


"""simple docstring"""



# Copyright 2022 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.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


__snake_case       =       """Run commands across TPU VMs for initial setup before running `accelerate launch`."""







def     __lowerCAmelCase		(		lowercase    :    int=None					)      ->		int:


    """simple docstring"""





    if subparsers is not None:
        snake_case       : Optional[int]    =       subparsers.add_parser("tpu-config"		,				description=_description					)
    else:
        snake_case       : int    =       argparse.ArgumentParser("Accelerate tpu-config command"		,				description=_description					)
    # Core arguments
    snake_case       : List[str]    =       parser.add_argument_group(
        "Config Arguments"		,				"Arguments that can be configured through `accelerate config`."					)
    config_args.add_argument(
        "--config_file"		,				type=lowercase		,				default=lowercase		,				help="Path to the config file to use for accelerate."		,				)
    config_args.add_argument(
        "--tpu_name"		,				default=lowercase		,				help="The name of the TPU to use. If not specified, will use the TPU specified in the config file."		,				)
    config_args.add_argument(
        "--tpu_zone"		,				default=lowercase		,				help="The zone of the TPU to use. If not specified, will use the zone specified in the config file."		,				)
    snake_case       : Any    =       parser.add_argument_group("TPU Arguments"		,				"Arguments for options ran inside the TPU."					)
    pod_args.add_argument(
        "--use_alpha"		,				action="store_true"		,				help="Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`."		,				)
    pod_args.add_argument(
        "--command_file"		,				default=lowercase		,				help="The path to the file containing the commands to run on the pod on startup."		,				)
    pod_args.add_argument(
        "--command"		,				action="append"		,				nargs="+"		,				help="A command to run on the pod. Can be passed multiple times."		,				)
    pod_args.add_argument(
        "--install_accelerate"		,				action="store_true"		,				help="Whether to install accelerate on the pod. Defaults to False."		,				)
    pod_args.add_argument(
        "--accelerate_version"		,				default="latest"		,				help="The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify 'dev' to install from GitHub."		,				)
    pod_args.add_argument(
        "--debug"		,				action="store_true"		,				help="If set, will print the command that would be run instead of running it."					)

    if subparsers is not None:
        parser.set_defaults(func=lowercase					)
    return parser







def     __lowerCAmelCase		(		lowercase    :    Optional[int]					)      ->		Optional[int]:


    """simple docstring"""





    snake_case       : int    =       None

    # Get the default from the config file if it exists.
    if args.config_file is not None or os.path.isfile(lowercase					):
        snake_case       : str    =       load_config_from_file(args.config_file					)
        if not args.command_file and defaults.command_file is not None and not args.command:
            snake_case       : Dict    =       defaults.command_file
        if not args.command and defaults.commands is not None:
            snake_case       : int    =       defaults.commands
        if not args.tpu_name:
            snake_case       : Union[str, Any]    =       defaults.tpu_name
        if not args.tpu_zone:
            snake_case       : str    =       defaults.tpu_zone
    if args.accelerate_version == "dev":
        snake_case       : Optional[Any]    =       "git+https://github.com/huggingface/accelerate.git"
    elif args.accelerate_version == "latest":
        snake_case       : Optional[int]    =       "accelerate -U"
    elif isinstance(parse(args.accelerate_version					)		,				lowercase					):
        snake_case       : int    =       F'accelerate=={args.accelerate_version}'

    if not args.command_file and not args.command:
        raise ValueError("You must specify either a command file or a command to run on the pod."					)

    if args.command_file:
        with open(args.command_file		,				"r"					) as f:
            snake_case       : int    =       [f.read().splitlines()]

    # To turn list of lists into list of strings
    if isinstance(args.command[0]		,				lowercase					):
        snake_case       : Optional[Any]    =       [line for cmd in args.command for line in cmd]
    # Default to the shared folder and install accelerate
    snake_case       : List[str]    =       ["cd /usr/share"]
    if args.install_accelerate:
        new_cmd += [F'pip install {args.accelerate_version}']
    new_cmd += args.command
    snake_case       : Optional[int]    =       "; ".join(lowercase					)

