






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__						(    _UpperCamelCase			,       unittest.TestCase						):





					"""simple docstring"""






					a_     =		CodeGenTokenizer
					a_     =		CodeGenTokenizerFast
					a_     =		True
					a_     =		{'add_prefix_space': True}
					a_     =		False



					def 	_lowercase					( self					:  Any	):
						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						snake_case__			:				Dict       =  [
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "\u0120",
						    "\u0120l",
						    "\u0120n",
						    "\u0120lo",
						    "\u0120low",
						    "er",
						    "\u0120lowest",
						    "\u0120newer",
						    "\u0120wider",
						    "<unk>",
						    "<|endoftext|>",
						]
						snake_case__			:				Dict       =  dict(zip(_SCREAMING_SNAKE_CASE							,		range(len(_SCREAMING_SNAKE_CASE	)	)	)	)
						snake_case__			:				str       =  ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
						snake_case__			:				str       =  {"unk_token": "<unk>"}

						snake_case__			:				int       =  os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["vocab_file"]	)
						snake_case__			:				List[Any]       =  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(_SCREAMING_SNAKE_CASE	) + "\n"	)
						with open(self.merges_file							,		"w"							,		encoding="utf-8"	) as fp:
							fp.write("\n".join(_SCREAMING_SNAKE_CASE	)	)



					def 	_lowercase					( self					:  Optional[Any]							,		**__A					:  Union[str, Any]	):
						kwargs.update(self.special_tokens_map	)
						return CodeGenTokenizer.from_pretrained(self.tmpdirname							,		**_SCREAMING_SNAKE_CASE	)



					def 	_lowercase					( self					:  Optional[Any]							,		**__A					:  Tuple	):
						kwargs.update(self.special_tokens_map	)
						return CodeGenTokenizerFast.from_pretrained(self.tmpdirname							,		**_SCREAMING_SNAKE_CASE	)



					def 	_lowercase					( self					:  Dict							,		__A					:  str	):
						snake_case__			:				Optional[int]       =  "lower newer"
						snake_case__			:				Dict       =  "lower newer"
						return input_text, output_text



					def 	_lowercase					( self					:  Union[str, Any]	):
						snake_case__			:				str       =  CodeGenTokenizer(self.vocab_file							,		self.merges_file							,		**self.special_tokens_map	)
						snake_case__			:				Any       =  "lower newer"
						snake_case__			:				Any       =  ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
						snake_case__			:				Optional[Any]       =  tokenizer.tokenize(_SCREAMING_SNAKE_CASE							,		add_prefix_space=_SCREAMING_SNAKE_CASE	)
						self.assertListEqual(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE	)

						snake_case__			:				List[str]       =  tokens + [tokenizer.unk_token]
						snake_case__			:				List[Any]       =  [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE	)							,		_SCREAMING_SNAKE_CASE	)



					def 	_lowercase					( self					:  List[str]	):
						if not self.test_rust_tokenizer:
							return

						snake_case__			:				Union[str, Any]       =  self.get_tokenizer()
						snake_case__			:				List[Any]       =  self.get_rust_tokenizer(add_prefix_space=_SCREAMING_SNAKE_CASE	)

						snake_case__			:				Any       =  "lower newer"

						# Testing tokenization
						snake_case__			:				List[str]       =  tokenizer.tokenize(_SCREAMING_SNAKE_CASE							,		add_prefix_space=_SCREAMING_SNAKE_CASE	)
						snake_case__			:				List[Any]       =  rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE	)
						self.assertListEqual(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE	)

						# Testing conversion to ids without special tokens
						snake_case__			:				Optional[int]       =  tokenizer.encode(_SCREAMING_SNAKE_CASE							,		add_special_tokens=_SCREAMING_SNAKE_CASE							,		add_prefix_space=_SCREAMING_SNAKE_CASE	)
						snake_case__			:				str       =  rust_tokenizer.encode(_SCREAMING_SNAKE_CASE							,		add_special_tokens=_SCREAMING_SNAKE_CASE	)
						self.assertListEqual(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE	)

						# Testing conversion to ids with special tokens
						snake_case__			:				Union[str, Any]       =  self.get_rust_tokenizer(add_prefix_space=_SCREAMING_SNAKE_CASE	)
						snake_case__			:				List[Any]       =  tokenizer.encode(_SCREAMING_SNAKE_CASE							,		add_prefix_space=_SCREAMING_SNAKE_CASE	)
						snake_case__			:				Tuple       =  rust_tokenizer.encode(_SCREAMING_SNAKE_CASE	)
						self.assertListEqual(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE	)

						# Testing the unknown token
						snake_case__			:				int       =  tokens + [rust_tokenizer.unk_token]
						snake_case__			:				Union[str, Any]       =  [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
						self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE	)							,		_SCREAMING_SNAKE_CASE	)



					def 	_lowercase					( self					:  Union[str, Any]							,		*__A					:  str							,		**__A					:  Dict	):
						# It's very difficult to mix/test pretokenization with byte-level
						# And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
						pass



					def 	_lowercase					( self					:  str							,		__A					:  Dict=1_5	):
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
								snake_case__			:				Union[str, Any]       =  self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE							,		**_SCREAMING_SNAKE_CASE	)

								# Simple input
								snake_case__			:				Optional[Any]       =  "This is a simple input"
								snake_case__			:				Tuple       =  ["This is a simple input 1", "This is a simple input 2"]
								snake_case__			:				Any       =  ("This is a simple input", "This is a pair")
								snake_case__			:				int       =  [
								    ("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(_SCREAMING_SNAKE_CASE							,		tokenizer_r.encode							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"	)

