
'''simple docstring'''







import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin


class 			lowerCAmelCase (				__UpperCAmelCase		,						unittest.TestCase			):
		a							:					Tuple       =					TransfoXLTokenizer
		a							:					str       =					False
		a							:					List[Any]       =					False




		def     lowercase       (				self      ):
								super().setUp()

								_SCREAMING_SNAKE_CASE				= [
								    "<unk>",
								    "[CLS]",
								    "[SEP]",
								    "want",
								    "unwanted",
								    "wa",
								    "un",
								    "running",
								    ",",
								    "low",
								    "l",
								]
								_SCREAMING_SNAKE_CASE				= os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES["vocab_file"]      )
								with open(self.vocab_file					,						"w"					,						encoding="utf-8"      ) as vocab_writer:
														vocab_writer.write("".join([x + "\n" for x in vocab_tokens]      )      )




		def     lowercase       (				self					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= True
								return TransfoXLTokenizer.from_pretrained(self.tmpdirname					,						**UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= "<unk> UNwanted , running"
								_SCREAMING_SNAKE_CASE				= "<unk> unwanted, running"
								return input_text, output_text




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= TransfoXLTokenizer(vocab_file=self.vocab_file					,						lower_case=UpperCamelCase      )

								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize("<unk> UNwanted , running"      )
								self.assertListEqual(UpperCamelCase					,						["<unk>", "unwanted", ",", "running"]      )

								self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase      )					,						[0, 4, 8, 7]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= TransfoXLTokenizer(lower_case=UpperCamelCase      )

								self.assertListEqual(
								    tokenizer.tokenize(" \tHeLLo ! how  \n Are yoU ?  "      )					,						["hello", "!", "how", "are", "you", "?"]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= TransfoXLTokenizer(lower_case=UpperCamelCase      )

								self.assertListEqual(
								    tokenizer.tokenize(" \tHeLLo ! how  \n Are yoU ?  "      )					,						["HeLLo", "!", "how", "Are", "yoU", "?"]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= TransfoXLTokenizer(lower_case=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= "Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"
								_SCREAMING_SNAKE_CASE				= [
								    "Hello",
								    "(",
								    "bracket",
								    ")",
								    "and",
								    "side",
								    "@-@",
								    "scrolled",
								    "[",
								    "and",
								    "]",
								    "Henry",
								    "'s",
								    "$",
								    "5",
								    "@,@",
								    "000",
								    "with",
								    "3",
								    "@.@",
								    "34",
								    "m",
								    ".",
								    "What",
								    "'s",
								    "up",
								    "!",
								    "?",
								]

								self.assertListEqual(tokenizer.tokenize(UpperCamelCase      )					,						UpperCamelCase      )

								self.assertEqual(tokenizer.convert_tokens_to_string(UpperCamelCase      )					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.get_tokenizer()
								_SCREAMING_SNAKE_CASE				= len(UpperCamelCase      )

								tokenizer.add_tokens(["new1", "new2"]      )
								tokenizer.move_added_token("new1"					,						1      )

								# Check that moved token is not copied (duplicate)
								self.assertEqual(len(UpperCamelCase      )					,						original_len + 2      )
								# Check that token is moved to specified id
								self.assertEqual(tokenizer.encode("new1"      )					,						[1]      )
								self.assertEqual(tokenizer.decode([1]      )					,						"new1"      )

'''simple docstring'''







import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								if isinstance(UpperCamelCase					,						UpperCamelCase      ):
														# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
														# modified it, it will not be accepted here again, since `auto` values would have been overridden
														_SCREAMING_SNAKE_CASE				= deepcopy(UpperCamelCase      )
								elif os.path.exists(UpperCamelCase      ):
														with io.open(UpperCamelCase					,						"r"					,						encoding="utf-8"      ) as f:
																				_SCREAMING_SNAKE_CASE				= json.load(UpperCamelCase      )
								else:
														try:
																				_SCREAMING_SNAKE_CASE				= baseaa.urlsafe_baadecode(UpperCamelCase      ).decode("utf-8"      )
																				_SCREAMING_SNAKE_CASE				= json.loads(UpperCamelCase      )
														except (UnicodeDecodeError, AttributeError, ValueError):
																				raise ValueError(
																				    F'Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}'      )

								_SCREAMING_SNAKE_CASE				= config

								self.set_stage_and_offload()




		def     lowercase       (				self      ):
								# zero stage - this is done as early as possible, before model is created, to allow
								# ``is_deepspeed_zero3_enabled`` query and getting to the early deepspeed config object
								# during ``zero.Init()`` which needs to know the dtype, and some other hparams.
								_SCREAMING_SNAKE_CASE				= self.get_value("zero_optimization.stage"					,						-1      )

								# offload
								_SCREAMING_SNAKE_CASE				= False
								if self.is_zeroa() or self.is_zeroa():
														_SCREAMING_SNAKE_CASE				= set(["cpu", "nvme"]      )
														_SCREAMING_SNAKE_CASE				= set(
														    [
														        self.get_value("zero_optimization.offload_optimizer.device"      ),
														        self.get_value("zero_optimization.offload_param.device"      ),
														    ]      )
														if len(offload_devices & offload_devices_valid      ) > 0:
																				_SCREAMING_SNAKE_CASE				= True




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								_SCREAMING_SNAKE_CASE				= nodes.pop()
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				return None, ds_key

								return config, ds_key




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=None      ):
								_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= self.find_config_node(UpperCamelCase      )
								if config is None:
														return default
								return config.get(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=False      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				if must_exist:
																										raise ValueError(F'Can\'t find {ds_key_long} entry in the config: {self.config}'      )
																				else:
																										return

        # if found remove it
								if parent_config is not None:
														parent_config.pop(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else bool(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else not bool(UpperCamelCase      )




		def     lowercase       (				self      ):
								return self._stage == 2




		def     lowercase       (				self      ):
								return self._stage == 3




		def     lowercase       (				self      ):
								return self._offload


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= engine




		def     lowercase       (				self					,						UpperCamelCase					,						**UpperCamelCase      ):
								# runs backpropagation and handles mixed precision
								self.engine.backward(UpperCamelCase					,						**UpperCamelCase      )

								# Deepspeed's `engine.step` performs the following operations:
								# - gradient accumulation check
								# - gradient clipping
								# - optimizer step
								# - zero grad
								# - checking overflow
								# - lr_scheduler step (only if engine.lr_scheduler is not None)
								self.engine.step()
								# and this plugin overrides the above calls with no-ops when Accelerate runs under
								# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
								# training loop that works transparently under many training regimes.


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						device_placement=UpperCamelCase					,						scaler=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= hasattr(self.optimizer					,						"overflow"      )




		def     lowercase       (				self					,						UpperCamelCase=None      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		@property
		def     lowercase       (				self      ):
								if self.__has_overflow__:
														return self.optimizer.overflow
								return False


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=0.0_01					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= params
								_SCREAMING_SNAKE_CASE				= lr
								_SCREAMING_SNAKE_CASE				= weight_decay
								_SCREAMING_SNAKE_CASE				= kwargs


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=None					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= optimizer
								_SCREAMING_SNAKE_CASE				= total_num_steps
								_SCREAMING_SNAKE_CASE				= warmup_num_steps
								_SCREAMING_SNAKE_CASE				= kwargs