


'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


a_  :				Dict						= logging.get_logger(__name__)

a_  :				str						= {
    """facebook/xlm-roberta-xl""": """https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json""",
    """facebook/xlm-roberta-xxl""": """https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json""",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}





class      snake_case    (    SCREAMING_SNAKE_CASE_			):





  """simple docstring"""




  _lowerCamelCase		    =  '''xlm-roberta-xl'''






  def __init__(    self			,  UpperCamelCase=25_0880			,  UpperCamelCase=2560			,  UpperCamelCase=36			,  UpperCamelCase=32			,  UpperCamelCase=1_0240			,  UpperCamelCase="gelu"			,  UpperCamelCase=0.1			,  UpperCamelCase=0.1			,  UpperCamelCase=514			,  UpperCamelCase=1			,  UpperCamelCase=0.02			,  UpperCamelCase=1e-05			,  UpperCamelCase=1			,  UpperCamelCase=0			,  UpperCamelCase=2			,  UpperCamelCase="absolute"			,  UpperCamelCase=True			,  UpperCamelCase=None			,  **UpperCamelCase			,  ):







   """simple docstring"""
   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





class      snake_case    (    SCREAMING_SNAKE_CASE_			):





  """simple docstring"""




  @property
  def   snake_case		(    self     ):







   """simple docstring"""
   if self.task == "multiple-choice":
    lowerCamelCase_      =  {0: """batch""", 1: """choice""", 2: """sequence"""}
   else:
    lowerCamelCase_      =  {0: """batch""", 1: """sequence"""}
   return OrderedDict(
       [
           ("input_ids", dynamic_axis),
           ("attention_mask", dynamic_axis),
       ]     )








'''simple docstring'''





# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


_lowerCAmelCase      						=	'''3'''

print('''Python version:''', sys.version)
print('''transformers version:''', transformers.__version__)

try:
 import torch

 print('''Torch version:''', torch.__version__)
 print('''Cuda available:''', torch.cuda.is_available())
 print('''Cuda version:''', torch.version.cuda)
 print('''CuDNN version:''', torch.backends.cudnn.version())
 print('''Number of GPUs available:''', torch.cuda.device_count())
 print('''NCCL version:''', torch.cuda.nccl.version())
except ImportError:
 print('''Torch version:''', None)

try:
 import deepspeed

 print('''DeepSpeed version:''', deepspeed.__version__)
except ImportError:
 print('''DeepSpeed version:''', None)

try:
 import tensorflow as tf

 print('''TensorFlow version:''', tf.__version__)
 print('''TF GPUs available:''', bool(tf.config.list_physical_devices('''GPU''')))
 print('''Number of TF GPUs available:''', len(tf.config.list_physical_devices('''GPU''')))
except ImportError:
 print('''TensorFlow version:''', None)


