






import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida

from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingface_hub.utils import (
    EntryNotFoundError,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    is_jinja_available,
)
from packaging import version
from requests import HTTPError

from .. import __version__
from .constants import (
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    SAFETENSORS_WEIGHTS_NAME,
    WEIGHTS_NAME,
)
from .import_utils import (
    ENV_VARS_TRUE_VALUES,
    _flax_version,
    _jax_version,
    _onnxruntime_version,
    _torch_version,
    is_flax_available,
    is_onnx_available,
    is_torch_available,
)
from .logging import get_logger


lowerCamelCase			:					Optional[Any]          =	get_logger(__name__)


lowerCamelCase			:					Union[str, Any]          =	Path(__file__).parent / '''model_card_template.md'''
lowerCamelCase			:					Any          =	uuida().hex
lowerCamelCase			:					str          =	os.getenv('''HF_HUB_OFFLINE''', '''''').upper() in ENV_VARS_TRUE_VALUES
lowerCamelCase			:					Any          =	os.getenv('''DISABLE_TELEMETRY''', '''''').upper() in ENV_VARS_TRUE_VALUES
lowerCamelCase			:					Optional[Any]          =	HUGGINGFACE_CO_RESOLVE_ENDPOINT + '''/api/telemetry/'''





def       __lowerCAmelCase      (						__snake_case = None       ):
     __lowerCAmelCase								=					F"""diffusers/{__version__}; python/{sys.version.split()[0]}; session_id/{SESSION_ID}"""
     if DISABLE_TELEMETRY or HF_HUB_OFFLINE:
          return ua + "; telemetry/off"
     if is_torch_available():
          ua += F"""; torch/{_torch_version}"""
     if is_flax_available():
          ua += F"""; jax/{_jax_version}"""
          ua += F"""; flax/{_flax_version}"""
     if is_onnx_available():
          ua += F"""; onnxruntime/{_onnxruntime_version}"""
     # CI will set this value to True
     if os.environ.get("DIFFUSERS_IS_CI"					, ""       ).upper() in ENV_VARS_TRUE_VALUES:
          ua += "; is_ci/true"
     if isinstance(__snake_case					, __snake_case       ):
          ua += "; " + "; ".join(F"""{k}/{v}""" for k, v in user_agent.items()       )
     elif isinstance(__snake_case					, __snake_case       ):
          ua += "; " + user_agent
     return ua





def       __lowerCAmelCase      (						__snake_case					, __snake_case = None					, __snake_case = None       ):
     if token is None:
          __lowerCAmelCase								=					HfFolder.get_token()
     if organization is None:
          __lowerCAmelCase								=					whoami(__snake_case       )["name"]
          return F"""{username}/{model_id}"""
     else:
          return F"""{organization}/{model_id}"""





def       __lowerCAmelCase      (						__snake_case					, __snake_case       ):
     if not is_jinja_available():
          raise ValueError(
              "Modelcard rendering is based on Jinja templates."
              " Please make sure to have `jinja` installed before using `create_model_card`."
              " To install it, please run `pip install Jinja2`."       )

     if hasattr(__snake_case					, "local_rank"       ) and args.local_rank not in [-1, 0]:
          return

     __lowerCAmelCase								=					args.hub_token if hasattr(__snake_case					, "hub_token"       ) else None
     __lowerCAmelCase								=					get_full_repo_name(__snake_case					, token=__snake_case       )

     __lowerCAmelCase								=					ModelCard.from_template(
         card_data=ModelCardData(  # Card metadata object that will be converted to YAML block
             language="en"					, license="apache-2.0"					, library_name="diffusers"					, tags=[]					, datasets=args.dataset_name					, metrics=[]					, )					, template_path=__snake_case					, model_name=__snake_case					, repo_name=__snake_case					, dataset_name=args.dataset_name if hasattr(__snake_case					, "dataset_name"       ) else None					, learning_rate=args.learning_rate					, train_batch_size=args.train_batch_size					, eval_batch_size=args.eval_batch_size					, gradient_accumulation_steps=(
             args.gradient_accumulation_steps if hasattr(__snake_case					, "gradient_accumulation_steps"       ) else None
         )					, adam_betaa=args.adam_betaa if hasattr(__snake_case					, "adam_beta1"       ) else None					, adam_betaa=args.adam_betaa if hasattr(__snake_case					, "adam_beta2"       ) else None					, adam_weight_decay=args.adam_weight_decay if hasattr(__snake_case					, "adam_weight_decay"       ) else None					, adam_epsilon=args.adam_epsilon if hasattr(__snake_case					, "adam_epsilon"       ) else None					, lr_scheduler=args.lr_scheduler if hasattr(__snake_case					, "lr_scheduler"       ) else None					, lr_warmup_steps=args.lr_warmup_steps if hasattr(__snake_case					, "lr_warmup_steps"       ) else None					, ema_inv_gamma=args.ema_inv_gamma if hasattr(__snake_case					, "ema_inv_gamma"       ) else None					, ema_power=args.ema_power if hasattr(__snake_case					, "ema_power"       ) else None					, ema_max_decay=args.ema_max_decay if hasattr(__snake_case					, "ema_max_decay"       ) else None					, mixed_precision=args.mixed_precision					, )

