






import importlib

import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=False						)->    Dict:



			"""simple docstring"""



			snake_case_				:					Any   =       OmegaConf.load(__magic_name__						)
			if display:
						print(yaml.dump(OmegaConf.to_container(__magic_name__						)						)						)
			return config

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=None     ,__magic_name__=None						)->    List[str]:



			"""simple docstring"""



			if conf_path is None:
						snake_case_				:					str   =       "./model_checkpoints/vqgan_only.yaml"
			snake_case_				:					List[Any]   =       load_config(__magic_name__     ,display=__magic_name__						)
			snake_case_				:					Dict   =       VQModel(**config.model.params						)
			if ckpt_path is None:
						snake_case_				:					Union[str, Any]   =       "./model_checkpoints/vqgan_only.pt"
			snake_case_				:					Optional[Any]   =       torch.load(__magic_name__     ,map_location=__magic_name__						)
			if ".ckpt" in ckpt_path:
						snake_case_				:					Optional[int]   =       sd["state_dict"]
			model.load_state_dict(__magic_name__     ,strict=__magic_name__						)
			model.to(__magic_name__						)
			del sd
			return model

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					Tuple   =       model.encode(__magic_name__						)
			print(F'''VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}'''						)
			snake_case_				:					List[Any]   =       model.decode(__magic_name__						)
			return xrec

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=False						)->    List[Any]:



			"""simple docstring"""



			snake_case_				:					List[str]   =       string.rsplit("."     ,1						)
			if reload:
						snake_case_				:					Dict   =       importlib.import_module(__magic_name__						)
						importlib.reload(__magic_name__						)
			return getattr(importlib.import_module(__magic_name__     ,package=__magic_name__						)     ,cls						)

def 	__UpperCAmelCase       ( __magic_name__						)->    Tuple:



			"""simple docstring"""



			if "target" not in config:
						raise KeyError("Expected key `target` to instantiate."						)
			return get_obj_from_str(config["target"]						)(**config.get("params"     ,{}						)						)

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__=True     ,__magic_name__=True						)->    Optional[int]:



			"""simple docstring"""



			snake_case_				:					Any   =       instantiate_from_config(__magic_name__						)
			if sd is not None:
						model.load_state_dict(__magic_name__						)
			if gpu:
						model.cuda()
			if eval_mode:
						model.eval()
			return {"model": model}






def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__     ,__magic_name__						)->    str:



			"""simple docstring"""



			if ckpt:
						snake_case_				:					Any   =       torch.load(__magic_name__     ,map_location="cpu"						)
						snake_case_				:					Any   =       pl_sd["global_step"]
						print(F'''loaded model from global step {global_step}.'''						)
			else:
						snake_case_				:					List[str]   =       {"state_dict": None}
						snake_case_				:					List[Any]   =       None
			snake_case_				:					str   =       load_model_from_config(config.model     ,pl_sd["state_dict"]     ,gpu=__magic_name__     ,eval_mode=__magic_name__						)["model"]
			return model, global_step












'''simple docstring'''




import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class    A_	(a_						,					unittest.TestCase							):
							"""simple docstring"""




							a__   		=	MgpstrTokenizer
							a__   		=	False
							a__   		=	{}
							a__   		=	False

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


										'''simple docstring'''




										super().setUp()

										# fmt: off
										snake_case_				:					Dict   =       ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
										# fmt: on
										snake_case_				:					List[str]   =       dict(zip(lowerCAmelCase__       ,							range(len(lowerCAmelCase__				)				)				)				)

										snake_case_				:					Tuple   =       os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES["vocab_file"]				)
										with open(self.vocab_file       ,							"w"       ,							encoding="utf-8"				) as fp:
													fp.write(json.dumps(lowerCAmelCase__				) + "\n"				)

							def 							_A	(		self			:Optional[Any]       ,							**lowerCAmelCase__			:Optional[Any]				)				->  Dict:


										'''simple docstring'''




										return MgpstrTokenizer.from_pretrained(self.tmpdirname       ,							**lowerCAmelCase__				)

							def 							_A	(		self			:Dict       ,							lowerCAmelCase__			:Any				)				->  str:


										'''simple docstring'''




										snake_case_				:					Dict   =       "tester"
										snake_case_				:					Tuple   =       "tester"
										return input_text, output_text

							@unittest.skip("MGP-STR always lower cases letters."				)
							def 							_A	(		self			:Dict				)				->  str:


										'''simple docstring'''




										pass

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


										'''simple docstring'''




										snake_case_				:					List[str]   =       self.get_tokenizers(do_lower_case=lowerCAmelCase__				)
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
																snake_case_				:					Tuple   =       "[SPECIAL_TOKEN]"

																tokenizer.add_special_tokens({"cls_token": special_token}				)
																snake_case_				:					str   =       tokenizer.encode([special_token]       ,							add_special_tokens=lowerCAmelCase__				)
																self.assertEqual(len(lowerCAmelCase__				)       ,							1				)

																snake_case_				:					Tuple   =       tokenizer.decode(lowerCAmelCase__       ,							skip_special_tokens=lowerCAmelCase__				)
																self.assertTrue(special_token not in decoded				)

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


										'''simple docstring'''




										snake_case_				:					Dict   =       self.get_tokenizers()
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
																snake_case_,	snake_case_				:					str   =       self.get_input_output_texts(lowerCAmelCase__				)

																snake_case_				:					Union[str, Any]   =       tokenizer.tokenize(lowerCAmelCase__				)
																snake_case_				:					List[Any]   =       tokenizer.convert_tokens_to_ids(lowerCAmelCase__				)
																snake_case_				:					Dict   =       tokenizer.encode(lowerCAmelCase__       ,							add_special_tokens=lowerCAmelCase__				)
																self.assertListEqual(lowerCAmelCase__       ,							lowerCAmelCase__				)

																snake_case_				:					List[str]   =       tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
																self.assertNotEqual(len(lowerCAmelCase__				)       ,							0				)
																snake_case_				:					List[str]   =       tokenizer.decode(lowerCAmelCase__				)
																self.assertIsInstance(lowerCAmelCase__       ,							lowerCAmelCase__				)

																self.assertEqual(text_a.replace(" "       ,							""				)       ,							lowerCAmelCase__				)

							@unittest.skip("MGP-STR tokenizer only handles one sequence."				)
							def 							_A	(		self			:Union[str, Any]				)				->  Any:


										'''simple docstring'''




										pass






							@unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"				)
							def 							_A	(		self			:int				)				->  Dict:


										'''simple docstring'''




										pass




