






from manim import *




class 				__A     (			a ):





				"""simple docstring"""







				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Optional[Any]       		=Rectangle(height=0.5							,  width=0.5    )
									__UpperCamelCase      :					Dict       		=Rectangle(height=0.46							,  width=0.46    ).set_stroke(width=0    )

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

									__UpperCamelCase      :					Union[str, Any]       		=[mem.copy() for i in range(4    )]
									__UpperCamelCase      :					List[str]       		=VGroup(*lowerCamelCase__    ).arrange(lowerCamelCase__							,  buff=0    )
									__UpperCamelCase      :					str       		=Text('GPU'							,  font_size=24    )
									__UpperCamelCase      :					List[str]       		=Group(lowerCamelCase__							,  lowerCamelCase__    ).arrange(lowerCamelCase__							,  buff=0.5							,  aligned_edge=lowerCamelCase__    )
									gpu.move_to([-1, -1, 0]    )
									self.add(lowerCamelCase__    )

									__UpperCamelCase      :					Optional[int]       		=[mem.copy() for i in range(6    )]
									__UpperCamelCase      :					Dict       		=VGroup(*lowerCamelCase__    ).arrange(lowerCamelCase__							,  buff=0    )

									__UpperCamelCase      :					Optional[int]       		=Text('Model'							,  font_size=24    )
									__UpperCamelCase      :					Tuple       		=Group(lowerCamelCase__							,  lowerCamelCase__    ).arrange(lowerCamelCase__							,  buff=0.5							,  aligned_edge=lowerCamelCase__    )
									model.move_to([3, -1.0, 0]    )
									self.add(lowerCamelCase__    )

									__UpperCamelCase      :					List[Any]       		=[]
									for i, rect in enumerate(lowerCamelCase__    ):
														rect.set_stroke(lowerCamelCase__    )
														# target = fill.copy().set_fill(YELLOW, opacity=0.7)
														# target.move_to(rect)
														# self.add(target)

														__UpperCamelCase      :					List[Any]       		=Rectangle(height=0.46 / 4							,  width=0.46 / 3    ).set_stroke(width=0.0    ).set_fill(lowerCamelCase__							,  opacity=0.7    )

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

									__UpperCamelCase      :					Tuple       		=[mem.copy() for i in range(6    )]
									__UpperCamelCase      :					List[str]       		=VGroup(*lowerCamelCase__    ).arrange(lowerCamelCase__							,  buff=0    )

									__UpperCamelCase      :					List[str]       		=Text('Loaded Checkpoint'							,  font_size=24    )
									__UpperCamelCase      :					Union[str, Any]       		=Group(lowerCamelCase__							,  lowerCamelCase__    ).arrange(lowerCamelCase__							,  aligned_edge=lowerCamelCase__							,  buff=0.4    )
									checkpoint.move_to([3, 0.5, 0]    )

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

									__UpperCamelCase      :					List[str]       		=MarkupText(
									    f'<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model'							,  font_size=18							,  )

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

									self.add(lowerCamelCase__							,  lowerCamelCase__    )

									__UpperCamelCase      :					Tuple       		=MarkupText(
									    f'<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'							,  font_size=18							,  )

									blue_text.next_to(lowerCamelCase__							,  DOWN * 2.4							,  aligned_edge=key_text.get_left()    )

									__UpperCamelCase      :					int       		=MarkupText(
									    f'Next, a <i><span fgcolor="{BLUE}">second</span></i> model is loaded into memory,\nwith the weights of a <span fgcolor="{BLUE}">single shard</span>.'							,  font_size=24							,  )
									step_a.move_to([2, 2, 0]    )
									self.play(Write(lowerCamelCase__    )							,  Write(lowerCamelCase__    )    )

									self.play(Write(lowerCamelCase__							,  run_time=1    )							,  Create(lowerCamelCase__							,  run_time=1    )    )

									__UpperCamelCase      :					str       		=[]
									__UpperCamelCase      :					Tuple       		=[]
									for i, rect in enumerate(lowerCamelCase__    ):
														__UpperCamelCase      :					List[Any]       		=fill.copy().set_fill(lowerCamelCase__							,  opacity=0.7    )
														target.move_to(lowerCamelCase__    )
														first_animations.append(GrowFromCenter(lowerCamelCase__							,  run_time=1    )    )

														__UpperCamelCase      :					Dict       		=target.copy()
														cpu_target.generate_target()
														if i < 5:
																			cpu_target.target.move_to(cpu_left_col_base[i + 1]    )
														else:
																			cpu_target.target.move_to(cpu_right_col_base[i - 5]    )
														second_animations.append(MoveToTarget(lowerCamelCase__							,  run_time=1.5    )    )

									self.play(*lowerCamelCase__    )
									self.play(*lowerCamelCase__    )
									self.wait()









import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_a      	=  get_tests_dir('''fixtures/spiece.model''')





@require_sentencepiece
@require_tokenizers
class __lowerCamelCase (      snake_case__     ,       unittest.TestCase):





