
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


lowerCamelCase__     :		Any        = """Create a default config file for Accelerate with only a few flags set."""

def 		UpperCamelCase						(   lowercase_="no"			,			lowercase_ = default_json_config_file			,			lowercase_ = False )		->						Any:


  '''simple docstring'''






  lowercase__	: Any     		=   Path(lowercase_ )
  path.parent.mkdir(parents=lowercase_			,			exist_ok=lowercase_ )
  if path.exists():
    print(
        F'Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.' )
    return False
  lowercase__	: int     		=   mixed_precision.lower()
  if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
    raise ValueError(
        F'`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}' )
  lowercase__	: Dict     		=   {
      """compute_environment""": """LOCAL_MACHINE""",
      """mixed_precision""": mixed_precision,
  }
  if torch.cuda.is_available():
    lowercase__	: Any     		=   torch.cuda.device_count()
    lowercase__	: Any     		=   num_gpus
    lowercase__	: Optional[int]     		=   False
    if num_gpus > 1:
      lowercase__	: Tuple     		=   """MULTI_GPU"""
    else:
      lowercase__	: Optional[Any]     		=   """NO"""
  elif is_xpu_available() and use_xpu:
    lowercase__	: Union[str, Any]     		=   torch.xpu.device_count()
    lowercase__	: str     		=   num_xpus
    lowercase__	: List[Any]     		=   False
    if num_xpus > 1:
      lowercase__	: str     		=   """MULTI_XPU"""
    else:
      lowercase__	: Optional[Any]     		=   """NO"""
  elif is_npu_available():
    lowercase__	: Tuple     		=   torch.npu.device_count()
    lowercase__	: Union[str, Any]     		=   num_npus
    lowercase__	: Union[str, Any]     		=   False
    if num_npus > 1:
      lowercase__	: List[Any]     		=   """MULTI_NPU"""
    else:
      lowercase__	: int     		=   """NO"""
  else:
    lowercase__	: Union[str, Any]     		=   0
    lowercase__	: str     		=   True
    lowercase__	: Union[str, Any]     		=   1
    lowercase__	: int     		=   """NO"""
  lowercase__	: Tuple     		=   ClusterConfig(**lowercase_ )
  config.to_json_file(lowercase_ )
  return path

def 		UpperCamelCase						(   lowercase_			,			lowercase_ )		->						Optional[Any]:


  '''simple docstring'''






  lowercase__	: List[str]     		=   parser.add_parser("""default"""			,			parents=lowercase_			,			help=lowercase_			,			formatter_class=lowercase_ )
  parser.add_argument(
      """--config_file"""			,			default=lowercase_			,			help=(
          """The path to use to store the config file. Will default to a file named default_config.yaml in the cache """
          """location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have """
          """such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed """
          """with 'huggingface'."""
      )			,			dest="""save_location"""			,			)

  parser.add_argument(
      """--mixed_precision"""			,			choices=["""no""", """fp16""", """bf16"""]			,			type=lowercase_			,			help="""Whether or not to use mixed precision training. """
      """Choose between FP16 and BF16 (bfloat16) training. """
      """BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later."""			,			default="""no"""			,			)
  parser.set_defaults(func=lowercase_ )
  return parser



def 		UpperCamelCase						(   lowercase_ )		->						Any:


  '''simple docstring'''






  lowercase__	: Optional[Any]     		=   write_basic_config(args.mixed_precision			,			args.save_location )
  if config_file:
    print(F'accelerate configuration saved at {config_file}' )








from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase__     :		List[Any]        = logging.get_logger(__name__)

lowerCamelCase__     :		Union[str, Any]        = {
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Union[str, Any]	   =      'convbert'


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=3_05_22       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=30_72       ,	SCREAMING_SNAKE_CASE_="gelu"       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=5_12       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=1E-12       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=0       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=9       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=None       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   super().__init__(
       pad_token_id=SCREAMING_SNAKE_CASE_       ,	bos_token_id=SCREAMING_SNAKE_CASE_       ,	eos_token_id=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_       ,	)

   lowercase__	: Dict     		=   vocab_size
   lowercase__	: List[Any]     		=   hidden_size
   lowercase__	: Optional[Any]     		=   num_hidden_layers
   lowercase__	: Union[str, Any]     		=   num_attention_heads
   lowercase__	: List[str]     		=   intermediate_size
   lowercase__	: Optional[int]     		=   hidden_act
   lowercase__	: Tuple     		=   hidden_dropout_prob
   lowercase__	: List[str]     		=   attention_probs_dropout_prob
   lowercase__	: Tuple     		=   max_position_embeddings
   lowercase__	: Dict     		=   type_vocab_size
   lowercase__	: Union[str, Any]     		=   initializer_range
   lowercase__	: Dict     		=   layer_norm_eps
   lowercase__	: Tuple     		=   embedding_size
   lowercase__	: List[str]     		=   head_ratio
   lowercase__	: Dict     		=   conv_kernel_size
   lowercase__	: Dict     		=   num_groups
   lowercase__	: int     		=   classifier_dropout



class    _snake_case (						UpperCAmelCase_				):


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   if self.task == "multiple-choice":
     lowercase__	: Union[str, Any]     		=   {0: """batch""", 1: """choice""", 2: """sequence"""}
   else:
     lowercase__	: str     		=   {0: """batch""", 1: """sequence"""}
   return OrderedDict(
       [
           ("""input_ids""", dynamic_axis),
           ("""attention_mask""", dynamic_axis),
           ("""token_type_ids""", dynamic_axis),
       ])






