import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type

from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm import tqdm


_UpperCAmelCase            =		re.compile("""[^A-Za-z_0-9]""")
# parameters used in DuplicationIndex
_UpperCAmelCase            =		10
_UpperCAmelCase            =		256




def     UpperCamelCase						(	__lowercase						:			List[str]     ):
		'''simple docstring'''




		if len(__lowercase     ) < MIN_NUM_TOKENS:
				return None
		A_		:    Tuple         =				MinHash(num_perm=__lowercase     )
		for token in set(__lowercase     ):
				min_hash.update(token.encode()     )
		return min_hash




def     UpperCamelCase						(	__lowercase						:			str     ):
		'''simple docstring'''




		return {t for t in NON_ALPHA.split(__lowercase     ) if len(t.strip()     ) > 0}





class UpperCAmelCase						:


				'''simple docstring'''






				def __init__(						self		,     *,
				    lowercase = 0.85		,     ):



						"""simple docstring"""





						A_		:    str         =				duplication_jaccard_threshold
						A_		:    int         =				NUM_PERM
						A_		:    int         =				MinHashLSH(threshold=self._duplication_jaccard_threshold		,     num_perm=self._num_perm )

						A_		:    int         =				defaultdict(lowercase )
				def   lowerCAmelCase_       (						self		,     lowercase		,     lowercase ):



						"""simple docstring"""





						A_		:    int         =				self._index.query(lowercase )
						if code_key in self._index.keys:
								print(F'''Duplicate key {code_key}''' )
								return

						self._index.insert(lowercase		,     lowercase )
						if len(lowercase ) > 0:
								for base_duplicate in close_duplicates:
										if base_duplicate in self._duplicate_clusters:
												self._duplicate_clusters[base_duplicate].add(lowercase )
												break
								else:
										self._duplicate_clusters[close_duplicates[0]].add(lowercase )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    List[str]         =				[]
						for base, duplicates in self._duplicate_clusters.items():
								A_		:    int         =				[base] + list(lowercase )
								# reformat the cluster to be a list of dict
								A_		:    str         =				[{'base_index': el[0], 'repo_name': el[1], 'path': el[2]} for el in cluster]
								duplicate_clusters.append(lowercase )
						return duplicate_clusters







				def   lowerCAmelCase_       (						self		,     lowercase ):



						"""simple docstring"""





						A_		:    Dict         =				self.get_duplicate_clusters()
						with open(lowercase		,     'w' ) as f:
								json.dump(lowercase		,     lowercase )




def     UpperCamelCase						(	__lowercase						:			Dict     ):
		'''simple docstring'''




		A_       ,      A_		:    Dict         =				element
		A_		:    Union[str, Any]         =				get_min_hash([t for t in NON_ALPHA.split(data['content']     ) if len(t.strip()     ) > 0]     )
		if min_hash is not None:
				return (index, data["repo_name"], data["path"]), min_hash




def     UpperCamelCase						(	__lowercase						:			Type[Dataset]     ):
		'''simple docstring'''




		with mp.Pool() as pool:
				for data in pool.imap_unordered(
				    _compute_min_hash						,ThreadedIterator(__lowercase						,max_queue_size=1_00_00     )						,chunksize=1_00						,):
						if data is not None:
								yield data




def     UpperCamelCase						(	__lowercase						:			Type[Dataset]						,__lowercase						:			float     ):
		'''simple docstring'''




		A_		:    Union[str, Any]         =				DuplicationIndex(duplication_jaccard_threshold=__lowercase     )

		for filename, min_hash in tqdm(ThreadedIterator(minhash_iter(enumerate(__lowercase     )     )						,max_queue_size=1_00     )     ):
				di.add(__lowercase						,__lowercase     )

		# Returns a List[Cluster] where Cluster is List[str] with the filenames.
		return di.get_duplicate_clusters()




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			str     ):
		'''simple docstring'''




		A_		:    int         =				get_tokens(__lowercase     )
		A_		:    Optional[int]         =				get_tokens(__lowercase     )
		return len(tokensa & tokensa     ) / len(tokensa | tokensa     )


_UpperCAmelCase            =		None




def     UpperCamelCase						(	__lowercase						:			Tuple						,__lowercase						:			Optional[int]     ):
		'''simple docstring'''




