






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 OwlViTImageProcessor, OwlViTProcessor



@require_vision
class 				SCREAMING_SNAKE_CASE__		(							unittest.TestCase		):





					"""simple docstring"""






					def 			_lowercase	(   self	:    Optional[Any]			):
						snake_case__					: List[str]  =    tempfile.mkdtemp()

						# fmt: off
						snake_case__					: Any  =    ["", "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
						snake_case__					: Optional[int]  =    dict(zip(a_				,						range(len(a_			)			)			)			)
						snake_case__					: Any  =    ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
						snake_case__					: List[Any]  =    {"unk_token": "<unk>"}

						snake_case__					: Union[str, Any]  =    os.path.join(self.tmpdirname				,						VOCAB_FILES_NAMES["vocab_file"]			)
						snake_case__					: str  =    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(a_			) + "\n"			)
						with open(self.merges_file				,						"w"				,						encoding="utf-8"			) as fp:
							fp.write("\n".join(a_			)			)

						snake_case__					: Any  =    {
						    "do_resize": True,
						    "size": 2_0,
						    "do_center_crop": True,
						    "crop_size": 1_8,
						    "do_normalize": True,
						    "image_mean": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
						    "image_std": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
						}
						snake_case__					: List[Any]  =    os.path.join(self.tmpdirname				,						a_			)
						with open(self.image_processor_file				,						"w"				,						encoding="utf-8"			) as fp:
							json.dump(a_				,						a_			)



					def 			_lowercase	(   self	:    Any				,						**__A	:    str			):
						return CLIPTokenizer.from_pretrained(self.tmpdirname				,						pad_token="!"				,						**a_			)



					def 			_lowercase	(   self	:    List[Any]				,						**__A	:    Union[str, Any]			):
						return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,						pad_token="!"				,						**a_			)



					def 			_lowercase	(   self	:    Optional[Any]				,						**__A	:    int			):
						return OwlViTImageProcessor.from_pretrained(self.tmpdirname				,						**a_			)



					def 			_lowercase	(   self	:    str			):
						shutil.rmtree(self.tmpdirname			)



					def 			_lowercase	(   self	:    Optional[int]			):
						snake_case__					: Optional[int]  =    [np.random.randint(2_5_5				,						size=(3, 3_0, 4_0_0)				,						dtype=np.uinta			)]

						snake_case__					: List[str]  =    [Image.fromarray(np.moveaxis(a_				,						0				,						-1			)			) for x in image_inputs]

						return image_inputs



					def 			_lowercase	(   self	:    Tuple			):
						snake_case__					: Any  =    self.get_tokenizer()
						snake_case__					: int  =    self.get_rust_tokenizer()
						snake_case__					: int  =    self.get_image_processor()

						snake_case__					: List[Any]  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)
						processor_slow.save_pretrained(self.tmpdirname			)
						snake_case__					: Tuple  =    OwlViTProcessor.from_pretrained(self.tmpdirname				,						use_fast=a_			)

						snake_case__					: Dict  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)
						processor_fast.save_pretrained(self.tmpdirname			)
						snake_case__					: Any  =    OwlViTProcessor.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				,						a_			)
						self.assertIsInstance(processor_fast.tokenizer				,						a_			)

						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				,						a_			)
						self.assertIsInstance(processor_fast.image_processor				,						a_			)



					def 			_lowercase	(   self	:    Optional[int]			):
						snake_case__					: Tuple  =    OwlViTProcessor(tokenizer=self.get_tokenizer()				,						image_processor=self.get_image_processor()			)
						processor.save_pretrained(self.tmpdirname			)

						snake_case__					: Union[str, Any]  =    self.get_tokenizer(bos_token="(BOS)"				,						eos_token="(EOS)"			)
						snake_case__					: List[Any]  =    self.get_image_processor(do_normalize=a_			)

						snake_case__					: Union[str, Any]  =    OwlViTProcessor.from_pretrained(
						    self.tmpdirname				,						bos_token="(BOS)"				,						eos_token="(EOS)"				,						do_normalize=a_			)

