


'''simple docstring'''

import argparse
import os
import re

import packaging.version


_UpperCAmelCase				: Union[str, Any]							    =				"""examples/"""
_UpperCAmelCase				: Dict							    =				{
    """examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
    """init""": (re.compile(r"""^__version__\s+=\s+\"([^\"]+)\"\s*$""", re.MULTILINE), """__version__ = \"VERSION\"\n"""),
    """setup""": (re.compile(r"""^(\s*)version\s*=\s*\"[^\"]+\",""", re.MULTILINE), r"""\1version=\"VERSION\","""),
    """doc""": (re.compile(r"""^(\s*)release\s*=\s*\"[^\"]+\"$""", re.MULTILINE), """release = \"VERSION\"\n"""),
}
_UpperCAmelCase				: Union[str, Any]							    =				{
    """init""": """src/diffusers/__init__.py""",
    """setup""": """setup.py""",
}
_UpperCAmelCase				: int							    =				"""README.md"""

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase,				lowerCamelCase):
						with open(lowerCamelCase,				'''r''',				encoding='''utf-8''',				newline='''\n''') as f:
												__lowerCAmelCase							       =				f.read()
						__lowerCAmelCase       ,					__lowerCAmelCase							       =				REPLACE_PATTERNS[pattern]
						__lowerCAmelCase							       =				replace.replace('''VERSION''',				lowerCamelCase)
						__lowerCAmelCase							       =				re_pattern.sub(lowerCamelCase,				lowerCamelCase)
						with open(lowerCamelCase,				'''w''',				encoding='''utf-8''',				newline='''\n''') as f:
												f.write(lowerCamelCase)

def 							__magic_name__(						lowerCamelCase):
						for folder, directories, fnames in os.walk(lowerCamelCase):
												# Removing some of the folders with non-actively maintained examples from the walk
												if "research_projects" in directories:
																		directories.remove('''research_projects''')
												if "legacy" in directories:
																		directories.remove('''legacy''')
												for fname in fnames:
																		if fname.endswith('''.py'''):
																								update_version_in_file(os.path.join(lowerCamelCase,				lowerCamelCase),				lowerCamelCase,				pattern='''examples''')

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase=False):
						for pattern, fname in REPLACE_FILES.items():
												update_version_in_file(lowerCamelCase,				lowerCamelCase,				lowerCamelCase)
						if not patch:
												update_version_in_examples(lowerCamelCase)

def 							__magic_name__(						):
						__lowerCAmelCase							       =				'''🤗 Transformers currently provides the following architectures'''
						__lowerCAmelCase							       =				'''1. Want to contribute a new model?'''
						with open(lowerCamelCase,				'''r''',				encoding='''utf-8''',				newline='''\n''') as f:
												__lowerCAmelCase							       =				f.readlines()

						# Find the start of the list.
						__lowerCAmelCase							       =				0
						while not lines[start_index].startswith(_start_prompt):
												start_index += 1
						start_index += 1

						__lowerCAmelCase							       =				start_index
						# Update the lines in the model list.
						while not lines[index].startswith(_end_prompt):
												if lines[index].startswith('''1.'''):
																		__lowerCAmelCase							       =				lines[index].replace(
																		    '''https://huggingface.co/docs/diffusers/main/model_doc''',				'''https://huggingface.co/docs/diffusers/model_doc''',				)
												index += 1

						with open(lowerCamelCase,				'''w''',				encoding='''utf-8''',				newline='''\n''') as f:
												f.writelines(lowerCamelCase)

def 							__magic_name__(						):
						with open(REPLACE_FILES['''init'''],				'''r''') as f:
												__lowerCAmelCase							       =				f.read()
						__lowerCAmelCase							       =				REPLACE_PATTERNS['''init'''][0].search(lowerCamelCase).groups()[0]
						return packaging.version.parse(lowerCamelCase)

def 							__magic_name__(						lowerCamelCase=False):
						__lowerCAmelCase							       =				get_version()
						if patch and default_version.is_devrelease:
												raise ValueError('''Can\'t create a patch version from the dev branch, checkout a released version!''')
						if default_version.is_devrelease:
												__lowerCAmelCase							       =				default_version.base_version
						elif patch:
												__lowerCAmelCase							       =				F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
						else:
												__lowerCAmelCase							       =				F"""{default_version.major}.{default_version.minor + 1}.0"""

						# Now let's ask nicely if that's the right one.
						__lowerCAmelCase							       =				input(F"""Which version are you releasing? [{default_version}]""")
						if len(lowerCamelCase) == 0:
												__lowerCAmelCase							       =				default_version

						print(F"""Updating version to {version}.""")
						global_version_update(lowerCamelCase,				patch=lowerCamelCase)

def 							__magic_name__(						):
						__lowerCAmelCase							       =				get_version()
						__lowerCAmelCase							       =				F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
						__lowerCAmelCase							       =				current_version.base_version

						# Check with the user we got that right.
						__lowerCAmelCase							       =				input(F"""Which version are we developing now? [{dev_version}]""")
						if len(lowerCamelCase) == 0:
												__lowerCAmelCase							       =				dev_version

						print(F"""Updating version to {version}.""")
						global_version_update(lowerCamelCase)


