


'''simple docstring'''







import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


snake_case_       :    Optional[Any]          =					logging.get_logger(__name__)  # pylint: disable=invalid-name


snake_case_       :    str          =					"lfs-multipart-upload"


class    __a (_a       ):

							@staticmethod
							def       UpperCAmelCase__		(							__magic_name__							:       ArgumentParser				)   ->    Tuple:







													"""simple docstring"""
													UpperCAmelCase_     : str         =					parser.add_parser(
													    '''lfs-enable-largefiles'''    ,       help=(
													        '''Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'''
													    )    ,       )
													enable_parser.add_argument('''path'''    ,       type=SCREAMING_SNAKE_CASE__    ,       help='''Local path to repository you want to configure.'''				)
													enable_parser.set_defaults(func=lambda __magic_name__				: LfsEnableCommand(SCREAMING_SNAKE_CASE__				)				)

													UpperCAmelCase_     : Optional[int]         =					parser.add_parser(
													    SCREAMING_SNAKE_CASE__    ,       help=(
													        '''Deprecated: use `huggingface-cli` instead. '''
													        '''Command will get called by git-lfs, do not call it directly.'''
													    )    ,       )
													upload_parser.set_defaults(func=lambda __magic_name__				: LfsUploadCommand(SCREAMING_SNAKE_CASE__				)				)





class    __a :

							def __init__(							self							:       Any    ,       __magic_name__							:       Tuple				)   ->    Optional[int]:







													"""simple docstring"""
													UpperCAmelCase_     : Tuple         =					args



							def       UpperCAmelCase__		(							self							:       Dict				)   ->    Dict:







													"""simple docstring"""
													warnings.warn(
													    '''Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'''				)
													UpperCAmelCase_     : Optional[Any]         =					os.path.abspath(self.args.path				)
													if not os.path.isdir(SCREAMING_SNAKE_CASE__				):
																			print('''This does not look like a valid git repo.'''				)
																			exit(1				)
													subprocess.run(
													    '''git config lfs.customtransfer.multipart.path transformers-cli'''.split()    ,       check=SCREAMING_SNAKE_CASE__    ,       cwd=SCREAMING_SNAKE_CASE__				)
													subprocess.run(
													    F"""git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}""".split()    ,       check=SCREAMING_SNAKE_CASE__    ,       cwd=SCREAMING_SNAKE_CASE__    ,       )
													print('''Local repo set up for largefiles'''				)





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     str				)	->		List[Any]:
						UpperCAmelCase_     : str         =					json.dumps(SCREAMING_SNAKE_CASE__				) + "\n"
						sys.stdout.write(SCREAMING_SNAKE_CASE__				)
						sys.stdout.flush()





def     lowerCamelCase_ (					)	->		Tuple:
						UpperCAmelCase_     : Union[str, Any]         =					json.loads(sys.stdin.readline().strip()				)

						if "terminate" in (msg.get('''type'''				), msg.get('''event'''				)):
												# terminate message received
												return None

						if msg.get('''event'''				) not in ("download", "upload"):
												logger.critical('''Received unexpected message'''				)
												sys.exit(1				)

						return msg


class    __a (_a       ):

							def __init__(							self							:       Optional[int]    ,       __magic_name__							:       str    ,       __magic_name__							:       int    ,       __magic_name__							:       int				)   ->    Dict:







													"""simple docstring"""
													UpperCAmelCase_     : Optional[Any]         =					filepath
													UpperCAmelCase_     : Optional[int]         =					seek_from
													UpperCAmelCase_     : List[str]         =					read_limit
													UpperCAmelCase_     : List[Any]         =					0

							def __enter__(							self							:       List[str]				)   ->    List[Any]:







													"""simple docstring"""
													UpperCAmelCase_     : Any         =					open(self.filepath    ,       '''rb'''				)
													self.f.seek(self.seek_from				)
													return self

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







													"""simple docstring"""
													UpperCAmelCase_     : List[str]         =					os.fstat(self.f.fileno()				).st_size
													return min(self.read_limit    ,       total_length - self.seek_from				)

							def       UpperCAmelCase__		(							self							:       int    ,       __magic_name__							:       List[str]=-1				)   ->    List[Any]:







													"""simple docstring"""
													if self.n_seen >= self.read_limit:
																			return b""
													UpperCAmelCase_     : Tuple         =					self.read_limit - self.n_seen
													UpperCAmelCase_     : Tuple         =					self.f.read(remaining_amount if n < 0 else min(SCREAMING_SNAKE_CASE__    ,       SCREAMING_SNAKE_CASE__				)				)
													self.n_seen += len(SCREAMING_SNAKE_CASE__				)
													return data

							def __iter__(							self							:       Optional[int]				)   ->    Optional[Any]:







													"""simple docstring"""
													yield self.read(n=4 * 10_24 * 10_24				)



							def __exit__(							self							:       List[str]    ,       *__magic_name__							:       Dict				)   ->    str:







													"""simple docstring"""
													self.f.close()





class    __a :

							def __init__(							self							:       Union[str, Any]    ,       __magic_name__							:       List[str]				)   ->    List[Any]:







													"""simple docstring"""
													UpperCAmelCase_     : List[Any]         =					args



							def       UpperCAmelCase__		(							self							:       List[str]				)   ->    Tuple:







													"""simple docstring"""
													# Immediately after invoking a custom transfer process, git-lfs
													# sends initiation data to the process over stdin.
													# This tells the process useful information about the configuration.
													UpperCAmelCase_     : List[str]         =					json.loads(sys.stdin.readline().strip()				)
													if not (init_msg.get('''event'''				) == "init" and init_msg.get('''operation'''				) == "upload"):
																			write_msg({'''error''': {'''code''': 32, '''message''': '''Wrong lfs init operation'''}}				)
																			sys.exit(1				)

													# The transfer process should use the information it needs from the
													# initiation structure, and also perform any one-off setup tasks it
													# needs to do. It should then respond on stdout with a simple empty
													# confirmation structure, as follows:
													write_msg({}				)

													# After the initiation exchange, git-lfs will send any number of
													# transfer requests to the stdin of the transfer process, in a serial sequence.
													while True:
																			UpperCAmelCase_     : Optional[Any]         =					read_msg()
																			if msg is None:
																									# When all transfers have been processed, git-lfs will send
																									# a terminate event to the stdin of the transfer process.
																									# On receiving this message the transfer process should
																									# clean up and terminate. No response is expected.
																									sys.exit(0				)

																			UpperCAmelCase_     : Dict         =					msg["oid"]
																			UpperCAmelCase_     : Union[str, Any]         =					msg["path"]
																			UpperCAmelCase_     : List[str]         =					msg["action"]["href"]
																			UpperCAmelCase_     : Union[str, Any]         =					msg["action"]["header"]
																			UpperCAmelCase_     : int         =					int(header.pop('''chunk_size'''				)				)
																			UpperCAmelCase_     : List[str]         =					list(header.values()				)

																			UpperCAmelCase_     : Tuple         =					[]
																			for i, presigned_url in enumerate(SCREAMING_SNAKE_CASE__				):
																									with FileSlice(SCREAMING_SNAKE_CASE__    ,       seek_from=i * chunk_size    ,       read_limit=SCREAMING_SNAKE_CASE__				) as data:
																															UpperCAmelCase_     : Optional[Any]         =					requests.put(SCREAMING_SNAKE_CASE__    ,       data=SCREAMING_SNAKE_CASE__				)
																															r.raise_for_status()
																															parts.append(
																															    {
																															        '''etag''': r.headers.get('''etag'''				),
																															        '''partNumber''': i + 1,
																															    }				)
																															# In order to support progress reporting while data is uploading / downloading,
																															# the transfer process should post messages to stdout
																															write_msg(
																															    {
																															        '''event''': '''progress''',
																															        '''oid''': oid,
																															        '''bytesSoFar''': (i + 1) * chunk_size,
																															        '''bytesSinceLast''': chunk_size,
																															    }				)
																															# Not precise but that's ok.

																			UpperCAmelCase_     : Dict         =					requests.post(
																			    SCREAMING_SNAKE_CASE__    ,       json={
																			        '''oid''': oid,
																			        '''parts''': parts,
																			    }    ,       )
																			r.raise_for_status()

																			write_msg({'''event''': '''complete''', '''oid''': oid}				)












'''simple docstring'''







from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput


class    __a (lowerCamelCase       ):
							__a   :				UNetaDModel
							__a   :				PNDMScheduler

							def __init__(							self							:       Optional[Any]    ,       __magic_name__							:       UNetaDModel    ,       __magic_name__							:       PNDMScheduler				)   ->    Tuple:







													"""simple docstring"""
													super().__init__()

													UpperCAmelCase_     : Optional[int]         =					PNDMScheduler.from_config(scheduler.config				)

													self.register_modules(unet=__magic_name__    ,       scheduler=__magic_name__				)



							@torch.no_grad()
							def __call__(							self							:       Union[str, Any]    ,       __magic_name__							:       int = 1    ,       __magic_name__							:       int = 50    ,       __magic_name__							:       Optional[Union[torch.Generator, List[torch.Generator]]] = None    ,       __magic_name__							:       Optional[str] = "pil"    ,       __magic_name__							:       bool = True    ,       **__magic_name__							:       Dict    ,       )   ->    Union[ImagePipelineOutput, Tuple]:







													"""simple docstring"""
													UpperCAmelCase_     : Dict         =					randn_tensor(
													    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)    ,       generator=__magic_name__    ,       device=self.device    ,       )

													self.scheduler.set_timesteps(__magic_name__				)
													for t in self.progress_bar(self.scheduler.timesteps				):
																			UpperCAmelCase_     : Optional[int]         =					self.unet(__magic_name__    ,       __magic_name__				).sample

																			UpperCAmelCase_     : str         =					self.scheduler.step(__magic_name__    ,       __magic_name__    ,       __magic_name__				).prev_sample

													UpperCAmelCase_     : int         =					(image / 2 + 0.5).clamp(0    ,       1				)
													UpperCAmelCase_     : Any         =					image.cpu().permute(0    ,       2    ,       3    ,       1				).numpy()
													if output_type == "pil":
																			UpperCAmelCase_     : Optional[int]         =					self.numpy_to_pil(__magic_name__				)

													if not return_dict:
																			return (image,)

													return ImagePipelineOutput(images=__magic_name__				)





