
import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




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





	'''simple docstring'''



	_UpperCAmelCase			:						Optional[Any]         =   CodeGenTokenizer
	_UpperCAmelCase			:						Optional[Any]         =   CodeGenTokenizerFast
	_UpperCAmelCase			:						Union[str, Any]         =   True
	_UpperCAmelCase			:						Dict         =   {'add_prefix_space': True}
	_UpperCAmelCase			:						Dict         =   False



	def 					A				(    self      :       Union[str, Any]      ):


				'''simple docstring'''


				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				_snake_case            =     [
				    'l',
				    'o',
				    'w',
				    'e',
				    'r',
				    's',
				    't',
				    'i',
				    'd',
				    'n',
				    '\u0120',
				    '\u0120l',
				    '\u0120n',
				    '\u0120lo',
				    '\u0120low',
				    'er',
				    '\u0120lowest',
				    '\u0120newer',
				    '\u0120wider',
				    '<unk>',
				    '<|endoftext|>',
				]
				_snake_case            =     dict(zip(lowercase     ,    range(len(lowercase      )      )      )      )
				_snake_case            =     ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
				_snake_case            =     {'unk_token': '<unk>'}

				_snake_case            =     os.path.join(self.tmpdirname     ,    VOCAB_FILES_NAMES['vocab_file']      )
				_snake_case            =     os.path.join(self.tmpdirname     ,    VOCAB_FILES_NAMES['merges_file']      )
				with open(self.vocab_file     ,    'w'     ,    encoding='utf-8'      ) as fp:
							fp.write(json.dumps(lowercase      ) + '\n'      )
				with open(self.merges_file     ,    'w'     ,    encoding='utf-8'      ) as fp:
							fp.write('\n'.join(lowercase      )      )



	def 					A				(    self      :       Optional[int]     ,    **lowercase      :       Dict      ):


				'''simple docstring'''


				kwargs.update(self.special_tokens_map      )
				return CodeGenTokenizer.from_pretrained(self.tmpdirname     ,    **lowercase      )



	def 					A				(    self      :       List[Any]     ,    **lowercase      :       int      ):


				'''simple docstring'''


				kwargs.update(self.special_tokens_map      )
				return CodeGenTokenizerFast.from_pretrained(self.tmpdirname     ,    **lowercase      )



	def 					A				(    self      :       Tuple     ,    lowercase      :       List[str]      ):


				'''simple docstring'''


				_snake_case            =     'lower newer'
				_snake_case            =     'lower newer'
				return input_text, output_text



	def 					A				(    self      :       Optional[int]      ):


				'''simple docstring'''


				_snake_case            =     CodeGenTokenizer(self.vocab_file     ,    self.merges_file     ,    **self.special_tokens_map      )
				_snake_case            =     'lower newer'
				_snake_case            =     ['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
				_snake_case            =     tokenizer.tokenize(lowercase     ,    add_prefix_space=lowercase      )
				self.assertListEqual(lowercase     ,    lowercase      )

				_snake_case            =     tokens + [tokenizer.unk_token]
				_snake_case            =     [14, 15, 10, 9, 3, 2, 15, 19]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase      )     ,    lowercase      )



	def 					A				(    self      :       str      ):


				'''simple docstring'''


				if not self.test_rust_tokenizer:
							return

				_snake_case            =     self.get_tokenizer()
				_snake_case            =     self.get_rust_tokenizer(add_prefix_space=lowercase      )

				_snake_case            =     'lower newer'

				# Testing tokenization
				_snake_case            =     tokenizer.tokenize(lowercase     ,    add_prefix_space=lowercase      )
				_snake_case            =     rust_tokenizer.tokenize(lowercase      )
				self.assertListEqual(lowercase     ,    lowercase      )

				# Testing conversion to ids without special tokens
				_snake_case            =     tokenizer.encode(lowercase     ,    add_special_tokens=lowercase     ,    add_prefix_space=lowercase      )
				_snake_case            =     rust_tokenizer.encode(lowercase     ,    add_special_tokens=lowercase      )
				self.assertListEqual(lowercase     ,    lowercase      )

				# Testing conversion to ids with special tokens
				_snake_case            =     self.get_rust_tokenizer(add_prefix_space=lowercase      )
				_snake_case            =     tokenizer.encode(lowercase     ,    add_prefix_space=lowercase      )
				_snake_case            =     rust_tokenizer.encode(lowercase      )
				self.assertListEqual(lowercase     ,    lowercase      )

				# Testing the unknown token
				_snake_case            =     tokens + [rust_tokenizer.unk_token]
				_snake_case            =     [14, 15, 10, 9, 3, 2, 15, 19]
				self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowercase      )     ,    lowercase      )



	def 					A				(    self      :       Tuple     ,    *lowercase      :       Dict     ,    **lowercase      :       Tuple      ):