     __lowerCAmelCase								=					os.path.join(args.output_dir					, "README.md"       )
     model_card.save(__snake_case       )





def       __lowerCAmelCase      (						__snake_case					, __snake_case = None       ):
     if resolved_file is None or commit_hash is not None:
          return commit_hash
     __lowerCAmelCase								=					str(Path(__snake_case       ).as_posix()       )
     __lowerCAmelCase								=					re.search(r"snapshots/([^/]+)/"					, __snake_case       )
     if search is None:
          return None
     __lowerCAmelCase								=					search.groups()[0]
     return commit_hash if REGEX_COMMIT_HASH.match(__snake_case       ) else None


# Old default cache path, potentially to be migrated.
# This logic was more or less taken from `transformers`, with the following differences:
# - Diffusers doesn't use custom environment variables to specify the cache path.
# - There is no need to migrate the cache format, just move the files to the new location.
lowerCamelCase			:					List[str]          =	os.path.expanduser(
    os.getenv('''HF_HOME''', os.path.join(os.getenv('''XDG_CACHE_HOME''', '''~/.cache'''), '''huggingface'''))
)
lowerCamelCase			:					Optional[Any]          =	os.path.join(hf_cache_home, '''diffusers''')





def       __lowerCAmelCase      (						__snake_case = None					, __snake_case = None       ):
     if new_cache_dir is None:
          __lowerCAmelCase								=					DIFFUSERS_CACHE
     if old_cache_dir is None:
          __lowerCAmelCase								=					old_diffusers_cache

     __lowerCAmelCase								=					Path(__snake_case       ).expanduser()
     __lowerCAmelCase								=					Path(__snake_case       ).expanduser()
     for old_blob_path in old_cache_dir.glob("**/blobs/*"       ):
          if old_blob_path.is_file() and not old_blob_path.is_symlink():
               __lowerCAmelCase								=					new_cache_dir / old_blob_path.relative_to(__snake_case       )
               new_blob_path.parent.mkdir(parents=__snake_case					, exist_ok=__snake_case       )
               os.replace(__snake_case					, __snake_case       )
               try:
                    os.symlink(__snake_case					, __snake_case       )
               except OSError:
                    logger.warning(
                        "Could not create symlink between old cache and new cache. If you use an older version of diffusers again, files will be re-downloaded."       )
     # At this point, old_cache_dir contains symlinks to the new cache (it can still be used).


lowerCamelCase			:					Tuple          =	os.path.join(DIFFUSERS_CACHE, '''version_diffusers_cache.txt''')
if not os.path.isfile(cache_version_file):
 lowerCamelCase			:					Dict          =	0
else:
 with open(cache_version_file) as f:
  try:
   lowerCamelCase			:					Union[str, Any]          =	int(f.read())
  except ValueError:
   lowerCamelCase			:					Any          =	0

if cache_version < 1:
 lowerCamelCase			:					int          =	os.path.isdir(old_diffusers_cache) and len(os.listdir(old_diffusers_cache)) > 0
 if old_cache_is_not_empty:
  logger.warning(
      '''The cache for model files in Diffusers v0.14.0 has moved to a new location. Moving your '''
      '''existing cached models. This is a one-time operation, you can interrupt it or run it '''
      '''later by calling `diffusers.utils.hub_utils.move_cache()`.'''
  )
  try:
   move_cache()
  except Exception as e:
   lowerCamelCase			:					Tuple          =	'''\n'''.join(traceback.format_tb(e.__traceback__))
   logger.error(
       F'''There was a problem when trying to move your cache:\n\n{trace}\n{e.__class__.__name__}: {e}\n\nPlease '''
       '''file an issue at https://github.com/huggingface/diffusers/issues/new/choose, copy paste this whole '''
       '''message and we will do our best to help.'''
   )

