
'''simple docstring'''







import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case				:   str     =				get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
						from transformers.models.mbart.modeling_mbart import shift_tokens_right

_snake_case				:   List[Any]     =				250_004
_snake_case				:   List[str]     =				250_020


@require_sentencepiece
@require_tokenizers
class 			lowerCAmelCase (				__UpperCAmelCase		,     unittest.TestCase			):
		a							:					List[str]       =					MBartaaTokenizer
		a							:					Any       =					MBartaaTokenizerFast
		a							:					List[Any]       =					True
		a							:					List[str]       =					True




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

								# We have a SentencePiece fixture for testing
								_SCREAMING_SNAKE_CASE				= MBartaaTokenizer(UpperCamelCase					,						src_lang="en_XX"					,						tgt_lang="ro_RO"					,						keep_accents=UpperCamelCase      )
								tokenizer.save_pretrained(self.tmpdirname      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= "<s>"
								_SCREAMING_SNAKE_CASE				= 0

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase      )					,						UpperCamelCase      )
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase      )					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= list(self.get_tokenizer().get_vocab().keys()      )

								self.assertEqual(vocab_keys[0]					,						"<s>"      )
								self.assertEqual(vocab_keys[1]					,						"<pad>"      )
								self.assertEqual(vocab_keys[-1]					,						"<mask>"      )
								self.assertEqual(len(UpperCamelCase      )					,						1_054      )




		def     lowercase       (				self      ):
								self.assertEqual(self.get_tokenizer().vocab_size					,						1_054      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= MBartaaTokenizer(UpperCamelCase					,						src_lang="en_XX"					,						tgt_lang="ro_RO"					,						keep_accents=UpperCamelCase      )

								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize("This is a test"      )
								self.assertListEqual(UpperCamelCase					,						["▁This", "▁is", "▁a", "▁t", "est"]      )

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(UpperCamelCase      )					,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]					,						)

								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize("I was born in 92000, and this is falsé."      )
								self.assertListEqual(
								    UpperCamelCase					,						[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "9", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "é", "."]					,						)
								_SCREAMING_SNAKE_CASE				= tokenizer.convert_tokens_to_ids(UpperCamelCase      )
								self.assertListEqual(
								    UpperCamelCase					,						[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]					,						)

								_SCREAMING_SNAKE_CASE				= tokenizer.convert_ids_to_tokens(UpperCamelCase      )
								self.assertListEqual(
								    UpperCamelCase					,						[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "<unk>", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "<unk>", "."]					,						)




		@slow
		def     lowercase       (				self      ):
								# fmt: off
								_SCREAMING_SNAKE_CASE				= {"input_ids": [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=UpperCamelCase					,						model_name="facebook/mbart-large-50"					,						revision="d3913889c59cd5c9e456b269c376325eabad57e2"					,						)




		def     lowercase       (				self      ):
								if not self.test_slow_tokenizer:
														# as we don't have a slow version, we can't compare the outputs between slow and fast versions
														return

								_SCREAMING_SNAKE_CASE				= (self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'      ):
																				_SCREAMING_SNAKE_CASE				= self.rust_tokenizer_class.from_pretrained(UpperCamelCase					,						**UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= self.tokenizer_class.from_pretrained(UpperCamelCase					,						**UpperCamelCase      )

																				_SCREAMING_SNAKE_CASE				= tempfile.mkdtemp()

																				_SCREAMING_SNAKE_CASE				= tokenizer_r.save_pretrained(UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.save_pretrained(UpperCamelCase      )

																				# Checks it save with the same files + the tokenizer.json file for the fast one
																				self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files      )      )
																				_SCREAMING_SNAKE_CASE				= tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f      )
																				self.assertSequenceEqual(UpperCamelCase					,						UpperCamelCase      )

																				# Checks everything loads correctly in the same way
																				_SCREAMING_SNAKE_CASE				= tokenizer_r.from_pretrained(UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.from_pretrained(UpperCamelCase      )

																				# Check special tokens are set accordingly on Rust and Python
																				for key in tokenizer_pp.special_tokens_map:
																										self.assertTrue(hasattr(UpperCamelCase					,						UpperCamelCase      )      )
																										# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																										# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																				shutil.rmtree(UpperCamelCase      )

																				# Save tokenizer rust, legacy_format=True
																				_SCREAMING_SNAKE_CASE				= tempfile.mkdtemp()

																				_SCREAMING_SNAKE_CASE				= tokenizer_r.save_pretrained(UpperCamelCase					,						legacy_format=UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.save_pretrained(UpperCamelCase      )

																				# Checks it save with the same files
																				self.assertSequenceEqual(UpperCamelCase					,						UpperCamelCase      )

																				# Checks everything loads correctly in the same way
																				_SCREAMING_SNAKE_CASE				= tokenizer_r.from_pretrained(UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.from_pretrained(UpperCamelCase      )

																				# Check special tokens are set accordingly on Rust and Python
																				for key in tokenizer_pp.special_tokens_map:
																										self.assertTrue(hasattr(UpperCamelCase					,						UpperCamelCase      )      )

																				shutil.rmtree(UpperCamelCase      )

																				# Save tokenizer rust, legacy_format=False
																				_SCREAMING_SNAKE_CASE				= tempfile.mkdtemp()

																				_SCREAMING_SNAKE_CASE				= tokenizer_r.save_pretrained(UpperCamelCase					,						legacy_format=UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.save_pretrained(UpperCamelCase      )

																				# Checks it saved the tokenizer.json file
																				self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files      )      )