				'''simple docstring'''


				pass



	def 					A				(    self      :       Optional[int]     ,    lowercase      :       Any=15      ):


				'''simple docstring'''


				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
										_snake_case            =     self.rust_tokenizer_class.from_pretrained(lowercase     ,    **lowercase      )

										# Simple input
										_snake_case            =     'This is a simple input'
										_snake_case            =     ['This is a simple input 1', 'This is a simple input 2']
										_snake_case            =     ('This is a simple input', 'This is a pair')
										_snake_case            =     [
										    ('This is a simple input 1', 'This is a simple input 2'),
										    ('This is a simple pair 1', 'This is a simple pair 2'),
										]

										# Simple input tests
										self.assertRaises(lowercase     ,    tokenizer_r.encode     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'      )

										# Simple input
										self.assertRaises(lowercase     ,    tokenizer_r.encode_plus     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'      )

										# Simple input
										self.assertRaises(
										    lowercase     ,    tokenizer_r.batch_encode_plus     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'     ,    )

										# Pair input
										self.assertRaises(lowercase     ,    tokenizer_r.encode     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'      )

										# Pair input
										self.assertRaises(lowercase     ,    tokenizer_r.encode_plus     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'      )

										# Pair input
										self.assertRaises(
										    lowercase     ,    tokenizer_r.batch_encode_plus     ,    lowercase     ,    max_length=lowercase     ,    padding='max_length'     ,    )



	def 					A				(    self      :       Optional[Any]      ):


				'''simple docstring'''


				_snake_case            =     CodeGenTokenizer.from_pretrained(self.tmpdirname     ,    pad_token='<pad>'      )

				# Simple input
				_snake_case            =     'This is a simple input'
				_snake_case            =     ['This is a simple input looooooooong', 'This is a simple input']
				_snake_case            =     ('This is a simple input', 'This is a pair')
				_snake_case            =     [
				    ('This is a simple input loooooong', 'This is a simple input'),
				    ('This is a simple pair loooooong', 'This is a simple pair'),
				]

				_snake_case            =     tokenizer.pad_token_id

				_snake_case            =     tokenizer(lowercase     ,    padding='max_length'     ,    max_length=30     ,    return_tensors='np'      )
				_snake_case            =     tokenizer(lowercase     ,    padding=lowercase     ,    truncate=lowercase     ,    return_tensors='np'      )
				_snake_case            =     tokenizer(*lowercase     ,    padding='max_length'     ,    max_length=60     ,    return_tensors='np'      )
				_snake_case            =     tokenizer(lowercase     ,    padding=lowercase     ,    truncate=lowercase     ,    return_tensors='np'      )

				# s
				# test single string max_length padding
				self.assertEqual(out_s['input_ids'].shape[-1]     ,    30      )
				self.assertTrue(pad_token_id in out_s['input_ids']      )
				self.assertTrue(0 in out_s['attention_mask']      )

				# s2
				# test automatic padding
				self.assertEqual(out_sa['input_ids'].shape[-1]     ,    33      )
				# long slice doesn't have padding
				self.assertFalse(pad_token_id in out_sa['input_ids'][0]      )
				self.assertFalse(0 in out_sa['attention_mask'][0]      )
				# short slice does have padding
				self.assertTrue(pad_token_id in out_sa['input_ids'][1]      )
				self.assertTrue(0 in out_sa['attention_mask'][1]      )

				# p
				# test single pair max_length padding
				self.assertEqual(out_p['input_ids'].shape[-1]     ,    60      )
				self.assertTrue(pad_token_id in out_p['input_ids']      )
				self.assertTrue(0 in out_p['attention_mask']      )

				# p2
				# test automatic padding pair
				self.assertEqual(out_pa['input_ids'].shape[-1]     ,    52      )
				# long slice pair doesn't have padding
				self.assertFalse(pad_token_id in out_pa['input_ids'][0]      )
				self.assertFalse(0 in out_pa['attention_mask'][0]      )
				# short slice pair does have padding
				self.assertTrue(pad_token_id in out_pa['input_ids'][1]      )
				self.assertTrue(0 in out_pa['attention_mask'][1]      )



	def 					A				(    self      :       str      ):


				'''simple docstring'''


				_snake_case            =     '$$$'
				_snake_case            =     CodeGenTokenizer.from_pretrained(self.tmpdirname     ,    bos_token=lowercase     ,    add_bos_token=lowercase      )

				_snake_case            =     'This is a simple input'
				_snake_case            =     ['This is a simple input 1', 'This is a simple input 2']

