       encoded_processor[key]				)







						def       snake_case	(     self					: str				):
										__UpperCamelCase  		=						self.get_image_processor()
										__UpperCamelCase  		=						self.get_tokenizer()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)

										__UpperCamelCase  		=						'''lower newer'''
										__UpperCamelCase  		=						self.prepare_image_inputs()

										__UpperCamelCase  		=						processor(text=snake_case ,       images=snake_case				)

										self.assertListEqual(list(inputs.keys()				) ,       ['''input_ids''', '''attention_mask''', '''pixel_values''']				)

										# test if it raises when no input is passed
										with pytest.raises(snake_case				):
														processor()







						def       snake_case	(     self					: Any				):
										__UpperCamelCase  		=						self.get_image_processor()
										__UpperCamelCase  		=						self.get_tokenizer()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)

										__UpperCamelCase  		=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										__UpperCamelCase  		=						processor.batch_decode(snake_case				)
										__UpperCamelCase  		=						tokenizer.batch_decode(snake_case				)

										self.assertListEqual(snake_case ,       snake_case				)







						def       snake_case	(     self					: Tuple				):
										__UpperCamelCase  		=						self.get_image_processor()
										__UpperCamelCase  		=						self.get_tokenizer()

										__UpperCamelCase  		=						CLIPProcessor(tokenizer=snake_case ,       image_processor=snake_case				)

										__UpperCamelCase  		=						'''lower newer'''
										__UpperCamelCase  		=						self.prepare_image_inputs()

										__UpperCamelCase  		=						processor(text=snake_case ,       images=snake_case				)

										self.assertListEqual(list(inputs.keys()				) ,       processor.model_input_names				)












import heapq
import sys

import numpy as np

a_   		=     tuple[int, int]

class  _lowerCamelCase						:

      """simple docstring"""

      def __init__(     self					: Dict				):
          __UpperCamelCase  		=						[]
          __UpperCamelCase  		=						set()







      def       snake_case	(     self					: Dict				):
          if not self.empty():
              return self.elements[0][0]
          else:
              return float('''inf'''				)







      def       snake_case	(     self					: Optional[Any]				):
          return len(self.elements				) == 0







      def       snake_case	(     self					: Optional[int] ,       snake_case					: Tuple ,       snake_case					: Any				):
          if item not in self.set:
              heapq.heappush(self.elements ,       (priority, item)				)
              self.set.add(snake_case				)
          else:
              # update
              # print("update", item)
              __UpperCamelCase  		=						[]
              ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						heapq.heappop(self.elements				)
              while x != item:
                  temp.append((pri, x)				)
                  ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						heapq.heappop(self.elements				)
              temp.append((priority, item)				)
              for pro, xxx in temp:
                  heapq.heappush(self.elements ,       (pro, xxx)				)







      def       snake_case	(     self					: Any ,       snake_case					: int				):
          if item in self.set:
              self.set.remove(snake_case				)
              __UpperCamelCase  		=						[]
              ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						heapq.heappop(self.elements				)
              while x != item:
                  temp.append((pro, x)				)
                  ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						heapq.heappop(self.elements				)
              for prito, yyy in temp:
                  heapq.heappush(self.elements ,       (prito, yyy)				)







      def       snake_case	(     self					: Tuple				):
          return self.elements[0][1]







      def       snake_case	(     self					: List[str]				):
          ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						heapq.heappop(self.elements				)
          self.set.remove(snake_case				)
          return (priority, item)







def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_      )       ->	Tuple:

    """simple docstring"""


    __UpperCamelCase  		=						np.array(lowercase_      )
    __UpperCamelCase  		=						np.array(lowercase_      )
    return np.linalg.norm(a - b      )




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_      )       ->	int:

    """simple docstring"""


    return consistent_heuristic(lowercase_					,     lowercase_      ) // t




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_      )       ->	Dict:

    """simple docstring"""


    return abs(p[0] - goal[0]      ) + abs(p[1] - goal[1]      )




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )       ->	str:

    """simple docstring"""


    __UpperCamelCase  		=						g_function[start] + Wa * heuristics[i](lowercase_					,     lowercase_      )
    return ans




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_      )       ->	Dict:

    """simple docstring"""


    __UpperCamelCase  		=						np.chararray((n, n)      )
    for i in range(lowercase_      ):
        for j in range(lowercase_      ):
            __UpperCamelCase  		=						'''*'''

    for i in range(lowercase_      ):
        for j in range(lowercase_      ):
            if (j, (n - 1) - i) in blocks:
                __UpperCamelCase  		=						'''#'''

    __UpperCamelCase  		=						'''-'''
    __UpperCamelCase  		=						back_pointer[goal]
    while x != start:
        ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						x
        # print(x)
        __UpperCamelCase  		=						'''-'''
        __UpperCamelCase  		=						back_pointer[x]
    __UpperCamelCase  		=						'''-'''

    for i in range(lowercase_      ):
        for j in range(lowercase_      ):
            if (i, j) == (0, n - 1):
                print(grid[i][j]					,     end=''' '''      )
                print('''<-- End position'''					,     end=''' '''      )
            else:
                print(grid[i][j]					,     end=''' '''      )
        print()
    print('''^'''      )
    print('''Start position'''      )
    print()
    print('''# is an obstacle'''      )
    print('''- is the path taken by algorithm'''      )
    print('''PATH TAKEN BY THE ALGORITHM IS:-'''      )
    __UpperCamelCase  		=						back_pointer[goal]
    while x != start:
        print(lowercase_					,     end=''' '''      )
        __UpperCamelCase  		=						back_pointer[x]
    print(lowercase_      )
    sys.exit()




def 					__SCREAMING_SNAKE_CASE   (  lowercase_      )       ->	List[Any]:

