




import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english





@require_tokenizers
class 					snake_case_   (     snake_case__   ,	unittest.TestCase	):



				'''simple docstring'''
				lowerCamelCase       =  RoCBertTokenizer
				lowerCamelCase       =  None
				lowerCamelCase       =  False
				lowerCamelCase       =  True
				lowerCamelCase       =  filter_non_english





				def    __SCREAMING_SNAKE_CASE     (      self							:   Dict							)							->			List[str]:
											super().setUp()

											lowerCamelCase_			:    int   						=      ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''你''', '''好''', '''是''', '''谁''', '''a''', '''b''', '''c''', '''d''']
											lowerCamelCase_			:    Tuple   						=      {}
											lowerCamelCase_			:    Union[str, Any]   						=      {}
											for i, value in enumerate(__lowercase							):
																		lowerCamelCase_			:    Dict   						=      i
																		lowerCamelCase_			:    Optional[Any]   						=      i
											lowerCamelCase_			:    Union[str, Any]   						=      os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES["vocab_file"]							)
											lowerCamelCase_			:    List[str]   						=      os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES["word_shape_file"]							)
											lowerCamelCase_			:    List[str]   						=      os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES["word_pronunciation_file"]							)
											with open(self.vocab_file      ,							"w"      ,							encoding="utf-8"							) as vocab_writer:
																		vocab_writer.write("".join([x + "\n" for x in vocab_tokens]							)							)
											with open(self.word_shape_file      ,							"w"      ,							encoding="utf-8"							) as word_shape_writer:
																		json.dump(__lowercase      ,							__lowercase      ,							ensure_ascii=__lowercase							)
											with open(self.word_pronunciation_file      ,							"w"      ,							encoding="utf-8"							) as word_pronunciation_writer:
																		json.dump(__lowercase      ,							__lowercase      ,							ensure_ascii=__lowercase							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   str							)							->			Optional[int]:
											lowerCamelCase_			:    Optional[int]   						=      self.tokenizer_class(self.vocab_file      ,							self.word_shape_file      ,							self.word_pronunciation_file							)

											lowerCamelCase_			:    Optional[Any]   						=      tokenizer.tokenize("你好[SEP]你是谁"							)
											self.assertListEqual(__lowercase      ,							["你", "好", "[SEP]", "你", "是", "谁"]							)
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase							)      ,							[5, 6, 2, 5, 7, 8]							)
											self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(__lowercase							)      ,							[5, 6, 2, 5, 7, 8]							)
											self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(__lowercase							)      ,							[5, 6, 2, 5, 7, 8]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Dict							)							->			Optional[Any]:
											lowerCamelCase_			:    Optional[int]   						=      RoCBertBasicTokenizer()

											self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"							)      ,							["ah", "\u535A", "\u63A8", "zz"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   List[Any]							)							->			Union[str, Any]:
											lowerCamelCase_			:    Optional[Any]   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase							)

											self.assertListEqual(
											    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "							)      ,							["hello", "!", "how", "are", "you", "?"]							)
											self.assertListEqual(tokenizer.tokenize("H\u00E9llo"							)      ,							["hello"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   List[Any]							)							->			Union[str, Any]:
											lowerCamelCase_			:    Optional[int]   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase      ,							strip_accents=__lowercase							)

											self.assertListEqual(
											    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "							)      ,							["hällo", "!", "how", "are", "you", "?"]							)
											self.assertListEqual(tokenizer.tokenize("H\u00E9llo"							)      ,							["h\u00E9llo"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Dict							)							->			List[Any]:
											lowerCamelCase_			:    List[str]   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase      ,							strip_accents=__lowercase							)

											self.assertListEqual(
											    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "							)      ,							["hallo", "!", "how", "are", "you", "?"]							)
											self.assertListEqual(tokenizer.tokenize("H\u00E9llo"							)      ,							["hello"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   int							)							->			Tuple:
											lowerCamelCase_			:    Dict   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase							)

											self.assertListEqual(
											    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "							)      ,							["hallo", "!", "how", "are", "you", "?"]							)
											self.assertListEqual(tokenizer.tokenize("H\u00E9llo"							)      ,							["hello"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   List[str]							)							->			Union[str, Any]:
											lowerCamelCase_			:    Tuple   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase							)