#    print("Cleaning main README, don't forget to run `make fix-copies`.")
#    clean_main_ref_in_model_list()


if __name__ == "__main__":
	_UpperCAmelCase				: Dict							    =				argparse.ArgumentParser()
	parser.add_argument("""--post_release""", action="""store_true""", help="""Whether this is pre or post release.""")
	parser.add_argument("""--patch""", action="""store_true""", help="""Whether or not this is a patch release.""")
	_UpperCAmelCase				: List[Any]							    =				parser.parse_args()
	if not args.post_release:
		pre_release_work(patch=args.patch)
	elif args.patch:
		print("""Nothing to do after a patch :-)""")
	else:
		post_release_work()





'''simple docstring'''

import argparse
import re

import torch
from CLAP import create_model

from transformers import AutoFeatureExtractor, ClapConfig, ClapModel


_UpperCAmelCase				: str							    =				{
    """text_branch""": """text_model""",
    """audio_branch""": """audio_model.audio_encoder""",
    """attn""": """attention.self""",
    """self.proj""": """output.dense""",
    """attention.self_mask""": """attn_mask""",
    """mlp.fc1""": """intermediate.dense""",
    """mlp.fc2""": """output.dense""",
    """norm1""": """layernorm_before""",
    """norm2""": """layernorm_after""",
    """bn0""": """batch_norm""",
}

_UpperCAmelCase				: Optional[int]							    =				AutoFeatureExtractor.from_pretrained("""laion/clap-htsat-unfused""", truncation="""rand_trunc""")

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase=False):
						__lowerCAmelCase       ,					__lowerCAmelCase							       =				create_model(
						    '''HTSAT-tiny''',				'''roberta''',				lowerCamelCase,				precision='''fp32''',				device='''cuda:0''' if torch.cuda.is_available() else '''cpu''',				enable_fusion=lowerCamelCase,				fusion_type='''aff_2d''' if enable_fusion else None,				)
						return model, model_cfg

def 							__magic_name__(						lowerCamelCase):
						__lowerCAmelCase							       =				{}

						__lowerCAmelCase							       =				r'''.*sequential.(\d+).*'''
						__lowerCAmelCase							       =				r'''.*_projection.(\d+).*'''

						for key, value in state_dict.items():
												# check if any key needs to be modified
												for key_to_modify, new_key in KEYS_TO_MODIFY_MAPPING.items():
																		if key_to_modify in key:
																								__lowerCAmelCase							       =				key.replace(lowerCamelCase,				lowerCamelCase)

												if re.match(lowerCamelCase,				lowerCamelCase):
																		# replace sequential layers with list
																		__lowerCAmelCase							       =				re.match(lowerCamelCase,				lowerCamelCase).group(1)

																		__lowerCAmelCase							       =				key.replace(F"""sequential.{sequential_layer}.""",				F"""layers.{int(lowerCamelCase)//3}.linear.""")
												elif re.match(lowerCamelCase,				lowerCamelCase):
																		__lowerCAmelCase							       =				int(re.match(lowerCamelCase,				lowerCamelCase).group(1))

																		# Because in CLAP they use `nn.Sequential`...
																		__lowerCAmelCase							       =				1 if projecton_layer == 0 else 2

																		__lowerCAmelCase							       =				key.replace(F"""_projection.{projecton_layer}.""",				F"""_projection.linear{transformers_projection_layer}.""")

												if "audio" and "qkv" in key:
																		# split qkv into query key and value
																		__lowerCAmelCase							       =				value
																		__lowerCAmelCase							       =				mixed_qkv.size(0) // 3

																		__lowerCAmelCase							       =				mixed_qkv[:qkv_dim]
																		__lowerCAmelCase							       =				mixed_qkv[qkv_dim : qkv_dim * 2]
																		__lowerCAmelCase							       =				mixed_qkv[qkv_dim * 2 :]

																		__lowerCAmelCase							       =				query_layer
																		__lowerCAmelCase							       =				key_layer
																		__lowerCAmelCase							       =				value_layer
												else:
																		__lowerCAmelCase							       =				value

						return model_state_dict

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase,				lowerCamelCase,				lowerCamelCase=False):
						__lowerCAmelCase       ,					__lowerCAmelCase							       =				init_clap(lowerCamelCase,				enable_fusion=lowerCamelCase)

						clap_model.eval()
						__lowerCAmelCase							       =				clap_model.state_dict()
						__lowerCAmelCase							       =				rename_state_dict(lowerCamelCase)

						__lowerCAmelCase							       =				ClapConfig()
						__lowerCAmelCase							       =				enable_fusion
						__lowerCAmelCase							       =				ClapModel(lowerCamelCase)

						# ignore the spectrogram embedding layer
						model.load_state_dict(lowerCamelCase,				strict=lowerCamelCase)

						model.save_pretrained(lowerCamelCase)
						transformers_config.save_pretrained(lowerCamelCase)


if __name__ == "__main__":
	_UpperCAmelCase				: 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 fairseq checkpoint""")
	parser.add_argument("""--config_path""", default=None, type=str, help="""Path to hf config.json of model to convert""")
	parser.add_argument("""--enable_fusion""", action="""store_true""", help="""Whether to enable fusion or not""")
	_UpperCAmelCase				: Optional[int]							    =				parser.parse_args()

	convert_clap_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path, args.enable_fusion)

