






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

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


A__			:    Dict         =				[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        'text-classification',
        'language-modeling',
        'summarization',
        'token-classification',
        'question-answering',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
							import run_clm_flax
							import run_flax_glue
							import run_flax_ner
							import run_mlm_flax
							import run_qa
							import run_summarization_flax
							import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

A__			:    Union[str, Any]         =				logging.getLogger()






def 						a    (		):






				'''simple docstring'''
				lowercase__     				=    argparse.ArgumentParser()
				parser.add_argument('''-f'''       )
				lowercase__     				=    parser.parse_args()
				return args.f






def 						a    (		lowerCamelCase_	,     lowerCamelCase_="eval"       ):






				'''simple docstring'''
				lowercase__     				=    os.path.join(lowerCamelCase_	,     F"""{split}_results.json"""       )
				if os.path.exists(lowerCamelCase_       ):
								with open(lowerCamelCase_	,     '''r'''       ) as f:
												return json.load(lowerCamelCase_       )
				raise ValueError(F"""can't find {path}"""       )


A__			:    Union[str, Any]         =				logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)




class    _UpperCAmelCase      ( A__			):

				"""simple docstring"""




				def        lowercase__     (  self		:					List[str]						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_flax_glue.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertGreaterEqual(result['''eval_accuracy'''],						0.75						)




				@slow
				def        lowercase__     (  self		:					Optional[int]						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_clm_flax.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_clm_flax.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertLess(result['''eval_perplexity'''],						100						)




				@slow
				def        lowercase__     (  self		:					Optional[int]						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_summarization_flax.main()
												lowercase__     				=    get_results(lowerCamelCase,						split='''test'''						)
												self.assertGreaterEqual(result['''test_rouge1'''],						10						)
												self.assertGreaterEqual(result['''test_rouge2'''],						2						)
												self.assertGreaterEqual(result['''test_rougeL'''],						7						)
												self.assertGreaterEqual(result['''test_rougeLsum'''],						7						)




				@slow
				def        lowercase__     (  self		:					int						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_mlm_flax.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertLess(result['''eval_perplexity'''],						42						)




				@slow
				def        lowercase__     (  self		:					str						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_ta_mlm_flax.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertGreaterEqual(result['''eval_accuracy'''],						0.42						)




				@slow
				def        lowercase__     (  self		:					List[Any]						):

								'''simple docstring'''
								# with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
								lowercase__     				=    7 if get_gpu_count() > 1 else 2

								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_flax_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --logging_steps 2 --eval_steps 2
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_flax_ner.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertGreaterEqual(result['''eval_accuracy'''],						0.75						)
												self.assertGreaterEqual(result['''eval_f1'''],						0.3						)




				@slow
				def        lowercase__     (  self		:					Optional[int]						):

								'''simple docstring'''
								lowercase__     				=    self.get_auto_remove_tmp_dir()
								lowercase__     				=    F"""
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase						):
												run_qa.main()
												lowercase__     				=    get_results(lowerCamelCase						)
												self.assertGreaterEqual(result['''eval_f1'''],						30						)
												self.assertGreaterEqual(result['''eval_exact'''],						30						)












from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class    _UpperCAmelCase      ( A__			):

				"""simple docstring"""




				lowercase__       							= DistilBertTokenizer
				lowercase__       							= DistilBertTokenizerFast
				lowercase__       							= True




				@slow
				def        lowercase__     (  self		:					str						):

								'''simple docstring'''
								lowercase__     				=    DistilBertTokenizer.from_pretrained('''distilbert-base-uncased'''						)

								lowercase__     				=    tokenizer.encode('''sequence builders''',						add_special_tokens=lowerCamelCase						)
								lowercase__     				=    tokenizer.encode('''multi-sequence build''',						add_special_tokens=lowerCamelCase						)

								lowercase__     				=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase						)
								lowercase__     				=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase,						lowerCamelCase						)

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]