		A_		:    List[str]         =				[]
		for elementa in cluster:
				A_		:    List[str]         =				_shared_dataset[elementa['base_index']]['content']
				for elementa in extremes:
						A_		:    str         =				_shared_dataset[elementa['base_index']]['content']
						if jaccard_similarity(__lowercase						,__lowercase     ) >= jaccard_threshold:
								elementa["copies"] += 1
								break
				else:
						A_		:    Union[str, Any]         =				1
						extremes.append(__lowercase     )
		return extremes




def     UpperCamelCase						(	__lowercase						:			Optional[Any]						,__lowercase						:			List[str]						,__lowercase						:			Tuple     ):
		'''simple docstring'''




		global _shared_dataset
		A_		:    Any         =				dataset
		A_		:    Union[str, Any]         =				[]
		A_		:    List[str]         =				partial(_find_cluster_extremes_shared						,jaccard_threshold=__lowercase     )
		with mp.Pool() as pool:
				for extremes in tqdm(
				    pool.imap_unordered(
				        __lowercase						,__lowercase						,)						,total=len(__lowercase     )						,):
						extremes_list.append(__lowercase     )
		return extremes_list




def     UpperCamelCase						(	__lowercase						:			Type[Dataset]						,__lowercase						:			float = 0.85     ):
		'''simple docstring'''




		A_		:    Tuple         =				make_duplicate_clusters(__lowercase						,__lowercase     )
		A_		:    List[str]         =				{x['base_index'] for cluster in duplicate_clusters for x in cluster}
		A_		:    Tuple         =				{}
		A_		:    int         =				find_extremes(__lowercase						,__lowercase						,__lowercase     )
		for extremes in extremes_clusters:
				for element in extremes:
						A_		:    Optional[int]         =				element
		A_		:    int         =				duplicate_indices - set(extreme_dict.keys()     )
		A_		:    int         =				dataset.filter(lambda __lowercase						,__lowercase     : idx not in remove_indices						,with_indices=__lowercase     )

		# update duplicate_clusters
		for cluster in duplicate_clusters:
				for element in cluster:
						A_		:    List[str]         =				element['base_index'] in extreme_dict
						if element["is_extreme"]:
								A_		:    Tuple         =				extreme_dict[element['base_index']]['copies']

		print(f'''Original dataset size: {len(__lowercase     )}'''     )
		print(f'''Number of duplicate clusters: {len(__lowercase     )}'''     )
		print(f'''Files in duplicate cluster: {len(__lowercase     )}'''     )
		print(f'''Unique files in duplicate cluster: {len(__lowercase     )}'''     )
		print(f'''Filtered dataset size: {len(__lowercase     )}'''     )

		return ds_filter, duplicate_clusters







import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402


_UpperCAmelCase            =		{
    """return_dict""": False,
    """output_hidden_states""": True,
    """output_attentions""": True,
    """torchscript""": True,
    """torch_dtype""": """float16""",
    """use_bfloat16""": True,
    """tf_legacy_loss""": True,
    """pruned_heads""": {"""a""": 1},
    """tie_word_embeddings""": False,
    """is_decoder""": True,
    """cross_attention_hidden_size""": 128,
    """add_cross_attention""": True,
    """tie_encoder_decoder""": True,
    """max_length""": 50,
    """min_length""": 3,
    """do_sample""": True,
    """early_stopping""": True,
    """num_beams""": 3,
    """num_beam_groups""": 3,
    """diversity_penalty""": 0.5,
    """temperature""": 2.0,
    """top_k""": 10,
    """top_p""": 0.7,
    """typical_p""": 0.2,
    """repetition_penalty""": 0.8,
    """length_penalty""": 0.8,
    """no_repeat_ngram_size""": 5,
    """encoder_no_repeat_ngram_size""": 5,
    """bad_words_ids""": [1, 2, 3],
    """num_return_sequences""": 3,
    """chunk_size_feed_forward""": 5,
    """output_scores""": True,
    """return_dict_in_generate""": True,
    """forced_bos_token_id""": 2,
    """forced_eos_token_id""": 3,
    """remove_invalid_values""": True,
    """architectures""": ["""BertModel"""],
    """finetuning_task""": """translation""",
    """id2label""": {0: """label"""},
    """label2id""": {"""label""": """0"""},
    """tokenizer_class""": """BertTokenizerFast""",
    """prefix""": """prefix""",
    """bos_token_id""": 6,
    """pad_token_id""": 7,
    """eos_token_id""": 8,
    """sep_token_id""": 9,
    """decoder_start_token_id""": 10,
    """exponential_decay_length_penalty""": (5, 1.01),
    """suppress_tokens""": [0, 1],
    """begin_suppress_tokens""": 2,
    """task_specific_params""": {"""translation""": """some_params"""},
    """problem_type""": """regression""",
}