    # Then send it to gcloud
    # Eventually try to use google-api-core to do this instead of subprocess
    snake_case       : Optional[int]    =       ["gcloud"]
    if args.use_alpha:
        cmd += ["alpha"]
    cmd += [
        "compute",
        "tpus",
        "tpu-vm",
        "ssh",
        args.tpu_name,
        "--zone",
        args.tpu_zone,
        "--command",
        args.command,
        "--worker",
        "all",
    ]
    if args.debug:
        print(F'Running {" ".join(lowercase					)}'					)
        return
    subprocess.run(lowercase					)
    print("Successfully setup pod."					)







def     __lowerCAmelCase		(		)      ->		Any:


    """simple docstring"""





    snake_case       : Union[str, Any]    =       tpu_command_parser()
    snake_case       : List[Any]    =       parser.parse_args()

    tpu_command_launcher(lowercase					)









"""simple docstring"""



import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError

from transformers import (
    AlbertTokenizer,
    AutoTokenizer,
    BertTokenizer,
    BertTokenizerFast,
    GPTaTokenizerFast,
    is_tokenizers_available,
)
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers
from transformers.tokenization_utils import Trie


sys.path.append(str(Path(__file__).parent.parent / """utils"""))

from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
  from test_module.custom_tokenization_fast import CustomTokenizerFast







class _lowerCAmelCase							( unittest.TestCase      ):







   def 					lowerCamelCase						(      self		)      ->						str:

       '''simple docstring'''




       snake_case       : List[str]    =       mock.Mock()
       snake_case       : Any    =       500
       snake_case       : int    =       {}
       snake_case       : int    =       HTTPError
       snake_case       : Dict    =       {}

       # Download this model to make sure it's in the cache.
       snake_case       : Dict    =       BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"		)

       # Under the mock environment we get a 500 error when trying to reach the tokenizer.
       with mock.patch("requests.Session.request"		,      return_value=UpperCamelCase__		) as mock_head:
           snake_case       : str    =       BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"		)
           # This check we did call the fake head request
           mock_head.assert_called()







   @require_tokenizers
   def 					lowerCamelCase						(      self		)      ->						int:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       mock.Mock()
       snake_case       : int    =       500
       snake_case       : Optional[int]    =       {}
       snake_case       : int    =       HTTPError
       snake_case       : int    =       {}

       # Download this model to make sure it's in the cache.
       snake_case       : Any    =       GPTaTokenizerFast.from_pretrained("gpt2"		)

       # Under the mock environment we get a 500 error when trying to reach the tokenizer.
       with mock.patch("requests.Session.request"		,      return_value=UpperCamelCase__		) as mock_head:
           snake_case       : Tuple    =       GPTaTokenizerFast.from_pretrained("gpt2"		)
           # This check we did call the fake head request
           mock_head.assert_called()







   def 					lowerCamelCase						(      self		)      ->						List[str]:

       '''simple docstring'''




       try:
           snake_case       : Tuple    =       tempfile.mktemp()
           with open(UpperCamelCase__		,      "wb"		) as f:
               http_get("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"		,      UpperCamelCase__		)

           snake_case       : List[str]    =       AlbertTokenizer.from_pretrained(UpperCamelCase__		)
       finally:
           os.remove(UpperCamelCase__		)

       # Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in
       # the current folder and have the right name.
       if os.path.isfile("tokenizer.json"		):
           # We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it.
           return
       try:
           with open("tokenizer.json"		,      "wb"		) as f:
               http_get("https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json"		,      UpperCamelCase__		)
           snake_case       : Dict    =       AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2"		)
           # The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000
           self.assertEqual(tokenizer.vocab_size		,      1000		)
           # Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file.

       finally:
           os.remove("tokenizer.json"		)







   def 					lowerCamelCase						(      self		)      ->						Optional[Any]:

       '''simple docstring'''




       snake_case       : int    =       AlbertTokenizer.from_pretrained("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"		)







@is_staging_test
class _lowerCAmelCase							( unittest.TestCase      ):
   __UpperCAmelCase					:			Dict				    =    ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''bla''', '''blou''']







   @classmethod
   def 					lowerCamelCase						(      cls		)      ->						Optional[int]:

       '''simple docstring'''




       snake_case       : List[str]    =       TOKEN
       HfFolder.save_token(UpperCamelCase__		)







   @classmethod
   def 					lowerCamelCase						(      cls		)      ->						Union[str, Any]:

