from manim import *





class UpperCAmelCase						(					lowerCAmelCase__  ):


				'''simple docstring'''






				def   lowerCAmelCase_   (						self					):



						"""simple docstring"""





						A_		:				int     =      Rectangle(height=0.5		,	width=0.5					)
						A_		:				str     =      Rectangle(height=0.46		,	width=0.46					).set_stroke(width=0					)

						A_		:				Tuple     =      [mem.copy() for i in range(6					)]
						A_		:				Optional[Any]     =      [mem.copy() for i in range(6					)]
						A_		:				Optional[int]     =      VGroup(*__a					).arrange(__a		,	buff=0					)
						A_		:				Optional[int]     =      VGroup(*__a					).arrange(__a		,	buff=0					)
						A_		:				List[str]     =      VGroup(__a		,	__a					).arrange(__a		,	buff=0					)
						A_		:				Tuple     =      Text('CPU'		,	font_size=2_4					)
						A_		:				Optional[int]     =      Group(__a		,	__a					).arrange(__a		,	buff=0.5		,	aligned_edge=__a					)
						cpu.move_to([-2.5, -0.5, 0]					)
						self.add(__a					)

						A_		:				str     =      [mem.copy() for i in range(4					)]
						A_		:				Optional[int]     =      VGroup(*__a					).arrange(__a		,	buff=0					)
						A_		:				Tuple     =      Text('GPU'		,	font_size=2_4					)
						A_		:				int     =      Group(__a		,	__a					).arrange(__a		,	buff=0.5		,	aligned_edge=__a					)
						gpu.move_to([-1, -1, 0]					)
						self.add(__a					)

						A_		:				Union[str, Any]     =      [mem.copy() for i in range(6					)]
						A_		:				Tuple     =      VGroup(*__a					).arrange(__a		,	buff=0					)

						A_		:				Optional[Any]     =      Text('Model'		,	font_size=2_4					)
						A_		:				List[str]     =      Group(__a		,	__a					).arrange(__a		,	buff=0.5		,	aligned_edge=__a					)
						model.move_to([3, -1.0, 0]					)
						self.add(__a					)

						A_		:				Optional[int]     =      []
						for i, rect in enumerate(__a					):
								rect.set_stroke(__a					)
								# target = fill.copy().set_fill(YELLOW, opacity=0.7)
								# target.move_to(rect)
								# self.add(target)

								A_		:				Union[str, Any]     =      Rectangle(height=0.46 / 4		,	width=0.46 / 3					).set_stroke(width=0.0					).set_fill(__a		,	opacity=0.7					)

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

						A_		:				Tuple     =      [mem.copy() for i in range(6					)]
						A_		:				Any     =      VGroup(*__a					).arrange(__a		,	buff=0					)

						A_		:				List[Any]     =      Text('Loaded Checkpoint'		,	font_size=2_4					)
						A_		:				int     =      Group(__a		,	__a					).arrange(__a		,	aligned_edge=__a		,	buff=0.4					)
						checkpoint.move_to([3, 0.5, 0]					)

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

						A_		:				List[str]     =      MarkupText(
						    F'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model'''		,	font_size=1_8		,	)

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

						self.add(__a		,	__a					)

						A_		:				str     =      MarkupText(
						    F'''<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'''		,	font_size=1_8		,	)

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

						A_		:				Optional[Any]     =      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=2_4		,	)
						step_a.move_to([2, 2, 0]					)
						self.play(Write(__a					)		,	Write(__a					)					)

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

						A_		:				Optional[int]     =      []
						A_		:				Any     =      []
						for i, rect in enumerate(__a					):
								A_		:				str     =      fill.copy().set_fill(__a		,	opacity=0.7					)
								target.move_to(__a					)
								first_animations.append(GrowFromCenter(__a		,	run_time=1					)					)

								A_		:				str     =      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(__a		,	run_time=1.5					)					)

						self.play(*__a					)
						self.play(*__a					)
						self.wait()










"""simple docstring"""


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor
@require_vision
class   _UpperCamelCase  (   unittest.TestCase		):
							'''simple docstring'''







							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			tempfile.mkdtemp()

										__lowerCAmelCase				    =			[
										    "[UNK]",
										    "[CLS]",
										    "[SEP]",
										    "[PAD]",
										    "[MASK]",
										    "的",
										    "价",
										    "格",
										    "是",
										    "15",
										    "便",
										    "alex",
										    "##andra",
										    "，",
										    "。",
										    "-",
										    "t",
										    "shirt",
										]
										__lowerCAmelCase				    =			os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES["vocab_file"]	)
										with open(self.vocab_file    ,   "w"    ,   encoding="utf-8"	) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in vocab_tokens]	)	)

										__lowerCAmelCase				    =			{
										    "do_resize": True,
										    "size": {"height": 2_24, "width": 2_24},
										    "do_center_crop": True,
										    "crop_size": {"height": 18, "width": 18},
										    "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],
										    "do_convert_rgb": True,
										}
										__lowerCAmelCase				    =			os.path.join(self.tmpdirname    ,   __a	)
										with open(self.image_processor_file    ,   "w"    ,   encoding="utf-8"	) as fp:
													json.dump(__a    ,   __a	)

							def 			snake_case				(     self    ,   **__a	):
										return BertTokenizer.from_pretrained(self.tmpdirname    ,   **__a	)

							def 			snake_case				(     self    ,   **__a	):
										return BertTokenizerFast.from_pretrained(self.tmpdirname    ,   **__a	)

							def 			snake_case				(     self    ,   **__a	):
										return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname    ,   **__a	)

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			[np.random.randint(2_55    ,   size=(3, 30, 4_00)    ,   dtype=np.uinta	)]

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

										return image_inputs

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_tokenizer()
										__lowerCAmelCase				    =			self.get_rust_tokenizer()
										__lowerCAmelCase				    =			self.get_image_processor()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)
										processor_slow.save_pretrained(self.tmpdirname	)
										__lowerCAmelCase				    =			ChineseCLIPProcessor.from_pretrained(self.tmpdirname    ,   use_fast=__a	)

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)
										processor_fast.save_pretrained(self.tmpdirname	)
										__lowerCAmelCase				    =			ChineseCLIPProcessor.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 			snake_case				(     self	):
										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=self.get_tokenizer()    ,   image_processor=self.get_image_processor()	)
										processor.save_pretrained(self.tmpdirname	)

										__lowerCAmelCase				    =			self.get_tokenizer(cls_token="(CLS)"    ,   sep_token="(SEP)"	)
										__lowerCAmelCase				    =			self.get_image_processor(do_normalize=__a	)

										__lowerCAmelCase				    =			ChineseCLIPProcessor.from_pretrained(
										    self.tmpdirname    ,   cls_token="(CLS)"    ,   sep_token="(SEP)"    ,   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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			image_processor(__a    ,   return_tensors="np"	)
										__lowerCAmelCase				    =			processor(images=__a    ,   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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"

										__lowerCAmelCase				    =			processor(text=__a	)

										__lowerCAmelCase				    =			tokenizer(__a	)

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"
										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			processor(text=__a    ,   images=__a	)

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

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

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

										__lowerCAmelCase				    =			processor.batch_decode(__a	)
										__lowerCAmelCase				    =			tokenizer.batch_decode(__a	)

										self.assertListEqual(__a    ,   __a	)



							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"
										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			processor(text=__a    ,   images=__a	)

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