																				# Checks everything loads correctly in the same way
																				_SCREAMING_SNAKE_CASE				= tokenizer_r.from_pretrained(UpperCamelCase      )
																				_SCREAMING_SNAKE_CASE				= tokenizer_p.from_pretrained(UpperCamelCase      )

																				# Check special tokens are set accordingly on Rust and Python
																				for key in tokenizer_pp.special_tokens_map:
																										self.assertTrue(hasattr(UpperCamelCase					,						UpperCamelCase      )      )

																				shutil.rmtree(UpperCamelCase      )


@require_torch
@require_sentencepiece
@require_tokenizers
class 			lowerCAmelCase (				unittest.TestCase			):
		a							:					Optional[Any]       =					"""facebook/mbart-large-50-one-to-many-mmt"""
		a							:					Union[str, Any]       =					[
		    """ UN Chief Says There Is No Military Solution in Syria""",
		    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
		]
		a							:					Tuple       =					[
		    """Şeful ONU declară că nu există o soluţie militară în Siria""",
		    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
		    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
		    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
		]
		a							:					Optional[int]       =					[EN_CODE, 8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2]




		@classmethod
		def     lowercase       (				cls      ):
								_SCREAMING_SNAKE_CASE				= MBartaaTokenizer.from_pretrained(
								    cls.checkpoint_name					,						src_lang="en_XX"					,						tgt_lang="ro_RO"      )
								_SCREAMING_SNAKE_CASE				= 1
								return cls




		def     lowercase       (				self      ):
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]					,						250_001      )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]					,						250_004      )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]					,						250_020      )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]					,						250_038      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
								self.assertListEqual(self.expected_src_tokens					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								self.assertIn(UpperCamelCase					,						self.tokenizer.all_special_ids      )
								_SCREAMING_SNAKE_CASE				= [RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
								_SCREAMING_SNAKE_CASE				= self.tokenizer.decode(UpperCamelCase					,						skip_special_tokens=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= self.tokenizer.decode(generated_ids[1:]					,						skip_special_tokens=UpperCamelCase      )
								self.assertEqual(UpperCamelCase					,						UpperCamelCase      )
								self.assertNotIn(self.tokenizer.eos_token					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= ["this is gunna be a long sentence " * 20]
								assert isinstance(src_text[0]					,						UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= 10
								_SCREAMING_SNAKE_CASE				= self.tokenizer(UpperCamelCase					,						max_length=UpperCamelCase					,						truncation=UpperCamelCase      ).input_ids[0]
								self.assertEqual(ids[0]					,						UpperCamelCase      )
								self.assertEqual(ids[-1]					,						2      )
								self.assertEqual(len(UpperCamelCase      )					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]      )					,						[250_053, 250_001]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= tempfile.mkdtemp()
								_SCREAMING_SNAKE_CASE				= self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= MBartaaTokenizer.from_pretrained(UpperCamelCase      )
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids					,						UpperCamelCase      )




		@require_torch
		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer(self.src_text					,						text_target=self.tgt_text					,						padding=UpperCamelCase					,						return_tensors="pt"      )
								_SCREAMING_SNAKE_CASE				= shift_tokens_right(batch["labels"]					,						self.tokenizer.pad_token_id      )

								# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
								assert batch.input_ids[1][0] == EN_CODE
								assert batch.input_ids[1][-1] == 2
								assert batch.labels[1][0] == RO_CODE
								assert batch.labels[1][-1] == 2
								assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]




		@require_torch
		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer(
								    self.src_text					,						text_target=self.tgt_text					,						padding=UpperCamelCase					,						truncation=UpperCamelCase					,						max_length=len(self.expected_src_tokens      )					,						return_tensors="pt"					,						)
								_SCREAMING_SNAKE_CASE				= shift_tokens_right(batch["labels"]					,						self.tokenizer.pad_token_id      )

								self.assertIsInstance(UpperCamelCase					,						UpperCamelCase      )

								self.assertEqual((2, 14)					,						batch.input_ids.shape      )
								self.assertEqual((2, 14)					,						batch.attention_mask.shape      )
								_SCREAMING_SNAKE_CASE				= batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens					,						UpperCamelCase      )
								self.assertEqual(2					,						batch.decoder_input_ids[0, 0]      )  # decoder_start_token_id
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens					,						[EN_CODE]      )
								self.assertEqual(self.tokenizer.suffix_tokens					,						[self.tokenizer.eos_token_id]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer(self.src_text					,						padding=UpperCamelCase					,						truncation=UpperCamelCase					,						max_length=3					,						return_tensors="pt"      )
								_SCREAMING_SNAKE_CASE				= self.tokenizer(
								    text_target=self.tgt_text					,						padding=UpperCamelCase					,						truncation=UpperCamelCase					,						max_length=10					,						return_tensors="pt"      )
								_SCREAMING_SNAKE_CASE				= targets["input_ids"]
								_SCREAMING_SNAKE_CASE				= shift_tokens_right(UpperCamelCase					,						self.tokenizer.pad_token_id      )

								self.assertEqual(batch.input_ids.shape[1]					,						3      )
								self.assertEqual(batch.decoder_input_ids.shape[1]					,						10      )




		@require_torch
		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer._build_translation_inputs(
								    "A test"					,						return_tensors="pt"					,						src_lang="en_XX"					,						tgt_lang="ar_AR"      )

								self.assertEqual(
								    nested_simplify(UpperCamelCase      )					,						{
								        # en_XX, A, test, EOS
								        "input_ids": [[250_004, 62, 3_034, 2]],
								        "attention_mask": [[1, 1, 1, 1]],
								        # ar_AR
								        "forced_bos_token_id": 250_001,
								    }					,						)

'''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