       '''simple docstring'''




       try:
           delete_repo(token=cls._token		,      repo_id="test-tokenizer"		)
       except HTTPError:
           pass

       try:
           delete_repo(token=cls._token		,      repo_id="valid_org/test-tokenizer-org"		)
       except HTTPError:
           pass

       try:
           delete_repo(token=cls._token		,      repo_id="test-dynamic-tokenizer"		)
       except HTTPError:
           pass







   def 					lowerCamelCase						(      self		)      ->						Dict:

       '''simple docstring'''




       with tempfile.TemporaryDirectory() as tmp_dir:
           snake_case       : Any    =       os.path.join(UpperCamelCase__		,      "vocab.txt"		)
           with open(UpperCamelCase__		,      "w"		,      encoding="utf-8"		) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]		)		)
           snake_case       : List[str]    =       BertTokenizer(UpperCamelCase__		)

       tokenizer.push_to_hub("test-tokenizer"		,      use_auth_token=self._token		)
       snake_case       : Dict    =       BertTokenizer.from_pretrained(F'{USER}/test-tokenizer'		)
       self.assertDictEqual(new_tokenizer.vocab		,      tokenizer.vocab		)

       # Reset repo
       delete_repo(token=self._token		,      repo_id="test-tokenizer"		)

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
           tokenizer.save_pretrained(UpperCamelCase__		,      repo_id="test-tokenizer"		,      push_to_hub=UpperCamelCase__		,      use_auth_token=self._token		)

       snake_case       : Dict    =       BertTokenizer.from_pretrained(F'{USER}/test-tokenizer'		)
       self.assertDictEqual(new_tokenizer.vocab		,      tokenizer.vocab		)







   def 					lowerCamelCase						(      self		)      ->						Any:

       '''simple docstring'''




       with tempfile.TemporaryDirectory() as tmp_dir:
           snake_case       : Dict    =       os.path.join(UpperCamelCase__		,      "vocab.txt"		)
           with open(UpperCamelCase__		,      "w"		,      encoding="utf-8"		) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]		)		)
           snake_case       : Optional[int]    =       BertTokenizer(UpperCamelCase__		)

       tokenizer.push_to_hub("valid_org/test-tokenizer-org"		,      use_auth_token=self._token		)
       snake_case       : Dict    =       BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"		)
       self.assertDictEqual(new_tokenizer.vocab		,      tokenizer.vocab		)

       # Reset repo
       delete_repo(token=self._token		,      repo_id="valid_org/test-tokenizer-org"		)

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
           tokenizer.save_pretrained(
               UpperCamelCase__		,      repo_id="valid_org/test-tokenizer-org"		,      push_to_hub=UpperCamelCase__		,      use_auth_token=self._token		)

       snake_case       : Optional[int]    =       BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"		)
       self.assertDictEqual(new_tokenizer.vocab		,      tokenizer.vocab		)







   @require_tokenizers
   def 					lowerCamelCase						(      self		)      ->						Union[str, Any]:

       '''simple docstring'''




       CustomTokenizer.register_for_auto_class()
       with tempfile.TemporaryDirectory() as tmp_dir:
           snake_case       : Tuple    =       os.path.join(UpperCamelCase__		,      "vocab.txt"		)
           with open(UpperCamelCase__		,      "w"		,      encoding="utf-8"		) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]		)		)
           snake_case       : Any    =       CustomTokenizer(UpperCamelCase__		)

       # No fast custom tokenizer
       tokenizer.push_to_hub("test-dynamic-tokenizer"		,      use_auth_token=self._token		)

       snake_case       : Union[str, Any]    =       AutoTokenizer.from_pretrained(F'{USER}/test-dynamic-tokenizer'		,      trust_remote_code=UpperCamelCase__		)
       # Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
       self.assertEqual(tokenizer.__class__.__name__		,      "CustomTokenizer"		)