				_snake_case            =     tokenizer.bos_token_id

				_snake_case            =     tokenizer(lowercase      )
				_snake_case            =     tokenizer(lowercase      )

				self.assertEqual(out_s.input_ids[0]     ,    lowercase      )
				self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

				_snake_case            =     tokenizer.decode(out_s.input_ids      )
				_snake_case            =     tokenizer.batch_decode(out_sa.input_ids      )

				self.assertEqual(decode_s.split()[0]     ,    lowercase      )
				self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )



	@slow
	def 					A				(    self      :       List[str]      ):


				'''simple docstring'''


				_snake_case            =     CodeGenTokenizer.from_pretrained('Salesforce/codegen-350M-mono'      )

				_snake_case            =     '\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#'
				_snake_case            =     '\nif len_a > len_b:      result = a\nelse:      result = b'

				_snake_case            =     tokenizer.encode(lowercase      )
				_snake_case            =     ['^#', re.escape('<|endoftext|>'      ), '^\'\'\'', '^"""', '\n\n\n']
				_snake_case            =     tokenizer.decode(lowercase     ,    truncate_before_pattern=lowercase      )
				self.assertEqual(lowercase     ,    lowercase      )





	def 					A				(    self      :       Optional[Any]      ):


				'''simple docstring'''


				pass






import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_lowercase		:  List[str]			       =5_0000
_lowercase		:  str			       =5000

_lowercase       , _lowercase		:  List[str]			       =os.path.split(__file__)
_lowercase		:  Union[str, Any]			       =os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))


@get_duration
def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__						):
		for i in range(lowerCAmelCase__						):
				lowerCamelCase_	:     Tuple 						=      dataset[i]


@get_duration
def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		for i in range(0							,len(lowerCAmelCase__						)							,lowerCAmelCase__						):
				lowerCamelCase_	:     Tuple 						=      dataset[i : i + batch_size]


@get_duration
def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		with dataset.formatted_as(type=lowerCAmelCase__						):
				for i in range(lowerCAmelCase__						):
						lowerCamelCase_	:     Tuple 						=      dataset[i]


@get_duration
def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		with dataset.formatted_as(type=lowerCAmelCase__						):
				for i in range(0							,lowerCAmelCase__							,lowerCAmelCase__						):
						lowerCamelCase_	:     Optional[int] 						=      dataset[i : i + batch_size]


def 		_SCREAMING_SNAKE_CASE     ( ):
		lowerCamelCase_	:     Any 						=      {'num examples': SPEED_TEST_N_EXAMPLES}
		lowerCamelCase_	:     Optional[Any] 						=      [
		    (read, {'length': SMALL_TEST}),
		    (read, {'length': SPEED_TEST_N_EXAMPLES}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_00}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10_00}),
		    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
		    (read_formatted, {'type': 'pandas', 'length': SMALL_TEST}),
		    (read_formatted, {'type': 'torch', 'length': SMALL_TEST}),
		    (read_formatted, {'type': 'tensorflow', 'length': SMALL_TEST}),
		    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
		    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10_00}),
		]

		lowerCamelCase_	:     Optional[Any] 						=      [
		    (read, {'length': SMALL_TEST}),
		    (read, {'length': SPEED_TEST_N_EXAMPLES}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_00}),
		    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10_00}),
		    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
		    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
		    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10_00}),
		]
		with tempfile.TemporaryDirectory() as tmp_dir:
				print('generating dataset'						)
				lowerCamelCase_	:     List[Any] 						=      datasets.Features(
				    {'list': datasets.Sequence(datasets.Value('float32'						)						), 'numbers': datasets.Value('float32'						)}						)
				lowerCamelCase_	:     Union[str, Any] 						=      generate_example_dataset(
				    os.path.join(lowerCAmelCase__							,'dataset.arrow'						)							,lowerCAmelCase__							,num_examples=lowerCAmelCase__							,seq_shapes={'list': (1_00,)}							,)
				print('first set of iterations'						)
				for func, kwargs in functions:
						print(func.__name__							,str(lowerCAmelCase__						)						)
						lowerCamelCase_	:     Optional[int] 						=      func(lowerCAmelCase__							,**lowerCAmelCase__						)

				print('shuffling dataset'						)
				lowerCamelCase_	:     int 						=      dataset.shuffle()
				print('Second set of iterations (after shuffling'						)
				for func, kwargs in functions_shuffled:
						print('shuffled '							,func.__name__							,str(lowerCAmelCase__						)						)
						lowerCamelCase_	:     Optional[Any] 						=      func(
						    lowerCAmelCase__							,**lowerCAmelCase__						)

		with open(lowerCAmelCase__							,'wb'						) as f:
				f.write(json.dumps(lowerCAmelCase__						).encode('utf-8'						)						)


if __name__ == "__main__":  # useful to run the profiler
		benchmark_iterating()