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





				def    __SCREAMING_SNAKE_CASE     (      self							:   Tuple							)							->			Union[str, Any]:
											lowerCamelCase_			:    str   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase      ,							strip_accents=__lowercase							)

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





				def    __SCREAMING_SNAKE_CASE     (      self							:   Union[str, Any]							)							->			Optional[int]:
											lowerCamelCase_			:    int   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase      ,							strip_accents=__lowercase							)

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





				def    __SCREAMING_SNAKE_CASE     (      self							:   Union[str, Any]							)							->			Tuple:
											lowerCamelCase_			:    Any   						=      RoCBertBasicTokenizer(do_lower_case=__lowercase      ,							never_split=["[UNK]"]							)

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





				def    __SCREAMING_SNAKE_CASE     (      self							:   Optional[int]							)							->			Union[str, Any]:
											lowerCamelCase_			:    str   						=      ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

											lowerCamelCase_			:    int   						=      {}
											for i, token in enumerate(__lowercase							):
																		lowerCamelCase_			:    Optional[int]   						=      i
											lowerCamelCase_			:    Any   						=      RoCBertWordpieceTokenizer(vocab=__lowercase      ,							unk_token="[UNK]"							)

											self.assertListEqual(tokenizer.tokenize(""							)      ,							[]							)

											self.assertListEqual(tokenizer.tokenize("unwanted running"							)      ,							["un", "##want", "##ed", "runn", "##ing"]							)

											self.assertListEqual(tokenizer.tokenize("unwantedX running"							)      ,							["[UNK]", "runn", "##ing"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   str							)							->			Union[str, Any]:
											self.assertTrue(_is_whitespace(" "							)							)
											self.assertTrue(_is_whitespace("\t"							)							)
											self.assertTrue(_is_whitespace("\r"							)							)
											self.assertTrue(_is_whitespace("\n"							)							)
											self.assertTrue(_is_whitespace("\u00A0"							)							)

											self.assertFalse(_is_whitespace("A"							)							)
											self.assertFalse(_is_whitespace("-"							)							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Union[str, Any]							)							->			Optional[Any]:
											self.assertTrue(_is_control("\u0005"							)							)

											self.assertFalse(_is_control("A"							)							)
											self.assertFalse(_is_control(" "							)							)
											self.assertFalse(_is_control("\t"							)							)
											self.assertFalse(_is_control("\r"							)							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Dict							)							->			str:
											self.assertTrue(_is_punctuation("-"							)							)
											self.assertTrue(_is_punctuation("$"							)							)
											self.assertTrue(_is_punctuation("`"							)							)
											self.assertTrue(_is_punctuation("."							)							)

											self.assertFalse(_is_punctuation("A"							)							)
											self.assertFalse(_is_punctuation(" "							)							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Dict							)							->			Dict:
											lowerCamelCase_			:    Optional[int]   						=      self.get_tokenizer()

											# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
											self.assertListEqual([tokenizer.tokenize(__lowercase							) for t in ["Test", "\xad", "test"]]      ,							[["[UNK]"], [], ["[UNK]"]]							)

											if self.test_rust_tokenizer:
																		lowerCamelCase_			:    Tuple   						=      self.get_rust_tokenizer()
																		self.assertListEqual(
																		    [rust_tokenizer.tokenize(__lowercase							) for t in ["Test", "\xad", "test"]]      ,							[["[UNK]"], [], ["[UNK]"]]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Optional[Any]							)							->			int:
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"							):
																									lowerCamelCase_			:    Optional[int]   						=      self.rust_tokenizer_class.from_pretrained(__lowercase      ,							**__lowercase							)

																									lowerCamelCase_			:    str   						=      F"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
																									lowerCamelCase_			:    int   						=      tokenizer_r.encode_plus(
																									    __lowercase      ,							return_attention_mask=__lowercase      ,							return_token_type_ids=__lowercase      ,							return_offsets_mapping=__lowercase      ,							add_special_tokens=__lowercase      ,							)