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

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



					def 			_lowercase	(   self	:    Dict			):
						snake_case__					: Union[str, Any]  =    self.get_image_processor()
						snake_case__					: Optional[Any]  =    self.get_tokenizer()

						snake_case__					: Tuple  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)

						snake_case__					: Dict  =    self.prepare_image_inputs()

						snake_case__					: Optional[Any]  =    image_processor(a_				,						return_tensors="np"			)
						snake_case__					: Optional[Any]  =    processor(images=a_				,						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 			_lowercase	(   self	:    int			):
						snake_case__					: Dict  =    self.get_image_processor()
						snake_case__					: List[Any]  =    self.get_tokenizer()

						snake_case__					: Union[str, Any]  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)

						snake_case__					: Tuple  =    "lower newer"

						snake_case__					: Optional[int]  =    processor(text=a_				,						return_tensors="np"			)

						snake_case__					: Dict  =    tokenizer(a_				,						return_tensors="np"			)

						for key in encoded_tok.keys():
							self.assertListEqual(encoded_tok[key][0].tolist()				,						encoded_processor[key][0].tolist()			)



					def 			_lowercase	(   self	:    List[Any]			):
						snake_case__					: Any  =    self.get_image_processor()
						snake_case__					: Dict  =    self.get_tokenizer()

						snake_case__					: Optional[Any]  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)

						snake_case__					: List[Any]  =    "lower newer"
						snake_case__					: Dict  =    self.prepare_image_inputs()

						snake_case__					: List[str]  =    processor(text=a_				,						images=a_			)

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

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



					def 			_lowercase	(   self	:    Optional[int]			):
						snake_case__					: int  =    "google/owlvit-base-patch32"
						snake_case__					: List[str]  =    OwlViTProcessor.from_pretrained(a_			)

						snake_case__					: Optional[int]  =    ["cat", "nasa badge"]
						snake_case__					: Union[str, Any]  =    processor(text=a_			)

						snake_case__					: Union[str, Any]  =    1_6
						self.assertListEqual(list(inputs.keys()			)				,						["input_ids", "attention_mask"]			)
						self.assertEqual(inputs["input_ids"].shape				,						(2, seq_length)			)

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



					def 			_lowercase	(   self	:    Dict			):
						snake_case__					: Any  =    "google/owlvit-base-patch32"
						snake_case__					: str  =    OwlViTProcessor.from_pretrained(a_			)

						snake_case__					: str  =    [["cat", "nasa badge"], ["person"]]
						snake_case__					: Optional[int]  =    processor(text=a_			)

						snake_case__					: str  =    1_6
						snake_case__					: Optional[int]  =    len(a_			)
						snake_case__					: List[Any]  =    max([len(a_			) for texts in input_texts]			)

						self.assertListEqual(list(inputs.keys()			)				,						["input_ids", "attention_mask"]			)
						self.assertEqual(inputs["input_ids"].shape				,						(batch_size * num_max_text_queries, seq_length)			)

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



					def 			_lowercase	(   self	:    int			):
						snake_case__					: Optional[Any]  =    "google/owlvit-base-patch32"
						snake_case__					: Dict  =    OwlViTProcessor.from_pretrained(a_			)

						snake_case__					: str  =    ["cat", "nasa badge"]
						snake_case__					: Optional[int]  =    processor(text=a_			)

						snake_case__					: Optional[int]  =    1_6
						snake_case__					: List[Any]  =    inputs["input_ids"]
						snake_case__					: Optional[Any]  =    [
						    [4_9_4_0_6, 2_3_6_8, 4_9_4_0_7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
						    [4_9_4_0_6, 6_8_4_1, 1_1_3_0_1, 4_9_4_0_7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
						]