@is_staging_test
class UpperCAmelCase						( unittest.TestCase  ):


				'''simple docstring'''






				@classmethod
				def   lowerCAmelCase_       (						cls ):



						"""simple docstring"""





						A_		:    Optional[int]         =				TOKEN
						HfFolder.save_token(lowercase )
				@classmethod
				def   lowerCAmelCase_       (						cls ):



						"""simple docstring"""





						try:
								delete_repo(token=cls._token		,     repo_id='test-config' )
						except HTTPError:
								pass

						try:
								delete_repo(token=cls._token		,     repo_id='valid_org/test-config-org' )
						except HTTPError:
								pass

						try:
								delete_repo(token=cls._token		,     repo_id='test-dynamic-config' )
						except HTTPError:
								pass
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Union[str, Any]         =				BertConfig(
						    vocab_size=9_9		,     hidden_size=3_2		,     num_hidden_layers=5		,     num_attention_heads=4		,     intermediate_size=3_7 )
						config.push_to_hub('test-config'		,     use_auth_token=self._token )

						A_		:    Dict         =				BertConfig.from_pretrained(F'''{USER}/test-config''' )
						for k, v in config.to_dict().items():
								if k != "transformers_version":
										self.assertEqual(lowercase		,     getattr(lowercase		,     lowercase ) )

        # Reset repo
						delete_repo(token=self._token		,     repo_id='test-config' )

						# Push to hub via save_pretrained
						with tempfile.TemporaryDirectory() as tmp_dir:
								config.save_pretrained(lowercase		,     repo_id='test-config'		,     push_to_hub=lowercase		,     use_auth_token=self._token )

						A_		:    Dict         =				BertConfig.from_pretrained(F'''{USER}/test-config''' )
						for k, v in config.to_dict().items():
								if k != "transformers_version":
										self.assertEqual(lowercase		,     getattr(lowercase		,     lowercase ) )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    List[str]         =				BertConfig(
						    vocab_size=9_9		,     hidden_size=3_2		,     num_hidden_layers=5		,     num_attention_heads=4		,     intermediate_size=3_7 )
						config.push_to_hub('valid_org/test-config-org'		,     use_auth_token=self._token )

						A_		:    List[Any]         =				BertConfig.from_pretrained('valid_org/test-config-org' )
						for k, v in config.to_dict().items():
								if k != "transformers_version":
										self.assertEqual(lowercase		,     getattr(lowercase		,     lowercase ) )

        # Reset repo
						delete_repo(token=self._token		,     repo_id='valid_org/test-config-org' )

						# Push to hub via save_pretrained
						with tempfile.TemporaryDirectory() as tmp_dir:
								config.save_pretrained(
								    lowercase		,     repo_id='valid_org/test-config-org'		,     push_to_hub=lowercase		,     use_auth_token=self._token )

						A_		:    Optional[Any]         =				BertConfig.from_pretrained('valid_org/test-config-org' )
						for k, v in config.to_dict().items():
								if k != "transformers_version":
										self.assertEqual(lowercase		,     getattr(lowercase		,     lowercase ) )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						CustomConfig.register_for_auto_class()
						A_		:    Optional[int]         =				CustomConfig(attribute=4_2 )

						config.push_to_hub('test-dynamic-config'		,     use_auth_token=self._token )

						# This has added the proper auto_map field to the config
						self.assertDictEqual(config.auto_map		,     {'AutoConfig': 'custom_configuration.CustomConfig'} )

						A_		:    Optional[int]         =				AutoConfig.from_pretrained(F'''{USER}/test-dynamic-config'''		,     trust_remote_code=lowercase )
						# Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
						self.assertEqual(new_config.__class__.__name__		,     'CustomConfig' )
						self.assertEqual(new_config.attribute		,     4_2 )





class UpperCAmelCase						( unittest.TestCase  ):


				'''simple docstring'''






				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    int         =				GPTaConfig()