																									lowerCamelCase_			:    Optional[Any]   						=      tokenizer_r.do_lower_case if hasattr(__lowercase      ,							"do_lower_case"							) else False
																									lowerCamelCase_			:    Union[str, Any]   						=      (
																									    [
																									        ((0, 0), tokenizer_r.cls_token),
																									        ((0, 1), '''A'''),
																									        ((1, 2), ''','''),
																									        ((3, 5), '''na'''),
																									        ((5, 6), '''##ï'''),
																									        ((6, 8), '''##ve'''),
																									        ((9, 15), tokenizer_r.mask_token),
																									        ((16, 21), '''Allen'''),
																									        ((21, 23), '''##NL'''),
																									        ((23, 24), '''##P'''),
																									        ((25, 33), '''sentence'''),
																									        ((33, 34), '''.'''),
																									        ((0, 0), tokenizer_r.sep_token),
																									    ]
																									    if not do_lower_case
																									    else [
																									        ((0, 0), tokenizer_r.cls_token),
																									        ((0, 1), '''a'''),
																									        ((1, 2), ''','''),
																									        ((3, 8), '''naive'''),
																									        ((9, 15), tokenizer_r.mask_token),
																									        ((16, 21), '''allen'''),
																									        ((21, 23), '''##nl'''),
																									        ((23, 24), '''##p'''),
																									        ((25, 33), '''sentence'''),
																									        ((33, 34), '''.'''),
																									        ((0, 0), tokenizer_r.sep_token),
																									    ]
																									)

																									self.assertEqual(
																									    [e[1] for e in expected_results]      ,							tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]							)							)
																									self.assertEqual([e[0] for e in expected_results]      ,							tokens["offset_mapping"]							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Union[str, Any]							)							->			Tuple:
											lowerCamelCase_			:    Union[str, Any]   						=      ['''的''', '''人''', '''有''']
											lowerCamelCase_			:    int   						=      ''''''.join(__lowercase							)
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"							):
																									lowerCamelCase_			:    Tuple   						=      True
																									lowerCamelCase_			:    Union[str, Any]   						=      self.tokenizer_class.from_pretrained(__lowercase      ,							**__lowercase							)
																									lowerCamelCase_			:    Optional[int]   						=      self.rust_tokenizer_class.from_pretrained(__lowercase      ,							**__lowercase							)

																									lowerCamelCase_			:    List[str]   						=      tokenizer_p.encode(__lowercase      ,							add_special_tokens=__lowercase							)
																									lowerCamelCase_			:    Any   						=      tokenizer_r.encode(__lowercase      ,							add_special_tokens=__lowercase							)

																									lowerCamelCase_			:    List[str]   						=      tokenizer_r.convert_ids_to_tokens(__lowercase							)
																									lowerCamelCase_			:    Optional[Any]   						=      tokenizer_p.convert_ids_to_tokens(__lowercase							)

																									# it is expected that each Chinese character is not preceded by "##"
																									self.assertListEqual(__lowercase      ,							__lowercase							)
																									self.assertListEqual(__lowercase      ,							__lowercase							)

																									lowerCamelCase_			:    Optional[int]   						=      False
																									lowerCamelCase_			:    str   						=      self.rust_tokenizer_class.from_pretrained(__lowercase      ,							**__lowercase							)
																									lowerCamelCase_			:    Optional[Any]   						=      self.tokenizer_class.from_pretrained(__lowercase      ,							**__lowercase							)

																									lowerCamelCase_			:    Optional[int]   						=      tokenizer_r.encode(__lowercase      ,							add_special_tokens=__lowercase							)
																									lowerCamelCase_			:    int   						=      tokenizer_p.encode(__lowercase      ,							add_special_tokens=__lowercase							)

																									lowerCamelCase_			:    List[Any]   						=      tokenizer_r.convert_ids_to_tokens(__lowercase							)
																									lowerCamelCase_			:    Any   						=      tokenizer_p.convert_ids_to_tokens(__lowercase							)

																									# it is expected that only the first Chinese character is not preceded by "##".
																									lowerCamelCase_			:    Dict   						=      [
																									    F"##{token}" if idx != 0 else token for idx, token in enumerate(__lowercase							)
																									]
																									self.assertListEqual(__lowercase      ,							__lowercase							)
																									self.assertListEqual(__lowercase      ,							__lowercase							)