    """simple docstring"""


    if p[0] < 0 or p[0] > n - 1:
        return False
    if p[1] < 0 or p[1] > n - 1:
        return False
    return True




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     )       ->	Tuple:

    """simple docstring"""


    for itera in range(lowercase_      ):
        open_list[itera].remove_element(lowercase_      )
    # print("s", s)
    # print("j", j)
    ((__UpperCamelCase)		,      (__UpperCamelCase))  		=						s
    __UpperCamelCase  		=						(x - 1, y)
    __UpperCamelCase  		=						(x + 1, y)
    __UpperCamelCase  		=						(x, y + 1)
    __UpperCamelCase  		=						(x, y - 1)

    for neighbours in [left, right, up, down]:
        if neighbours not in blocks:
            if valid(lowercase_      ) and neighbours not in visited:
                # print("neighbour", neighbours)
                visited.add(lowercase_      )
                __UpperCamelCase  		=						-1
                __UpperCamelCase  		=						float('''inf'''      )

            if valid(lowercase_      ) and g_function[neighbours] > g_function[s] + 1:
                __UpperCamelCase  		=						g_function[s] + 1
                __UpperCamelCase  		=						s
                if neighbours not in close_list_anchor:
                    open_list[0].put(lowercase_					,     key(lowercase_					,     0					,     lowercase_					,     lowercase_      )      )
                    if neighbours not in close_list_inad:
                        for var in range(1					,     lowercase_      ):
                            if key(lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      ) <= Wa * key(
                                lowercase_					,     0					,     lowercase_					,     lowercase_      ):
                                open_list[j].put(
                                    lowercase_					,     key(lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )      )




def 					__SCREAMING_SNAKE_CASE   (  )       ->	str:

    """simple docstring"""


    __UpperCamelCase  		=						[]
    for x in range(1					,     5      ):
        for y in range(1					,     6      ):
            some_list.append((x, y)      )

    for x in range(15					,     20      ):
        some_list.append((x, 17)      )

    for x in range(10					,     19      ):
        for y in range(1					,     15      ):
            some_list.append((x, y)      )

    # L block
    for x in range(1					,     4      ):
        for y in range(12					,     19      ):
            some_list.append((x, y)      )
    for x in range(3					,     13      ):
        for y in range(16					,     19      ):
            some_list.append((x, y)      )
    return some_list


a_   		=     {0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

a_   		=     [
    (0, 1),
    (1, 1),
    (2, 1),
    (3, 1),
    (4, 1),
    (5, 1),
    (6, 1),
    (7, 1),
    (8, 1),
    (9, 1),
    (10, 1),
    (11, 1),
    (12, 1),
    (13, 1),
    (14, 1),
    (15, 1),
    (16, 1),
    (17, 1),
    (18, 1),
    (19, 1),
]
a_   		=     make_common_ground()


a_   		=     blocks_blk
# hyper parameters
a_   		=     1
a_   		=     1
a_   		=     20
a_   		=     3  # one consistent and two other inconsistent

# start and end destination
a_   		=     (0, 0)
a_   		=     (n - 1, n - 1)

a_   		=     1




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_      )       ->	str:

    """simple docstring"""


    __UpperCamelCase  		=						{start: 0, goal: float('''inf'''      )}
    __UpperCamelCase  		=						{start: -1, goal: -1}
    __UpperCamelCase  		=						[]
    __UpperCamelCase  		=						set()

    for i in range(lowercase_      ):
        open_list.append(PriorityQueue()      )
        open_list[i].put(lowercase_					,     key(lowercase_					,     lowercase_					,     lowercase_					,     lowercase_      )      )

    __UpperCamelCase  		=						[]
    __UpperCamelCase  		=						[]
    while open_list[0].minkey() < float('''inf'''      ):
        for i in range(1					,     lowercase_      ):
            # print(open_list[0].minkey(), open_list[i].minkey())
            if open_list[i].minkey() <= Wa * open_list[0].minkey():
                global t
                t += 1
                if g_function[goal] <= open_list[i].minkey():
                    if g_function[goal] < float('''inf'''      ):
                        do_something(lowercase_					,     lowercase_					,     lowercase_      )
                else:
                    __UpperCamelCase		,      __UpperCamelCase  		=						open_list[i].top_show()
                    visited.add(lowercase_      )
                    expand_state(
                        lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     )
                    close_list_inad.append(lowercase_      )
            else:
                if g_function[goal] <= open_list[0].minkey():
                    if g_function[goal] < float('''inf'''      ):
                        do_something(lowercase_					,     lowercase_					,     lowercase_      )
                else:
                    __UpperCamelCase  		=						open_list[0].top_show()
                    visited.add(lowercase_      )
                    expand_state(
                        lowercase_					,     0					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     )
                    close_list_anchor.append(lowercase_      )
    print('''No path found to goal'''      )
    print()
    for i in range(n - 1					,     -1					,     -1      ):
        for j in range(lowercase_      ):
            if (j, i) in blocks:
                print('''#'''					,     end=''' '''      )
            elif (j, i) in back_pointer:
                if (j, i) == (n - 1, n - 1):
                    print('''*'''					,     end=''' '''      )
                else:
                    print('''-'''					,     end=''' '''      )
            else:
                print('''*'''					,     end=''' '''      )
            if (j, i) == (n - 1, n - 1):
                print('''<-- End position'''					,     end=''' '''      )
        print()
    print('''^'''      )
    print('''Start position'''      )
    print()
    print('''# is an obstacle'''      )
    print('''- is the path taken by algorithm'''      )


if __name__ == "__main__":
 multi_a_star(start, goal, n_heuristic)






