import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig




def 	A_ (							snake_case							:   int ,      snake_case							:   int ,      snake_case							:   List[str] ,      snake_case							:   str )      ->    Tuple:



						'''simple docstring'''

						__UpperCamelCase       =			s.rsplit(__lowerCAmelCase ,      __lowerCAmelCase )
						return new.join(__lowerCAmelCase )




def 	A_ (							snake_case							:   Optional[int] )      ->    Dict:



						'''simple docstring'''

						return sum(param.float().sum() if '''encoder.embeddings''' not in key else 0 for key, param in state_dict.items() )




def 	A_ (							snake_case							:   List[str] )      ->    Any:



						'''simple docstring'''

						__UpperCamelCase       =			{}

						__UpperCamelCase       =			["""group_1""", """group_2""", """group_3""", """group_4"""]
						for key, value in state_dict.items():
												for group_key in group_keys:
																		if group_key in key:
																								__UpperCamelCase       =			key.replace(f"{group_key}." ,      f"{group_key}.group." )

												if "res_path" in key:
																		__UpperCamelCase       =			key.replace('''res_path.''' ,      '''res_path.path.''' )

												if key.endswith('''.w''' ):
																		__UpperCamelCase       =			rreplace(__lowerCAmelCase ,      '''.w''' ,      '''.weight''' ,      1 )
												if key.endswith('''.b''' ):
																		__UpperCamelCase       =			rreplace(__lowerCAmelCase ,      '''.b''' ,      '''.bias''' ,      1 )

												__UpperCamelCase       =			value.float()

						return upgrade




@torch.no_grad()
def 	A_ (							snake_case							:   List[str] ,      snake_case							:   Any ,      snake_case							:   Tuple=None ,      snake_case							:   Union[str, Any]=True )      ->    List[str]:



						'''simple docstring'''

						from dall_e import Encoder

						__UpperCamelCase       =			Encoder()
						if os.path.exists(__lowerCAmelCase ):
												__UpperCamelCase       =			torch.load(__lowerCAmelCase )
						else:
												__UpperCamelCase       =			torch.hub.load_state_dict_from_url(__lowerCAmelCase )

						if isinstance(__lowerCAmelCase ,      __lowerCAmelCase ):
												__UpperCamelCase       =			ckpt.state_dict()
						encoder.load_state_dict(__lowerCAmelCase )

						if config_path is not None:
												__UpperCamelCase       =			FlavaImageCodebookConfig.from_pretrained(__lowerCAmelCase )
						else:
												__UpperCamelCase       =			FlavaImageCodebookConfig()

						__UpperCamelCase       =			FlavaImageCodebook(__lowerCAmelCase ).eval()
						__UpperCamelCase       =			encoder.state_dict()

						__UpperCamelCase       =			upgrade_state_dict(__lowerCAmelCase )
						hf_model.load_state_dict(__lowerCAmelCase )
						__UpperCamelCase       =			hf_model.state_dict()
						__UpperCamelCase       =			count_parameters(__lowerCAmelCase )
						__UpperCamelCase       =			count_parameters(__lowerCAmelCase )

						assert torch.allclose(__lowerCAmelCase ,      __lowerCAmelCase ,      atol=1e-3 )

						if save_checkpoint:
												hf_model.save_pretrained(__lowerCAmelCase )
						else:
												return hf_state_dict


if __name__ == "__main__":
				lowercase__							:							Any									=			argparse.ArgumentParser()
				parser.add_argument("--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model.")
				parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to flava checkpoint")
				parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
				lowercase__							:							List[Any]									=			parser.parse_args()

				convert_dalle_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path)






import os
import re
import shutil
import sys
import tempfile
import unittest

import black


lowercase__							:							Optional[Any]									=			os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
lowercase__							:							Dict									=			"    \"\"\"\n    Output class for the scheduler's step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"\"\"\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n"






class        SCREAMING_SNAKE_CASE__    (							unittest.TestCase    ):

							"""simple docstring"""






							def     A__		(  self			)->   Dict:





													'''simple docstring'''






													__UpperCamelCase       =			tempfile.mkdtemp()
													os.makedirs(os.path.join(self.diffusers_dir     ,	'''schedulers/'''			)			)
													__UpperCamelCase       =			self.diffusers_dir
													shutil.copy(
													    os.path.join(SCREAMING_SNAKE_CASE_     ,	'''src/diffusers/schedulers/scheduling_ddpm.py'''			)     ,	os.path.join(self.diffusers_dir     ,	'''schedulers/scheduling_ddpm.py'''			)     ,	)



							def     A__		(  self			)->   Optional[int]:





													'''simple docstring'''






													__UpperCamelCase       =			'''src/diffusers'''
													shutil.rmtree(self.diffusers_dir			)



							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_=None			)->   Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			comment + F"\nclass {class_name}(nn.Module):\n" + class_code
													if overwrite_result is not None:
																			__UpperCamelCase       =			comment + F"\nclass {class_name}(nn.Module):\n" + overwrite_result
													__UpperCamelCase       =			black.Mode(target_versions={black.TargetVersion.PYaa}     ,	line_length=119			)
													__UpperCamelCase       =			black.format_str(SCREAMING_SNAKE_CASE_     ,	mode=SCREAMING_SNAKE_CASE_			)
													__UpperCamelCase       =			os.path.join(self.diffusers_dir     ,	'''new_code.py'''			)
													with open(SCREAMING_SNAKE_CASE_     ,	'''w'''     ,	newline='''\n'''			) as f:
																			f.write(SCREAMING_SNAKE_CASE_			)
													if overwrite_result is None:
																			self.assertTrue(len(check_copies.is_copy_consistent(SCREAMING_SNAKE_CASE_			)			) == 0			)
													else:
																			check_copies.is_copy_consistent(f.name     ,	overwrite=SCREAMING_SNAKE_CASE_			)
																			with open(SCREAMING_SNAKE_CASE_     ,	'''r'''			) as f:
																									self.assertTrue(f.read()     ,	SCREAMING_SNAKE_CASE_			)



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





													'''simple docstring'''






													__UpperCamelCase       =			check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''			)
													self.assertEqual(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_			)



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





													'''simple docstring'''






													self.check_copy_consistency(
													    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''     ,	'''DDPMSchedulerOutput'''     ,	REFERENCE_CODE + '''\n'''     ,	)

													# With no empty line at the end
													self.check_copy_consistency(
													    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput'''     ,	'''DDPMSchedulerOutput'''     ,	SCREAMING_SNAKE_CASE_     ,	)

													# Copy consistency with rename
													self.check_copy_consistency(
													    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''     ,	'''TestSchedulerOutput'''     ,	re.sub('''DDPM'''     ,	'''Test'''     ,	SCREAMING_SNAKE_CASE_			)     ,	)

													# Copy consistency with a really long name
													__UpperCamelCase       =			'''TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
													self.check_copy_consistency(
													    F"# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}"     ,	F"{long_class_name}SchedulerOutput"     ,	re.sub('''Bert'''     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_			)     ,	)

													# Copy consistency with overwrite
													self.check_copy_consistency(
													    '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test'''     ,	'''TestSchedulerOutput'''     ,	SCREAMING_SNAKE_CASE_     ,	overwrite_result=re.sub('''DDPM'''     ,	'''Test'''     ,	SCREAMING_SNAKE_CASE_			)     ,	)




