
'''simple docstring'''
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 	snake_case__       (      unittest.TestCase					):







		"""simple docstring"""

		def       lowerCAmelCase				(      self				:			List[str]      )						->			Dict:






				"""simple docstring"""







				snake_case  :       List[Any]     			=						tempfile.mkdtemp()

				# fmt: off
				snake_case  :       Tuple     			=						["", "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  :       Union[str, Any]     			=						dict(zip(UpperCamelCase__  ,	range(len(UpperCamelCase__      )      )      )      )
				snake_case  :       List[Any]     			=						["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
				snake_case  :       List[Any]     			=						{"unk_token": "<unk>"}

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

				snake_case  :       Optional[Any]     			=						{
				    "do_resize": True,
				    "size": 20,
				    "do_center_crop": True,
				    "crop_size": 18,
				    "do_normalize": True,
				    "image_mean": [0.48_145_466, 0.4_578_275, 0.40_821_073],
				    "image_std": [0.26_862_954, 0.26_130_258, 0.27_577_711],
				}
				snake_case  :       List[str]     			=						os.path.join(self.tmpdirname  ,	UpperCamelCase__      )
				with open(self.image_processor_file  ,	'''w'''  ,	encoding='''utf-8'''      ) as fp:
						json.dump(UpperCamelCase__  ,	UpperCamelCase__      )



		def       lowerCAmelCase				(      self				:			List[str]  ,	**UpperCamelCase__				:			Optional[Any]      )						->			Tuple:






				"""simple docstring"""







				return CLIPTokenizer.from_pretrained(self.tmpdirname  ,	pad_token='''!'''  ,	**UpperCamelCase__      )



		def       lowerCAmelCase				(      self				:			List[str]  ,	**UpperCamelCase__				:			List[Any]      )						->			int:






				"""simple docstring"""







				return CLIPTokenizerFast.from_pretrained(self.tmpdirname  ,	pad_token='''!'''  ,	**UpperCamelCase__      )



		def       lowerCAmelCase				(      self				:			Any  ,	**UpperCamelCase__				:			str      )						->			Any:






				"""simple docstring"""







				return OwlViTImageProcessor.from_pretrained(self.tmpdirname  ,	**UpperCamelCase__      )



		def       lowerCAmelCase				(      self				:			Any      )						->			Optional[int]:






				"""simple docstring"""







				shutil.rmtree(self.tmpdirname      )



		def       lowerCAmelCase				(      self				:			Union[str, Any]      )						->			Tuple:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						[np.random.randint(255  ,	size=(3, 30, 400)  ,	dtype=np.uinta      )]

				snake_case  :       Optional[int]     			=						[Image.fromarray(np.moveaxis(UpperCamelCase__  ,	0  ,	-1      )      ) for x in image_inputs]

				return image_inputs



		def       lowerCAmelCase				(      self				:			Optional[int]      )						->			str:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						self.get_tokenizer()
				snake_case  :       List[Any]     			=						self.get_rust_tokenizer()
				snake_case  :       Any     			=						self.get_image_processor()

				snake_case  :       str     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )
				processor_slow.save_pretrained(self.tmpdirname      )
				snake_case  :       Any     			=						OwlViTProcessor.from_pretrained(self.tmpdirname  ,	use_fast=UpperCamelCase__      )

				snake_case  :       List[str]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )
				processor_fast.save_pretrained(self.tmpdirname      )
				snake_case  :       Optional[int]     			=						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  ,	UpperCamelCase__      )
				self.assertIsInstance(processor_fast.tokenizer  ,	UpperCamelCase__      )

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



		def       lowerCAmelCase				(      self				:			Any      )						->			List[Any]:






				"""simple docstring"""







				snake_case  :       Optional[Any]     			=						OwlViTProcessor(tokenizer=self.get_tokenizer()  ,	image_processor=self.get_image_processor()      )
				processor.save_pretrained(self.tmpdirname      )

				snake_case  :       List[str]     			=						self.get_tokenizer(bos_token='''(BOS)'''  ,	eos_token='''(EOS)'''      )
				snake_case  :       Optional[int]     			=						self.get_image_processor(do_normalize=UpperCamelCase__      )

				snake_case  :       List[Any]     			=						OwlViTProcessor.from_pretrained(
				    self.tmpdirname  ,	bos_token='''(BOS)'''  ,	eos_token='''(EOS)'''  ,	do_normalize=UpperCamelCase__      )

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

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



		def       lowerCAmelCase				(      self				:			Optional[int]      )						->			str:






				"""simple docstring"""







				snake_case  :       Optional[Any]     			=						self.get_image_processor()
				snake_case  :       int     			=						self.get_tokenizer()

				snake_case  :       Optional[Any]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )

				snake_case  :       Dict     			=						self.prepare_image_inputs()

				snake_case  :       Optional[Any]     			=						image_processor(UpperCamelCase__  ,	return_tensors='''np'''      )
				snake_case  :       Dict     			=						processor(images=UpperCamelCase__  ,	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       lowerCAmelCase				(      self				:			Tuple      )						->			Any:






				"""simple docstring"""







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

				snake_case  :       List[str]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )

				snake_case  :       str     			=						"lower newer"

				snake_case  :       int     			=						processor(text=UpperCamelCase__  ,	return_tensors='''np'''      )

				snake_case  :       List[str]     			=						tokenizer(UpperCamelCase__  ,	return_tensors='''np'''      )

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



		def       lowerCAmelCase				(      self				:			Optional[Any]      )						->			Optional[Any]:






				"""simple docstring"""







				snake_case  :       Tuple     			=						self.get_image_processor()
				snake_case  :       Dict     			=						self.get_tokenizer()

				snake_case  :       List[str]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )

				snake_case  :       Any     			=						"lower newer"
				snake_case  :       Any     			=						self.prepare_image_inputs()

				snake_case  :       Optional[int]     			=						processor(text=UpperCamelCase__  ,	images=UpperCamelCase__      )

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

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



		def       lowerCAmelCase				(      self				:			Union[str, Any]      )						->			Tuple:






				"""simple docstring"""







				snake_case  :       str     			=						"google/owlvit-base-patch32"
				snake_case  :       int     			=						OwlViTProcessor.from_pretrained(UpperCamelCase__      )

				snake_case  :       Optional[int]     			=						["cat", "nasa badge"]
				snake_case  :       Optional[int]     			=						processor(text=UpperCamelCase__      )

				snake_case  :       Dict     			=						16
				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(UpperCamelCase__      ):
						processor()



		def       lowerCAmelCase				(      self				:			int      )						->			Union[str, Any]:






				"""simple docstring"""







				snake_case  :       str     			=						"google/owlvit-base-patch32"
				snake_case  :       List[Any]     			=						OwlViTProcessor.from_pretrained(UpperCamelCase__      )

				snake_case  :       str     			=						[["cat", "nasa badge"], ["person"]]
				snake_case  :       Optional[Any]     			=						processor(text=UpperCamelCase__      )

				snake_case  :       Any     			=						16
				snake_case  :       Union[str, Any]     			=						len(UpperCamelCase__      )
				snake_case  :       List[str]     			=						max([len(UpperCamelCase__      ) 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(UpperCamelCase__      ):
						processor()



		def       lowerCAmelCase				(      self				:			List[str]      )						->			str:






				"""simple docstring"""







				snake_case  :       Any     			=						"google/owlvit-base-patch32"
				snake_case  :       Optional[Any]     			=						OwlViTProcessor.from_pretrained(UpperCamelCase__      )

				snake_case  :       Any     			=						["cat", "nasa badge"]
				snake_case  :       str     			=						processor(text=UpperCamelCase__      )

				snake_case  :       Any     			=						16
				snake_case  :       Optional[int]     			=						inputs["input_ids"]
				snake_case  :       int     			=						[
				    [4_9406, 2368, 4_9407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
				    [4_9406, 6841, 1_1301, 4_9407, 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       lowerCAmelCase				(      self				:			List[Any]      )						->			Tuple:






				"""simple docstring"""







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

				snake_case  :       List[Any]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )

				snake_case  :       Dict     			=						self.prepare_image_inputs()
				snake_case  :       Dict     			=						self.prepare_image_inputs()

				snake_case  :       Union[str, Any]     			=						processor(images=UpperCamelCase__  ,	query_images=UpperCamelCase__      )

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

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



		def       lowerCAmelCase				(      self				:			List[Any]      )						->			List[Any]:






				"""simple docstring"""







				snake_case  :       List[Any]     			=						self.get_image_processor()
				snake_case  :       Any     			=						self.get_tokenizer()

				snake_case  :       List[str]     			=						OwlViTProcessor(tokenizer=UpperCamelCase__  ,	image_processor=UpperCamelCase__      )

				snake_case  :       Optional[Any]     			=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

				snake_case  :       str     			=						processor.batch_decode(UpperCamelCase__      )
				snake_case  :       Any     			=						tokenizer.batch_decode(UpperCamelCase__      )

				self.assertListEqual(UpperCamelCase__  ,	UpperCamelCase__      )






import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


SCREAMING_SNAKE_CASE__     					=			logging.getLogger(__name__)



class 						_UpperCAmelCase      (     lowercase							):






		def __init__(						self				:     Optional[int]   ,  UpperCAmelCase				:     Any=-1):
				# in NER datasets, the last column is usually reserved for NER label
				SCREAMING_SNAKE_CASE_				:Tuple				     =						label_idx






		def _snake_case		(						self				:     Tuple   ,  UpperCAmelCase				:     Any   ,  UpperCAmelCase				:     Union[Split, str]):
				if isinstance(UpperCAmelCase   ,  UpperCAmelCase):
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						mode.value
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						os.path.join(UpperCAmelCase   ,  F"{mode}.txt")
				SCREAMING_SNAKE_CASE_				:Tuple				     =						1
				SCREAMING_SNAKE_CASE_				:str				     =						[]
				with open(UpperCAmelCase   ,  encoding="utf-8") as f:
						SCREAMING_SNAKE_CASE_				:Tuple				     =						[]
						SCREAMING_SNAKE_CASE_				:int				     =						[]
						for line in f:
								if line.startswith("-DOCSTART-") or line == "" or line == "\n":
										if words:
												examples.append(InputExample(guid=F"{mode}-{guid_index}"   ,  words=UpperCAmelCase   ,  labels=UpperCAmelCase))
												guid_index += 1
												SCREAMING_SNAKE_CASE_				:Tuple				     =						[]
												SCREAMING_SNAKE_CASE_				:Any				     =						[]
								else:
										SCREAMING_SNAKE_CASE_				:int				     =						line.split(" ")
										words.append(splits[0])
										if len(UpperCAmelCase) > 1:
												labels.append(splits[self.label_idx].replace("\n"   ,  ""))
										else:
												# Examples could have no label for mode = "test"
												labels.append("O")
						if words:
								examples.append(InputExample(guid=F"{mode}-{guid_index}"   ,  words=UpperCAmelCase   ,  labels=UpperCAmelCase))
				return examples






		def _snake_case		(						self				:     List[Any]   ,  UpperCAmelCase				:     TextIO   ,  UpperCAmelCase				:     TextIO   ,  UpperCAmelCase				:     List):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						0
				for line in test_input_reader:
						if line.startswith("-DOCSTART-") or line == "" or line == "\n":
								writer.write(UpperCAmelCase)
								if not preds_list[example_id]:
										example_id += 1
						elif preds_list[example_id]:
								SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						line.split()[0] + " " + preds_list[example_id].pop(0) + "\n"
								writer.write(UpperCAmelCase)
						else:
								logger.warning("Maximum sequence length exceeded: No prediction for '%s'."   ,  line.split()[0])