	"""simple docstring"""






	UpperCamelCase__								=      AlbertTokenizer
	UpperCamelCase__								=      AlbertTokenizerFast
	UpperCamelCase__								=      True
	UpperCamelCase__								=      True
	UpperCamelCase__								=      True

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							super().setUp()

							# We have a SentencePiece fixture for testing
							_UpperCAmelCase									=			AlbertTokenizer(UpperCAmelCase    )
							tokenizer.save_pretrained(self.tmpdirname    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			'this is a test'
							_UpperCAmelCase									=			'this is a test'
							return input_text, output_text

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			'<pad>'
							_UpperCAmelCase									=			0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase    )       ,    UpperCAmelCase    )
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase    )       ,    UpperCAmelCase    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			list(self.get_tokenizer().get_vocab().keys()    )

							self.assertEqual(vocab_keys[0]       ,    '<pad>'    )
							self.assertEqual(vocab_keys[1]       ,    '<unk>'    )
							self.assertEqual(vocab_keys[-1]       ,    '▁eloquent'    )
							self.assertEqual(len(UpperCAmelCase    )       ,    3_0000    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							self.assertEqual(self.get_tokenizer().vocab_size       ,    3_0000    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							if not self.test_rust_tokenizer:
													return

							_UpperCAmelCase									=			self.get_tokenizer()
							_UpperCAmelCase									=			self.get_rust_tokenizer()

							_UpperCAmelCase									=			'I was born in 92000, and this is falsé.'

							_UpperCAmelCase									=			tokenizer.tokenize(UpperCAmelCase    )
							_UpperCAmelCase									=			rust_tokenizer.tokenize(UpperCAmelCase    )
							self.assertListEqual(UpperCAmelCase       ,    UpperCAmelCase    )

							_UpperCAmelCase									=			tokenizer.encode(UpperCAmelCase       ,    add_special_tokens=UpperCAmelCase    )
							_UpperCAmelCase									=			rust_tokenizer.encode(UpperCAmelCase       ,    add_special_tokens=UpperCAmelCase    )
							self.assertListEqual(UpperCAmelCase       ,    UpperCAmelCase    )

							_UpperCAmelCase									=			self.get_rust_tokenizer()
							_UpperCAmelCase									=			tokenizer.encode(UpperCAmelCase    )
							_UpperCAmelCase									=			rust_tokenizer.encode(UpperCAmelCase    )
							self.assertListEqual(UpperCAmelCase       ,    UpperCAmelCase    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			AlbertTokenizer(UpperCAmelCase       ,    keep_accents=UpperCAmelCase    )

							_UpperCAmelCase									=			tokenizer.tokenize('This is a test'    )
							self.assertListEqual(UpperCAmelCase       ,    ['▁this', '▁is', '▁a', '▁test']    )

							self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase    )       ,    [48, 25, 21, 1289]    )

							_UpperCAmelCase									=			tokenizer.tokenize('I was born in 92000, and this is falsé.'    )
							self.assertListEqual(
							    UpperCAmelCase       ,    ['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.']    )
							_UpperCAmelCase									=			tokenizer.convert_tokens_to_ids(UpperCAmelCase    )
							self.assertListEqual(UpperCAmelCase       ,    [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]    )

							_UpperCAmelCase									=			tokenizer.convert_ids_to_tokens(UpperCAmelCase    )
							self.assertListEqual(
							    UpperCAmelCase       ,    ['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.']       ,    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			AlbertTokenizer(UpperCAmelCase    )

							_UpperCAmelCase									=			tokenizer.encode('sequence builders'    )
							_UpperCAmelCase									=			tokenizer.encode('multi-sequence build'    )

							_UpperCAmelCase									=			tokenizer.build_inputs_with_special_tokens(UpperCAmelCase    )
							_UpperCAmelCase									=			tokenizer.build_inputs_with_special_tokens(UpperCAmelCase       ,    UpperCAmelCase    )

							assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
							assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
							    tokenizer.sep_token_id
							]

	@slow
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			{'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'input_ids': [[2, 2_1970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 1_2051, 18, 17, 7103, 2153, 673, 8, 3515, 1_8684, 8, 4461, 6, 1927, 297, 8, 1_2060, 2607, 18, 13, 5, 4461, 15, 1_0538, 38, 8, 135, 15, 822, 58, 15, 993, 1_0363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 1_0641, 6, 29, 84, 2512, 2430, 782, 1_8684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 1_1712, 15, 7103, 2153, 673, 17, 2_4883, 9990, 9, 3], [2, 1_1502, 25, 1006, 20, 782, 8, 1_1809, 855, 1732, 1_9393, 1_8667, 37, 367, 2_1018, 69, 1854, 34, 1_1860, 1_9124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 2231, 886, 2385, 1_7659, 84, 14, 1_6792, 1952, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=UpperCAmelCase       ,    model_name='albert-base-v2'       ,    revision='6b6560eaf5ff2e250b00c50f380c5389a9c2d82e'       ,    )