if cache_version < 1:
 try:
  os.makedirs(DIFFUSERS_CACHE, exist_ok=True)
  with open(cache_version_file, '''w''') as f:
   f.write('''1''')
 except Exception:
  logger.warning(
      F'''There was a problem when trying to write in your cache folder ({DIFFUSERS_CACHE}). Please, ensure '''
      '''the directory exists and can be written to.'''
  )





def       __lowerCAmelCase      (						__snake_case					, __snake_case = None       ):
     if variant is not None:
          __lowerCAmelCase								=					weights_name.split("."       )
          __lowerCAmelCase								=					splits[:-1] + [variant] + splits[-1:]
          __lowerCAmelCase								=					".".join(__snake_case       )

     return weights_name





def       __lowerCAmelCase      (						__snake_case					, *,
    __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case					, __snake_case=None					, ):
     __lowerCAmelCase								=					str(__snake_case       )
     if os.path.isfile(__snake_case       ):
          return pretrained_model_name_or_path
     elif os.path.isdir(__snake_case       ):
          if os.path.isfile(os.path.join(__snake_case					, __snake_case       )       ):
               # Load from a PyTorch checkpoint
               __lowerCAmelCase								=					os.path.join(__snake_case					, __snake_case       )
               return model_file
          elif subfolder is not None and os.path.isfile(
              os.path.join(__snake_case					, __snake_case					, __snake_case       )       ):
               __lowerCAmelCase								=					os.path.join(__snake_case					, __snake_case					, __snake_case       )
               return model_file
          else:
               raise EnvironmentError(
                   F"""Error no file named {weights_name} found in directory {pretrained_model_name_or_path}."""       )
     else:
          # 1. First check if deprecated way of loading from branches is used
          if (
              revision in DEPRECATED_REVISION_ARGS
              and (weights_name == WEIGHTS_NAME or weights_name == SAFETENSORS_WEIGHTS_NAME)
              and version.parse(version.parse(__snake_case       ).base_version       ) >= version.parse("0.20.0"       )
          ):
               try:
                    __lowerCAmelCase								=					hf_hub_download(
                        __snake_case					, filename=_add_variant(__snake_case					, __snake_case       )					, cache_dir=__snake_case					, force_download=__snake_case					, proxies=__snake_case					, resume_download=__snake_case					, local_files_only=__snake_case					, use_auth_token=__snake_case					, user_agent=__snake_case					, subfolder=__snake_case					, revision=revision or commit_hash					, )
                    warnings.warn(
                        F"""Loading the variant {revision} from {pretrained_model_name_or_path} via `revision='{revision}'` is deprecated. Loading instead from `revision='main'` with `variant={revision}`. Loading model variants via `revision='{revision}'` will be removed in diffusers v1. Please use `variant='{revision}'` instead."""					, __snake_case					, )
                    return model_file
               except:  # noqa: E722
                    warnings.warn(
                        F"""You are loading the variant {revision} from {pretrained_model_name_or_path} via `revision='{revision}'`. This behavior is deprecated and will be removed in diffusers v1. One should use `variant='{revision}'` instead. However, it appears that {pretrained_model_name_or_path} currently does not have a {_add_variant(__snake_case					, __snake_case       )} file in the 'main' branch of {pretrained_model_name_or_path}. \n The Diffusers team and community would be very grateful if you could open an issue: https://github.com/huggingface/diffusers/issues/new with the title '{pretrained_model_name_or_path} is missing {_add_variant(__snake_case					, __snake_case       )}' so that the correct variant file can be added."""					, __snake_case					, )
          try:
               # 2. Load model file as usual
               __lowerCAmelCase								=					hf_hub_download(
                   __snake_case					, filename=__snake_case					, cache_dir=__snake_case					, force_download=__snake_case					, proxies=__snake_case					, resume_download=__snake_case					, local_files_only=__snake_case					, use_auth_token=__snake_case					, user_agent=__snake_case					, subfolder=__snake_case					, revision=revision or commit_hash					, )
               return model_file

