


'''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


a_  :				Tuple						= """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)







'''simple docstring'''

import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class      snake_case    (    lowercase			,						unittest.TestCase			):





  """simple docstring"""




  _lowerCamelCase		    =  BlenderbotSmallTokenizer
  _lowerCamelCase		    =  False






  def   snake_case		(    self     ):







   """simple docstring"""
   super().setUp()

   lowerCamelCase_      =  ["__start__", "adapt", "act", "ap@@", "te", "__end__", "__unk__"]
   lowerCamelCase_      =  dict(zip(UpperCamelCase			,  range(len(UpperCamelCase     )     )     )     )

   lowerCamelCase_      =  ["#version: 0.2", "a p", "t e</w>", "ap t</w>", "a d", "ad apt</w>", "a c", "ac t</w>", ""]
   lowerCamelCase_      =  {"unk_token": "__unk__", "bos_token": "__start__", "eos_token": "__end__"}

   lowerCamelCase_      =  os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["vocab_file"]     )
   lowerCamelCase_      =  os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["merges_file"]     )
   with open(self.vocab_file			,  "w"			,  encoding="utf-8"     ) as fp:
    fp.write(json.dumps(UpperCamelCase     ) + "\n"     )
   with open(self.merges_file			,  "w"			,  encoding="utf-8"     ) as fp:
    fp.write("\n".join(UpperCamelCase     )     )






  def   snake_case		(    self			,  **UpperCamelCase     ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map     )
   return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname			,  **UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  "adapt act apte"
   lowerCamelCase_      =  "adapt act apte"
   return input_text, output_text






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer(self.vocab_file			,  self.merges_file			,  **self.special_tokens_map     )
   lowerCamelCase_      =  "adapt act apte"
   lowerCamelCase_      =  ["adapt", "act", "ap@@", "te"]
   lowerCamelCase_      =  tokenizer.tokenize(UpperCamelCase     )
   self.assertListEqual(UpperCamelCase			,  UpperCamelCase     )

   lowerCamelCase_      =  [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

   lowerCamelCase_      =  [0, 1, 2, 3, 4, 5]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase     )			,  UpperCamelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
   assert tok("sam"     ).input_ids == [1384]
   lowerCamelCase_      =  "I am a small frog."
   lowerCamelCase_      =  tok([src_text]			,  padding=UpperCamelCase			,  truncation=UpperCamelCase     )["input_ids"]
   lowerCamelCase_      =  tok.batch_decode(UpperCamelCase			,  skip_special_tokens=UpperCamelCase			,  clean_up_tokenization_spaces=UpperCamelCase     )[0]
   assert src_text != decoded  # I wish it did!
   assert decoded == "i am a small frog ."







  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
   lowerCamelCase_      =  "I am a small frog ."
   lowerCamelCase_      =  "."
   lowerCamelCase_      =  tok(UpperCamelCase     )["input_ids"]
   lowerCamelCase_      =  tok(UpperCamelCase     )["input_ids"]

   assert encoded[-1] == encoded_dot[0]



