'''simple docstring'''

import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast


@require_vision
class 	a__     (				unittest.TestCase	):


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

					"""simple docstring"""

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

					SCREAMING_SNAKE_CASE  :						Any      					= BlipImageProcessor()
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= BertTokenizer.from_pretrained('''hf-internal-testing/tiny-random-BertModel'''      )

					SCREAMING_SNAKE_CASE  :						Dict      					= BlipProcessor(__UpperCAmelCase,					__UpperCAmelCase      )

					processor.save_pretrained(self.tmpdirname      )


	def 				lowercase__  (self : List[str],					**__UpperCAmelCase : Optional[int]      )     ->			Tuple:

					"""simple docstring"""

					return AutoProcessor.from_pretrained(self.tmpdirname,					**__UpperCAmelCase      ).tokenizer


	def 				lowercase__  (self : Optional[int],					**__UpperCAmelCase : List[Any]      )     ->			str:

					"""simple docstring"""

					return AutoProcessor.from_pretrained(self.tmpdirname,					**__UpperCAmelCase      ).image_processor


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

					"""simple docstring"""

					shutil.rmtree(self.tmpdirname      )


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

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Tuple      					= [np.random.randint(255,					size=(3, 30, 400),					dtype=np.uinta      )]

					SCREAMING_SNAKE_CASE  :						Any      					= [Image.fromarray(np.moveaxis(__UpperCAmelCase,					0,					-1      )      ) for x in image_inputs]

					return image_inputs


	def 				lowercase__  (self : Optional[int]      )     ->			Tuple:

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Tuple      					= BlipProcessor(tokenizer=self.get_tokenizer(),					image_processor=self.get_image_processor()      )
					processor.save_pretrained(self.tmpdirname      )

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= self.get_tokenizer(bos_token='''(BOS)''',					eos_token='''(EOS)'''      )
					SCREAMING_SNAKE_CASE  :						int      					= self.get_image_processor(do_normalize=__UpperCAmelCase,					padding_value=1.0      )

					SCREAMING_SNAKE_CASE  :						Optional[int]      					= BlipProcessor.from_pretrained(
					    self.tmpdirname,					bos_token='''(BOS)''',					eos_token='''(EOS)''',					do_normalize=__UpperCAmelCase,					padding_value=1.0      )

					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 				lowercase__  (self : Union[str, Any]      )     ->			Any:

					"""simple docstring"""

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

					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= BlipProcessor(tokenizer=__UpperCAmelCase,					image_processor=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						int      					= self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= image_processor(__UpperCAmelCase,					return_tensors='''np'''      )
					SCREAMING_SNAKE_CASE  :						List[Any]      					= processor(images=__UpperCAmelCase,					return_tensors='''np'''      )

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


	def 				lowercase__  (self : Union[str, Any]      )     ->			List[Any]:

					"""simple docstring"""

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

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= BlipProcessor(tokenizer=__UpperCAmelCase,					image_processor=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						Any      					= '''lower newer'''

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= processor(text=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						int      					= tokenizer(__UpperCAmelCase,					return_token_type_ids=__UpperCAmelCase      )

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


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

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Tuple      					= self.get_image_processor()
					SCREAMING_SNAKE_CASE  :						Tuple      					= self.get_tokenizer()

					SCREAMING_SNAKE_CASE  :						Tuple      					= BlipProcessor(tokenizer=__UpperCAmelCase,					image_processor=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						Tuple      					= '''lower newer'''
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE  :						str      					= processor(text=__UpperCAmelCase,					images=__UpperCAmelCase      )

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

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


	def 				lowercase__  (self : str      )     ->			int:

					"""simple docstring"""

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

					SCREAMING_SNAKE_CASE  :						Optional[int]      					= BlipProcessor(tokenizer=__UpperCAmelCase,					image_processor=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						Optional[int]      					= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= processor.batch_decode(__UpperCAmelCase      )
					SCREAMING_SNAKE_CASE  :						Any      					= tokenizer.batch_decode(__UpperCAmelCase      )

					self.assertListEqual(__UpperCAmelCase,					__UpperCAmelCase      )






	def 				lowercase__  (self : int      )     ->			List[str]:

					"""simple docstring"""

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

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= BlipProcessor(tokenizer=__UpperCAmelCase,					image_processor=__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= '''lower newer'''
					SCREAMING_SNAKE_CASE  :						str      					= self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE  :						Optional[int]      					= processor(text=__UpperCAmelCase,					images=__UpperCAmelCase      )

					# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
					self.assertListEqual(list(inputs.keys()      ),					['''pixel_values''', '''input_ids''', '''attention_mask''']      )