						# attempt to modify each of int/float/bool/str config records and verify they were updated
						A_		:    Optional[int]         =				c.n_embd + 1  # int
						A_		:    List[str]         =				c.resid_pdrop + 1.0  # float
						A_		:    str         =				not c.scale_attn_weights  # bool
						A_		:    Optional[int]         =				c.summary_type + 'foo'  # str
						c.update_from_string(
						    F'''n_embd={n_embd},resid_pdrop={resid_pdrop},scale_attn_weights={scale_attn_weights},summary_type={summary_type}''' )
						self.assertEqual(lowercase		,     c.n_embd		,     'mismatch for key: n_embd' )
						self.assertEqual(lowercase		,     c.resid_pdrop		,     'mismatch for key: resid_pdrop' )
						self.assertEqual(lowercase		,     c.scale_attn_weights		,     'mismatch for key: scale_attn_weights' )
						self.assertEqual(lowercase		,     c.summary_type		,     'mismatch for key: summary_type' )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Optional[int]         =				PretrainedConfig()
						A_		:    int         =				[key for key in base_config.__dict__ if key not in config_common_kwargs]
						# If this part of the test fails, you have arguments to addin config_common_kwargs above.
						self.assertListEqual(
						    lowercase		,     ['is_encoder_decoder', '_name_or_path', '_commit_hash', 'transformers_version'] )
						A_		:    List[str]         =				[key for key, value in config_common_kwargs.items() if value == getattr(lowercase		,     lowercase )]
						if len(lowercase ) > 0:
								raise ValueError(
								    'The following keys are set with the default values in'
								    ' `test_configuration_common.config_common_kwargs` pick another value for them:'
								    F''' {', '.join(lowercase )}.''' )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						with self.assertRaises(lowercase ):
								# config is in subfolder, the following should not work without specifying the subfolder
								A_		:    Union[str, Any]         =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder' )

						A_		:    Optional[int]         =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder'		,     subfolder='bert' )

						self.assertIsNotNone(lowercase )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    int         =				mock.Mock()
						A_		:    int         =				5_0_0
						A_		:    Union[str, Any]         =				{}
						A_		:    List[str]         =				HTTPError
						A_		:    List[Any]         =				{}

						# Download this model to make sure it's in the cache.
						A_		:    Tuple         =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert' )

						# Under the mock environment we get a 500 error when trying to reach the model.
						with mock.patch('requests.Session.request'		,     return_value=lowercase ) as mock_head:
								A_		:    Optional[int]         =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert' )
								# This check we did call the fake head request
								mock_head.assert_called()
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Any         =				BertConfig.from_pretrained(
						    'https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json' )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    int         =				AutoConfig.from_pretrained('bert-base-cased' )
						A_		:    Tuple         =				['config.4.0.0.json']

						with tempfile.TemporaryDirectory() as tmp_dir:
								configuration.save_pretrained(lowercase )
								A_		:    Dict         =				2
								json.dump(configuration.to_dict()		,     open(os.path.join(lowercase		,     'config.4.0.0.json' )		,     'w' ) )

								# This should pick the new configuration file as the version of Transformers is > 4.0.0
								A_		:    Tuple         =				AutoConfig.from_pretrained(lowercase )
								self.assertEqual(new_configuration.hidden_size		,     2 )

								# Will need to be adjusted if we reach v42 and this test is still here.
								# Should pick the old configuration file as the version of Transformers is < 4.42.0
								A_		:    int         =				['config.42.0.0.json']
								A_		:    str         =				7_6_8
								configuration.save_pretrained(lowercase )
								shutil.move(os.path.join(lowercase		,     'config.4.0.0.json' )		,     os.path.join(lowercase		,     'config.42.0.0.json' ) )
								A_		:    str         =				AutoConfig.from_pretrained(lowercase )
								self.assertEqual(new_configuration.hidden_size		,     7_6_8 )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    List[Any]         =				'hf-internal-testing/test-two-configs'

						import transformers as new_transformers

						A_		:    List[Any]         =				'v4.0.0'
						A_       ,      A_		:    List[str]         =				new_transformers.models.auto.AutoConfig.from_pretrained(
						    lowercase		,     return_unused_kwargs=lowercase )
						self.assertEqual(new_configuration.hidden_size		,     2 )
						# This checks `_configuration_file` ia not kept in the kwargs by mistake.
						self.assertDictEqual(lowercase		,     {} )

						# Testing an older version by monkey-patching the version in the module it's used.
						import transformers as old_transformers

						A_		:    Optional[int]         =				'v3.0.0'
						A_		:    List[Any]         =				old_transformers.models.auto.AutoConfig.from_pretrained(lowercase )
						self.assertEqual(old_configuration.hidden_size		,     7_6_8 )