				@slow
				def    __SCREAMING_SNAKE_CASE     (      self							:   str							)							->			Union[str, Any]:
											lowerCamelCase_			:    Optional[Any]   						=      self.tokenizer_class(self.vocab_file      ,							self.word_shape_file      ,							self.word_pronunciation_file							)

											lowerCamelCase_			:    Any   						=      tokenizer.encode("你好"      ,							add_special_tokens=__lowercase							)
											lowerCamelCase_			:    Tuple   						=      tokenizer.encode("你是谁"      ,							add_special_tokens=__lowercase							)

											lowerCamelCase_			:    Optional[int]   						=      tokenizer.build_inputs_with_special_tokens(__lowercase							)
											lowerCamelCase_			:    Optional[Any]   						=      tokenizer.build_inputs_with_special_tokens(__lowercase      ,							__lowercase							)

											assert encoded_sentence == [1] + text + [2]
											assert encoded_pair == [1] + text + [2] + text_a + [2]





				def    __SCREAMING_SNAKE_CASE     (      self							:   Tuple							)							->			Tuple:
											lowerCamelCase_			:    Dict   						=      self.get_tokenizers(do_lower_case=__lowercase							)
											for tokenizer in tokenizers:
																		with self.subTest(F"{tokenizer.__class__.__name__}"							):
																									lowerCamelCase_			:    Optional[Any]   						=      '''你好，你是谁'''
																									lowerCamelCase_			:    Optional[int]   						=      tokenizer.tokenize(__lowercase							)
																									lowerCamelCase_			:    str   						=      tokenizer.convert_tokens_to_ids(__lowercase							)
																									lowerCamelCase_			:    int   						=      tokenizer.convert_tokens_to_shape_ids(__lowercase							)
																									lowerCamelCase_			:    int   						=      tokenizer.convert_tokens_to_pronunciation_ids(__lowercase							)
																									lowerCamelCase_			:    Optional[int]   						=      tokenizer.prepare_for_model(
																									    __lowercase      ,							__lowercase      ,							__lowercase      ,							add_special_tokens=__lowercase							)

																									lowerCamelCase_			:    List[str]   						=      tokenizer.encode_plus(__lowercase      ,							add_special_tokens=__lowercase							)

																									self.assertEqual(__lowercase      ,							__lowercase							)








"""simple docstring"""





import argparse
import os
import sys
from unittest.mock import patch

import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main

from transformers import MarianMTModel
from transformers.file_utils import cached_path
from transformers.testing_utils import TestCasePlus, require_torch_gpu, slow
from utils import load_json


_UpperCamelCase					      =   'sshleifer/mar_enro_6_3_student'
class 		SCREAMING_SNAKE_CASE_				(     snake_case__ ):
				"""simple docstring"""




				def        __lowercase	(  self	:List[Any]      ):
											super().setUp()

											__lowerCamelCase   :   int       =cached_path(
											    '''https://cdn-datasets.huggingface.co/translation/wmt_en_ro-tr40k-va0.5k-te0.5k.tar.gz'''    ,     extract_compressed_file=__lowercase    ,     )
											__lowerCamelCase   :   Dict       =f'{data_cached}/wmt_en_ro-tr40k-va0.5k-te0.5k'




				@slow
				@require_torch_gpu
				def        __lowercase	(  self	:int      ):
											MarianMTModel.from_pretrained(__lowercase      )




				@slow
				@require_torch_gpu
				def        __lowercase	(  self	:Union[str, Any]      ):
											__lowerCamelCase   :   Tuple       ={
											    '''$MAX_LEN''': 64,
											    '''$BS''': 64,
											    '''$GAS''': 1,
											    '''$ENRO_DIR''': self.data_dir,
											    '''facebook/mbart-large-cc25''': MARIAN_MODEL,
											    # "val_check_interval=0.25": "val_check_interval=1.0",
											    '''--learning_rate=3e-5''': '''--learning_rate 3e-4''',
											    '''--num_train_epochs 6''': '''--num_train_epochs 1''',
											}

											# Clean up bash script
											__lowerCamelCase   :   str       =(self.test_file_dir / '''train_mbart_cc25_enro.sh''').open().read().split('''finetune.py'''      )[1].strip()
											__lowerCamelCase   :   Union[str, Any]       =bash_script.replace('''\\\n'''    ,     ''''''      ).strip().replace('''"$@"'''    ,     ''''''      )
											for k, v in env_vars_to_replace.items():
																		__lowerCamelCase   :   Tuple       =bash_script.replace(__lowercase    ,     str(__lowercase      )      )
											__lowerCamelCase   :   Union[str, Any]       =self.get_auto_remove_tmp_dir()