'''simple docstring'''

from manim import *


class 	a__     (				_lowercase	):


	def 				lowercase__  (self : Optional[Any]      )     ->			str:

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						List[Any]      					= Rectangle(height=0.5,					width=0.5      )
					SCREAMING_SNAKE_CASE  :						str      					= Rectangle(height=0.46,					width=0.46      ).set_stroke(width=0      )

					SCREAMING_SNAKE_CASE  :						List[str]      					= [mem.copy() for i in range(6      )]
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= [mem.copy() for i in range(6      )]
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= VGroup(*__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0      )
					SCREAMING_SNAKE_CASE  :						List[str]      					= VGroup(*__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0      )
					SCREAMING_SNAKE_CASE  :						List[Any]      					= VGroup(__UpperCAmelCase,					__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0      )
					SCREAMING_SNAKE_CASE  :						Tuple      					= Text('''CPU''',					font_size=24      )
					SCREAMING_SNAKE_CASE  :						Dict      					= Group(__UpperCAmelCase,					__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0.5,					aligned_edge=__UpperCAmelCase      )
					cpu.move_to([-2.5, -0.5, 0]      )
					self.add(__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						Any      					= [mem.copy() for i in range(1      )]
					SCREAMING_SNAKE_CASE  :						Dict      					= VGroup(*__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0      )
					SCREAMING_SNAKE_CASE  :						List[str]      					= Text('''GPU''',					font_size=24      )
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= Group(__UpperCAmelCase,					__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0.5,					aligned_edge=__UpperCAmelCase      )
					gpu.align_to(__UpperCAmelCase,					__UpperCAmelCase      )
					gpu.set_x(gpu.get_x() - 1      )

					self.add(__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						List[Any]      					= [mem.copy() for i in range(6      )]
					SCREAMING_SNAKE_CASE  :						Any      					= VGroup(*__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0      )

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= Text('''Model''',					font_size=24      )
					SCREAMING_SNAKE_CASE  :						Dict      					= Group(__UpperCAmelCase,					__UpperCAmelCase      ).arrange(__UpperCAmelCase,					buff=0.5,					aligned_edge=__UpperCAmelCase      )
					model.move_to([3, -1.0, 0]      )

					self.play(
					    Create(__UpperCAmelCase,					run_time=1      ),					Create(__UpperCAmelCase,					run_time=1      ),					Create(__UpperCAmelCase,					run_time=1      ),					)

					SCREAMING_SNAKE_CASE  :						Tuple      					= MarkupText(
					    F'''First, an empty model skeleton is loaded\ninto <span fgcolor=\'{YELLOW}\'>memory</span> without using much RAM.''',					font_size=24,					)

					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= Square(side_length=2.2      )
					key.move_to([-5, 2, 0]      )

					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= MarkupText(
					    F'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model''',					font_size=18,					)

					key_text.move_to([-5, 2.4, 0]      )

					step_a.move_to([2, 2, 0]      )
					self.play(Write(__UpperCAmelCase,					run_time=2.5      ),					Write(__UpperCAmelCase      ),					Write(__UpperCAmelCase      )      )

					self.add(__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						List[str]      					= []
					SCREAMING_SNAKE_CASE  :						List[str]      					= []
					SCREAMING_SNAKE_CASE  :						Dict      					= []
					for i, rect in enumerate(__UpperCAmelCase      ):
									SCREAMING_SNAKE_CASE  :						Optional[int]      					= Rectangle(height=0.46,					width=0.46      ).set_stroke(width=0.0      ).set_fill(__UpperCAmelCase,					opacity=0.7      )
									cpu_target.move_to(__UpperCAmelCase      )
									cpu_target.generate_target()
									SCREAMING_SNAKE_CASE  :						List[str]      					= 0.46 / 4
									SCREAMING_SNAKE_CASE  :						Any      					= 0.46 / 3

									if i == 0:
													cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT      ),					buff=0.02,					direction=__UpperCAmelCase      )
													cpu_target.target.set_x(cpu_target.target.get_x() + 0.1      )
									elif i == 3:
													cpu_target.target.next_to(cpu_targs[0].target,					direction=__UpperCAmelCase,					buff=0.0      )
									else:
													cpu_target.target.next_to(cpu_targs[i - 1].target,					direction=__UpperCAmelCase,					buff=0.0      )
									cpu_targs.append(__UpperCAmelCase      )

									first_animations.append(rect.animate(run_time=0.5      ).set_stroke(__UpperCAmelCase      )      )
									second_animations.append(MoveToTarget(__UpperCAmelCase,					run_time=1.5      )      )

					self.play(*__UpperCAmelCase      )
					self.play(*__UpperCAmelCase      )

					self.wait()