						self.assertListEqual(list(inputs.keys()			)				,						["input_ids", "attention_mask"]			)
						self.assertEqual(inputs["input_ids"].shape				,						(2, seq_length)			)
						self.assertListEqual(list(input_ids[0]			)				,						predicted_ids[0]			)
						self.assertListEqual(list(input_ids[1]			)				,						predicted_ids[1]			)



					def 			_lowercase	(   self	:    Optional[Any]			):
						snake_case__					: Dict  =    self.get_image_processor()
						snake_case__					: Dict  =    self.get_tokenizer()

						snake_case__					: Union[str, Any]  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)

						snake_case__					: List[Any]  =    self.prepare_image_inputs()
						snake_case__					: int  =    self.prepare_image_inputs()

						snake_case__					: Dict  =    processor(images=a_				,						query_images=a_			)

						self.assertListEqual(list(inputs.keys()			)				,						["query_pixel_values", "pixel_values"]			)

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






					def 			_lowercase	(   self	:    Any			):
						snake_case__					: int  =    self.get_image_processor()
						snake_case__					: int  =    self.get_tokenizer()

						snake_case__					: Dict  =    OwlViTProcessor(tokenizer=a_				,						image_processor=a_			)

						snake_case__					: str  =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

						snake_case__					: List[str]  =    processor.batch_decode(a_			)
						snake_case__					: Optional[int]  =    tokenizer.batch_decode(a_			)

						self.assertListEqual(a_				,						a_			)










"""simple docstring"""






__UpperCAmelCase						=			[
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]






def      lowercase__ (					lowerCAmelCase__   :			Dict							,			lowerCAmelCase__   :			Optional[int]							,			lowerCAmelCase__   :			List[str]							,			lowerCAmelCase__   :			Tuple			)    ->			Dict:



			'''simple docstring'''
			# Return True if there is node that has not iterated.
			a__  :	int		 =			[False] * len(lowerCAmelCase__			)
			a__  :	Optional[Any]		 =			[s]
			a__  :	Optional[int]		 =			True

			while queue:
						a__  :	Any		 =			queue.pop(0			)
						for ind in range(len(graph[u]			)			):
									if visited[ind] is False and graph[u][ind] > 0:
												queue.append(lowerCAmelCase__			)
												a__  :	Any		 =			True
												a__  :	Union[str, Any]		 =			u

			return visited[t]






def      lowercase__ (					lowerCAmelCase__   :			List[str]							,			lowerCAmelCase__   :			List[Any]							,			lowerCAmelCase__   :			Optional[Any]			)    ->			Any:



			'''simple docstring'''
			a__  :	Any		 =			[-1] * (len(lowerCAmelCase__			))
			a__  :	Any		 =			0
			a__  :	List[str]		 =			[]
			a__  :	Tuple		 =			[i[:] for i in graph]  # Record original cut, copy.
			while bfs(lowerCAmelCase__							,			lowerCAmelCase__							,			lowerCAmelCase__							,			lowerCAmelCase__			):
						a__  :	Any		 =			float("Inf"			)
						a__  :	Optional[int]		 =			sink

						while s != source:
									# Find the minimum value in select path
									a__  :	Union[str, Any]		 =			min(lowerCAmelCase__							,			graph[parent[s]][s]			)
									a__  :	List[str]		 =			parent[s]

						max_flow += path_flow
						a__  :	List[str]		 =			sink

						while v != source:
									a__  :	int		 =			parent[v]
									graph[u][v] -= path_flow
									graph[v][u] += path_flow
									a__  :	List[str]		 =			parent[v]

			for i in range(len(lowerCAmelCase__			)			):
						for j in range(len(graph[0]			)			):
									if graph[i][j] == 0 and temp[i][j] > 0:
												res.append((i, j)			)

			return res


if __name__ == "__main__":
		print(mincut(test_graph, source=0, sink=5))