											# bash_script = bash_script.replace("--fp16 ", "")
											__lowerCamelCase   :   List[Any]       =f'\n            --output_dir {output_dir}\n            --tokenizer_name Helsinki-NLP/opus-mt-en-ro\n            --sortish_sampler\n            --do_predict\n            --gpus 1\n            --freeze_encoder\n            --n_train 40000\n            --n_val 500\n            --n_test 500\n            --fp16_opt_level O1\n            --num_sanity_val_steps 0\n            --eval_beams 2\n        '.split()
											# XXX: args.gpus > 1 : handle multi_gpu in the future

											__lowerCamelCase   :   str       =['''finetune.py'''] + bash_script.split() + args
											with patch.object(__lowercase    ,     '''argv'''    ,     __lowercase      ):
																		__lowerCamelCase   :   str       =argparse.ArgumentParser()
																		__lowerCamelCase   :   Dict       =pl.Trainer.add_argparse_args(__lowercase      )
																		__lowerCamelCase   :   List[Any]       =SummarizationModule.add_model_specific_args(__lowercase    ,     os.getcwd()      )
																		__lowerCamelCase   :   int       =parser.parse_args()
																		__lowerCamelCase   :   Tuple       =main(__lowercase      )

											# Check metrics
											__lowerCamelCase   :   Union[str, Any]       =load_json(model.metrics_save_path      )
											__lowerCamelCase   :   Any       =metrics['''val'''][0]
											__lowerCamelCase   :   int       =metrics['''val'''][-1]
											self.assertEqual(len(metrics['''val''']      )    ,     (args.max_epochs / args.val_check_interval)      )
											assert isinstance(last_step_stats[f'val_avg_{model.val_metric}']    ,     __lowercase      )

											self.assertGreater(last_step_stats['''val_avg_gen_time''']    ,     0.01      )
											# model hanging on generate. Maybe bad config was saved. (XXX: old comment/assert?)
											self.assertLessEqual(last_step_stats['''val_avg_gen_time''']    ,     1.0      )

											# test learning requirements:

											# 1. BLEU improves over the course of training by more than 2 pts
											self.assertGreater(last_step_stats['''val_avg_bleu'''] - first_step_stats['''val_avg_bleu''']    ,     2      )

											# 2. BLEU finishes above 17
											self.assertGreater(last_step_stats['''val_avg_bleu''']    ,     17      )

											# 3. test BLEU and val BLEU within ~1.1 pt.
											self.assertLess(abs(metrics['''val'''][-1]['''val_avg_bleu'''] - metrics['''test'''][-1]['''test_avg_bleu''']      )    ,     1.1      )

											# check lightning ckpt can be loaded and has a reasonable statedict
											__lowerCamelCase   :   Any       =os.listdir(__lowercase      )
											__lowerCamelCase   :   Tuple       =[x for x in contents if x.endswith('''.ckpt'''      )][0]
											__lowerCamelCase   :   int       =os.path.join(args.output_dir    ,     __lowercase      )
											__lowerCamelCase   :   List[str]       =torch.load(__lowercase    ,     map_location='''cpu'''      )
											__lowerCamelCase   :   str       ='''model.model.decoder.layers.0.encoder_attn_layer_norm.weight'''
											assert expected_key in ckpt["state_dict"]
											assert ckpt["state_dict"]["model.model.decoder.layers.0.encoder_attn_layer_norm.weight"].dtype == torch.floataa

											# TODO: turn on args.do_predict when PL bug fixed.
											if args.do_predict:
																		__lowerCamelCase   :   str       ={os.path.basename(__lowercase      ) for p in contents}
																		assert "test_generations.txt" in contents
																		assert "test_results.txt" in contents
																		# assert len(metrics["val"]) ==  desired_n_evals
																		assert len(metrics['''test''']      ) == 1

class 		SCREAMING_SNAKE_CASE_				(     snake_case__ ):
				"""simple docstring"""




				@timeout_decorator.timeout(600      )
				@slow
				@require_torch_gpu
				def        __lowercase	(  self	:str      ):
											__lowerCamelCase   :   int       =f'{self.test_file_dir_str}/test_data/wmt_en_ro'
											__lowerCamelCase   :   List[Any]       ={
											    '''--fp16_opt_level=O1''': '''''',
											    '''$MAX_LEN''': 128,
											    '''$BS''': 16,
											    '''$GAS''': 1,
											    '''$ENRO_DIR''': data_dir,
											    '''$m''': '''sshleifer/student_marian_en_ro_6_1''',
											    '''val_check_interval=0.25''': '''val_check_interval=1.0''',
											}

