






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


__snake_case    :    Optional[Any]         =     [
    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)

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







def 	_UpperCamelCase   (    )  ->   Optional[int]:

						"""simple docstring"""



						lowerCAmelCase__    						=						argparse.ArgumentParser()
						parser.add_argument('-f'		)
						lowerCAmelCase__    						=						parser.parse_args()
						return args.f







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[int]    ,       UpperCamelCase_       :					Tuple="eval"		)  ->   List[Any]:

						"""simple docstring"""



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


__snake_case    :    List[str]         =     logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


class     __SCREAMING_SNAKE_CASE					(   __lowercase):






						def       UpperCamelCase__      (	self   ):






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

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






						@slow
						def       UpperCamelCase__      (	self   ):






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

												with patch.object(_UpperCamelCase     ,						'argv'     ,						_UpperCamelCase   ):
																		run_clm_flax.main()
																		lowerCAmelCase__    						=						get_results(_UpperCamelCase   )
																		self.assertLess(result['eval_perplexity']     ,						1_00   )






						@slow
						def       UpperCamelCase__      (	self   ):






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

												with patch.object(_UpperCamelCase     ,						'argv'     ,						_UpperCamelCase   ):
																		run_summarization_flax.main()
																		lowerCAmelCase__    						=						get_results(_UpperCamelCase     ,						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       UpperCamelCase__      (	self   ):






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

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






						@slow
						def       UpperCamelCase__      (	self   ):






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

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






						@slow
						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						7 if get_gpu_count() > 1 else 2

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

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







						@slow
						def       UpperCamelCase__      (	self   ):






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

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













from collections import deque

from .hash_table import HashTable


class     __SCREAMING_SNAKE_CASE					(   __lowercase):






						def __init__(	self     ,						*_UpperCamelCase     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												super().__init__(*_UpperCamelCase     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						_UpperCamelCase     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						deque([]   ) if self.values[key] is None else self.values[key]
												self.values[key].appendleft(_UpperCamelCase   )
												lowerCAmelCase__    						=						self.values[key]






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												return (
												    sum(self.charge_factor - len(_UpperCamelCase   ) for slot in self.values   )
												    / self.size_table
												    * self.charge_factor
												)







						def       UpperCamelCase__      (	self     ,						_UpperCamelCase     ,						_UpperCamelCase=None   ):






												"""simple docstring"""
												if not (
												    len(self.values[key]   ) == self.charge_factor and self.values.count(_UpperCamelCase   ) == 0
												):
																		return key
												return super()._collision_resolution(_UpperCamelCase     ,						_UpperCamelCase   )