          except RepositoryNotFoundError:
               raise EnvironmentError(
                   F"""{pretrained_model_name_or_path} is not a local folder and is not a valid model identifier """
                   "listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to pass a "
                   "token having permission to this repo with `use_auth_token` or log in with `huggingface-cli "
                   "login`."       )
          except RevisionNotFoundError:
               raise EnvironmentError(
                   F"""{revision} is not a valid git identifier (branch name, tag name or commit id) that exists for """
                   "this model name. Check the model page at "
                   F"""'https://huggingface.co/{pretrained_model_name_or_path}' for available revisions."""       )
          except EntryNotFoundError:
               raise EnvironmentError(
                   F"""{pretrained_model_name_or_path} does not appear to have a file named {weights_name}."""       )
          except HTTPError as err:
               raise EnvironmentError(
                   F"""There was a specific connection error when trying to load {pretrained_model_name_or_path}:\n{err}"""       )
          except ValueError:
               raise EnvironmentError(
                   F"""We couldn't connect to '{HUGGINGFACE_CO_RESOLVE_ENDPOINT}' to load this model, couldn't find it"""
                   F""" in the cached files and it looks like {pretrained_model_name_or_path} is not the path to a"""
                   F""" directory containing a file named {weights_name} or"""
                   " \nCheckout your internet connection or see how to run the library in"
                   " offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'."       )
          except EnvironmentError:
               raise EnvironmentError(
                   F"""Can't load the model for '{pretrained_model_name_or_path}'. If you were trying to load it from """
                   "'https://huggingface.co/models', make sure you don't have a local directory with the same name. "
                   F"""Otherwise, make sure '{pretrained_model_name_or_path}' is the correct path to a directory """
                   F"""containing a file named {weights_name}"""       )














from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase			:					Any         =	logging.get_logger(__name__)

lowerCamelCase			:					Dict         =	{
    '''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json''',
    '''microsoft/markuplm-large''': '''https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json''',
}



class 							_UpperCamelCase			(a_			):
      snake_case_  =							"""markuplm"""


      def __init__(	self					,						__UpperCamelCase=3_0_5_2_2					,						__UpperCamelCase=7_6_8					,						__UpperCamelCase=1_2					,						__UpperCamelCase=1_2					,						__UpperCamelCase=3_0_7_2					,						__UpperCamelCase="gelu"					,						__UpperCamelCase=0.1					,						__UpperCamelCase=0.1					,						__UpperCamelCase=5_1_2					,						__UpperCamelCase=2					,						__UpperCamelCase=0.0_2					,						__UpperCamelCase=1e-12					,						__UpperCamelCase=0					,						__UpperCamelCase=0					,						__UpperCamelCase=2					,						__UpperCamelCase=2_5_6					,						__UpperCamelCase=1_0_2_4					,						__UpperCamelCase=2_1_6					,						__UpperCamelCase=1_0_0_1					,						__UpperCamelCase=3_2					,						__UpperCamelCase=5_0					,						__UpperCamelCase="absolute"					,						__UpperCamelCase=True					,						__UpperCamelCase=None					,						**__UpperCamelCase					,						)->	Dict:
           super().__init__(
               pad_token_id=__UpperCamelCase					,						bos_token_id=__UpperCamelCase					,						eos_token_id=__UpperCamelCase					,						**__UpperCamelCase					,						)
           __lowerCAmelCase								=					vocab_size
           __lowerCAmelCase								=					hidden_size
           __lowerCAmelCase								=					num_hidden_layers
           __lowerCAmelCase								=					num_attention_heads
           __lowerCAmelCase								=					hidden_act
           __lowerCAmelCase								=					intermediate_size
           __lowerCAmelCase								=					hidden_dropout_prob
           __lowerCAmelCase								=					attention_probs_dropout_prob
           __lowerCAmelCase								=					max_position_embeddings
           __lowerCAmelCase								=					type_vocab_size
           __lowerCAmelCase								=					initializer_range
           __lowerCAmelCase								=					layer_norm_eps
           __lowerCAmelCase								=					position_embedding_type
           __lowerCAmelCase								=					use_cache
           __lowerCAmelCase								=					classifier_dropout
           # additional properties
           __lowerCAmelCase								=					max_depth
           __lowerCAmelCase								=					max_xpath_tag_unit_embeddings
           __lowerCAmelCase								=					max_xpath_subs_unit_embeddings
           __lowerCAmelCase								=					tag_pad_id
           __lowerCAmelCase								=					subs_pad_id
           __lowerCAmelCase								=					xpath_unit_hidden_size