											# Clean up bash script
											__lowerCamelCase   :   Any       =(
											    (self.test_file_dir / '''distil_marian_no_teacher.sh''').open().read().split('''distillation.py'''      )[1].strip()
											)
											__lowerCamelCase   :   Optional[Any]       =bash_script.replace('''\\\n'''    ,     ''''''      ).strip().replace('''"$@"'''    ,     ''''''      )
											__lowerCamelCase   :   Union[str, Any]       =bash_script.replace('''--fp16 '''    ,     ''' '''      )

											for k, v in env_vars_to_replace.items():
																		__lowerCamelCase   :   str       =bash_script.replace(__lowercase    ,     str(__lowercase      )      )
											__lowerCamelCase   :   Any       =self.get_auto_remove_tmp_dir()
											__lowerCamelCase   :   Optional[int]       =bash_script.replace('''--fp16'''    ,     ''''''      )
											__lowerCamelCase   :   Tuple       =6
											__lowerCamelCase   :   str       =(
											    ['''distillation.py''']
											    + bash_script.split()
											    + [
											        f'--output_dir={output_dir}',
											        '''--gpus=1''',
											        '''--learning_rate=1e-3''',
											        f'--num_train_epochs={epochs}',
											        '''--warmup_steps=10''',
											        '''--val_check_interval=1.0''',
											        '''--do_predict''',
											    ]
											)
											with patch.object(__lowercase    ,     '''argv'''    ,     __lowercase      ):
																		__lowerCamelCase   :   int       =argparse.ArgumentParser()
																		__lowerCamelCase   :   int       =pl.Trainer.add_argparse_args(__lowercase      )
																		__lowerCamelCase   :   Optional[int]       =SummarizationDistiller.add_model_specific_args(__lowercase    ,     os.getcwd()      )
																		__lowerCamelCase   :   Union[str, Any]       =parser.parse_args()
																		# assert args.gpus == gpus THIS BREAKS for multi_gpu

																		__lowerCamelCase   :   Union[str, Any]       =distill_main(__lowercase      )

											# Check metrics
											__lowerCamelCase   :   Dict       =load_json(model.metrics_save_path      )
											__lowerCamelCase   :   List[str]       =metrics['''val'''][0]
											__lowerCamelCase   :   Tuple       =metrics['''val'''][-1]
											assert len(metrics['''val''']      ) >= (args.max_epochs / args.val_check_interval)  # +1 accounts for val_sanity_check

											assert last_step_stats["val_avg_gen_time"] >= 0.01

											assert first_step_stats["val_avg_bleu"] < last_step_stats["val_avg_bleu"]  # model learned nothing
											assert 1.0 >= last_step_stats["val_avg_gen_time"]  # model hanging on generate. Maybe bad config was saved.
											assert isinstance(last_step_stats[f'val_avg_{model.val_metric}']    ,     __lowercase      )

											# check lightning ckpt can be loaded and has a reasonable statedict
											__lowerCamelCase   :   int       =os.listdir(__lowercase      )
											__lowerCamelCase   :   str       =[x for x in contents if x.endswith('''.ckpt'''      )][0]
											__lowerCamelCase   :   Union[str, Any]       =os.path.join(args.output_dir    ,     __lowercase      )
											__lowerCamelCase   :   Optional[int]       =torch.load(__lowercase    ,     map_location='''cpu'''      )
											__lowerCamelCase   :   int       ='''model.model.decoder.layers.0.encoder_attn_layer_norm.weight'''
											assert expected_key in ckpt["state_dict"]
											assert ckpt["state_dict"]["model.model.decoder.layers.0.encoder_attn_layer_norm.weight"].dtype == torch.floataa

											# TODO: turn on args.do_predict when PL bug fixed.
											if args.do_predict:
																		__lowerCamelCase   :   int       ={os.path.basename(__lowercase      ) for p in contents}
																		assert "test_generations.txt" in contents
																		assert "test_results.txt" in contents
																		# assert len(metrics["val"]) ==  desired_n_evals
																		assert len(metrics['''test''']      ) == 1