		def _snake_case		(						self				:     List[str]   ,  UpperCAmelCase				:     str):
				if path:
						with open(UpperCAmelCase   ,  "r") as f:
								SCREAMING_SNAKE_CASE_				:Any				     =						f.read().splitlines()
						if "O" not in labels:
								SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						["O"] + labels
						return labels
				else:
						return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]




class 						_UpperCAmelCase      (     lowercase							):






		def __init__(						self				:     Dict):
				# in CONLL2003 dataset chunk column is second-to-last
				super().__init__(label_idx=-2)







		def _snake_case		(						self				:     Union[str, Any]   ,  UpperCAmelCase				:     str):
				if path:
						with open(UpperCAmelCase   ,  "r") as f:
								SCREAMING_SNAKE_CASE_				:Optional[int]				     =						f.read().splitlines()
						if "O" not in labels:
								SCREAMING_SNAKE_CASE_				:Dict				     =						["O"] + labels
						return labels
				else:
						return [
						    "O",
						    "B-ADVP",
						    "B-INTJ",
						    "B-LST",
						    "B-PRT",
						    "B-NP",
						    "B-SBAR",
						    "B-VP",
						    "B-ADJP",
						    "B-CONJP",
						    "B-PP",
						    "I-ADVP",
						    "I-INTJ",
						    "I-LST",
						    "I-PRT",
						    "I-NP",
						    "I-SBAR",
						    "I-VP",
						    "I-ADJP",
						    "I-CONJP",
						    "I-PP",
						]




class 						_UpperCAmelCase      (     lowercase							):






		def _snake_case		(						self				:     int   ,  UpperCAmelCase				:     List[Any]   ,  UpperCAmelCase				:     Union[Split, str]):
				if isinstance(UpperCAmelCase   ,  UpperCAmelCase):
						SCREAMING_SNAKE_CASE_				:List[str]				     =						mode.value
				SCREAMING_SNAKE_CASE_				:List[str]				     =						os.path.join(UpperCAmelCase   ,  F"{mode}.txt")
				SCREAMING_SNAKE_CASE_				:Dict				     =						1
				SCREAMING_SNAKE_CASE_				:List[str]				     =						[]

				with open(UpperCAmelCase   ,  encoding="utf-8") as f:
						for sentence in parse_incr(UpperCAmelCase):
								SCREAMING_SNAKE_CASE_				:List[str]				     =						[]
								SCREAMING_SNAKE_CASE_				:int				     =						[]
								for token in sentence:
										words.append(token["form"])
										labels.append(token["upos"])
								assert len(UpperCAmelCase) == len(UpperCAmelCase)
								if words:
										examples.append(InputExample(guid=F"{mode}-{guid_index}"   ,  words=UpperCAmelCase   ,  labels=UpperCAmelCase))
										guid_index += 1
				return examples






		def _snake_case		(						self				:     List[Any]   ,  UpperCAmelCase				:     TextIO   ,  UpperCAmelCase				:     TextIO   ,  UpperCAmelCase				:     List):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						0
				for sentence in parse_incr(UpperCAmelCase):
						SCREAMING_SNAKE_CASE_				:str				     =						preds_list[example_id]
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						""
						for token in sentence:
								out += F"{token['form']} ({token['upos']}|{s_p.pop(0)}) "
						out += "\n"
						writer.write(UpperCAmelCase)
						example_id += 1







		def _snake_case		(						self				:     Tuple   ,  UpperCAmelCase				:     str):
				if path:
						with open(UpperCAmelCase   ,  "r") as f:
								return f.read().splitlines()
				else:
						return [
						    "ADJ",
						    "ADP",
						    "ADV",
						    "AUX",
						    "CCONJ",
						    "DET",
						    "INTJ",
						    "NOUN",
						    "NUM",
						    "PART",
						    "PRON",
						    "PROPN",
						    "PUNCT",
						    "SCONJ",
						    "SYM",
						    "VERB",
						    "X",
						]