       # Fast and slow custom tokenizer
       CustomTokenizerFast.register_for_auto_class()
       with tempfile.TemporaryDirectory() as tmp_dir:
           snake_case       : int    =       os.path.join(UpperCamelCase__		,      "vocab.txt"		)
           with open(UpperCamelCase__		,      "w"		,      encoding="utf-8"		) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]		)		)

           snake_case       : Optional[Any]    =       BertTokenizerFast.from_pretrained(UpperCamelCase__		)
           bert_tokenizer.save_pretrained(UpperCamelCase__		)
           snake_case       : List[Any]    =       CustomTokenizerFast.from_pretrained(UpperCamelCase__		)

       tokenizer.push_to_hub("test-dynamic-tokenizer"		,      use_auth_token=self._token		)

       snake_case       : Union[str, Any]    =       AutoTokenizer.from_pretrained(F'{USER}/test-dynamic-tokenizer'		,      trust_remote_code=UpperCamelCase__		)
       # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
       self.assertEqual(tokenizer.__class__.__name__		,      "CustomTokenizerFast"		)
       snake_case       : Optional[Any]    =       AutoTokenizer.from_pretrained(
           F'{USER}/test-dynamic-tokenizer'		,      use_fast=UpperCamelCase__		,      trust_remote_code=UpperCamelCase__		)
       # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
       self.assertEqual(tokenizer.__class__.__name__		,      "CustomTokenizer"		)







class _lowerCAmelCase							( unittest.TestCase      ):







   def 					lowerCamelCase						(      self		)      ->						str:

       '''simple docstring'''




       snake_case       : Any    =       Trie()
       trie.add("Hello 友達"		)
       self.assertEqual(trie.data		,      {"H": {"e": {"l": {"l": {"o": {" ": {"友": {"達": {"": 1}}}}}}}}}		)
       trie.add("Hello"		)
       trie.data
       self.assertEqual(trie.data		,      {"H": {"e": {"l": {"l": {"o": {"": 1, " ": {"友": {"達": {"": 1}}}}}}}}}		)







   def 					lowerCamelCase						(      self		)      ->						Any:

       '''simple docstring'''




       snake_case       : Tuple    =       Trie()
       self.assertEqual(trie.split("[CLS] This is a extra_id_100"		)		,      ["[CLS] This is a extra_id_100"]		)
       trie.add("[CLS]"		)
       trie.add("extra_id_1"		)
       trie.add("extra_id_100"		)
       self.assertEqual(trie.split("[CLS] This is a extra_id_100"		)		,      ["[CLS]", " This is a ", "extra_id_100"]		)







   def 					lowerCamelCase						(      self		)      ->						List[str]:

       '''simple docstring'''




       snake_case       : str    =       Trie()
       trie.add("A"		)
       self.assertEqual(trie.split("ABC"		)		,      ["A", "BC"]		)
       self.assertEqual(trie.split("BCA"		)		,      ["BC", "A"]		)







   def 					lowerCamelCase						(      self		)      ->						int:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       Trie()
       trie.add("TOKEN]"		)
       trie.add("[SPECIAL_TOKEN]"		)
       self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"		)		,      ["This is something ", "[SPECIAL_TOKEN]"]		)







   def 					lowerCamelCase						(      self		)      ->						Tuple:

       '''simple docstring'''




       snake_case       : Optional[int]    =       Trie()
       trie.add("A"		)
       trie.add("P"		)
       trie.add("[SPECIAL_TOKEN]"		)
       self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"		)		,      ["This is something ", "[SPECIAL_TOKEN]"]		)







   def 					lowerCamelCase						(      self		)      ->						List[str]:

       '''simple docstring'''




       snake_case       : List[Any]    =       Trie()
       trie.add("AB"		)
       trie.add("B"		)
       trie.add("C"		)
       self.assertEqual(trie.split("ABC"		)		,      ["AB", "C"]		)







   def 					lowerCamelCase						(      self		)      ->						Dict:

       '''simple docstring'''




       snake_case       : str    =       Trie()
       trie.add("ABC"		)
       trie.add("B"		)
       trie.add("CD"		)
       self.assertEqual(trie.split("ABCD"		)		,      ["ABC", "D"]		)







   def 					lowerCamelCase						(      self		)      ->						Optional[Any]:

       '''simple docstring'''




       snake_case       : Optional[int]    =       Trie()
       snake_case       : Union[str, Any]    =       trie.cut_text("ABC"		,      [0, 0, 2, 1, 2, 3]		)
       self.assertEqual(UpperCamelCase__		,      ["AB", "C"]		)