								# Simple input
								self.assertRaises(_SCREAMING_SNAKE_CASE							,		tokenizer_r.encode_plus							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"	)

								# Simple input
								self.assertRaises(
								    _SCREAMING_SNAKE_CASE							,		tokenizer_r.batch_encode_plus							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"							,		)

								# Pair input
								self.assertRaises(_SCREAMING_SNAKE_CASE							,		tokenizer_r.encode							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"	)

								# Pair input
								self.assertRaises(_SCREAMING_SNAKE_CASE							,		tokenizer_r.encode_plus							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"	)

								# Pair input
								self.assertRaises(
								    _SCREAMING_SNAKE_CASE							,		tokenizer_r.batch_encode_plus							,		_SCREAMING_SNAKE_CASE							,		max_length=_SCREAMING_SNAKE_CASE							,		padding="max_length"							,		)



					def 	_lowercase					( self					:  Any	):
						snake_case__			:				Any       =  CodeGenTokenizer.from_pretrained(self.tmpdirname							,		pad_token="<pad>"	)

						# Simple input
						snake_case__			:				Dict       =  "This is a simple input"
						snake_case__			:				Optional[Any]       =  ["This is a simple input looooooooong", "This is a simple input"]
						snake_case__			:				Dict       =  ("This is a simple input", "This is a pair")
						snake_case__			:				Dict       =  [
						    ("This is a simple input loooooong", "This is a simple input"),
						    ("This is a simple pair loooooong", "This is a simple pair"),
						]

						snake_case__			:				int       =  tokenizer.pad_token_id

						snake_case__			:				int       =  tokenizer(_SCREAMING_SNAKE_CASE							,		padding="max_length"							,		max_length=3_0							,		return_tensors="np"	)
						snake_case__			:				Tuple       =  tokenizer(_SCREAMING_SNAKE_CASE							,		padding=_SCREAMING_SNAKE_CASE							,		truncate=_SCREAMING_SNAKE_CASE							,		return_tensors="np"	)
						snake_case__			:				Dict       =  tokenizer(*_SCREAMING_SNAKE_CASE							,		padding="max_length"							,		max_length=6_0							,		return_tensors="np"	)
						snake_case__			:				int       =  tokenizer(_SCREAMING_SNAKE_CASE							,		padding=_SCREAMING_SNAKE_CASE							,		truncate=_SCREAMING_SNAKE_CASE							,		return_tensors="np"	)

						# s
						# test single string max_length padding
						self.assertEqual(out_s["input_ids"].shape[-1]							,		3_0	)
						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]							,		3_3	)
						# 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]							,		6_0	)
						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]							,		5_2	)
						# 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 	_lowercase					( self					:  List[str]	):
						snake_case__			:				List[str]       =  "$$$"
						snake_case__			:				Union[str, Any]       =  CodeGenTokenizer.from_pretrained(self.tmpdirname							,		bos_token=_SCREAMING_SNAKE_CASE							,		add_bos_token=_SCREAMING_SNAKE_CASE	)

						snake_case__			:				Tuple       =  "This is a simple input"
						snake_case__			:				Dict       =  ["This is a simple input 1", "This is a simple input 2"]

						snake_case__			:				str       =  tokenizer.bos_token_id

						snake_case__			:				Tuple       =  tokenizer(_SCREAMING_SNAKE_CASE	)
						snake_case__			:				str       =  tokenizer(_SCREAMING_SNAKE_CASE	)

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

						snake_case__			:				int       =  tokenizer.decode(out_s.input_ids	)
						snake_case__			:				List[Any]       =  tokenizer.batch_decode(out_sa.input_ids	)

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



					@slow
					def 	_lowercase					( self					:  int	):
						snake_case__			:				Dict       =  CodeGenTokenizer.from_pretrained("Salesforce/codegen-350M-mono"	)

						snake_case__			:				List[Any]       =  "\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"
						snake_case__			:				List[Any]       =  "\nif len_a > len_b:      result = a\nelse:      result = b"

						snake_case__			:				Any       =  tokenizer.encode(_SCREAMING_SNAKE_CASE	)
						snake_case__			:				List[str]       =  ["^#", re.escape("<|endoftext|>"	), "^\'\'\'", "^\"\"\"", "\n\n\n"]
						snake_case__			:				Optional[int]       =  tokenizer.decode(_SCREAMING_SNAKE_CASE							,		truncate_before_pattern=_SCREAMING_SNAKE_CASE	)
						self.assertEqual(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE	)






					def 	_lowercase					( self					:  Tuple	):
						pass











from datetime import datetime

import matplotlib.pyplot as plt
import torch







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							int       ):
	for param in module.parameters():
		snake_case__			:				Tuple       =  False







def 					SCREAMING_SNAKE_CASE    (			):
	snake_case__			:				Any       =  "cuda" if torch.cuda.is_available() else "cpu"
	if torch.backends.mps.is_available() and torch.backends.mps.is_built():
		snake_case__			:				List[Any]       =  "mps"
	if device == "mps":
		print(
		    "WARNING: MPS currently doesn't seem to work, and messes up backpropagation without any visible torch"
		    " errors. I recommend using CUDA on a colab notebook or CPU instead if you're facing inexplicable issues"
		    " with generations."       )
	return device







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							str       ):
	snake_case__			:				List[str]       =  plt.imshow(snake_case_       )
	fig.axes.get_xaxis().set_visible(snake_case_       )
	fig.axes.get_yaxis().set_visible(snake_case_       )
	plt.show()







def 					SCREAMING_SNAKE_CASE    (			):
	snake_case__			:				str       =  datetime.now()
	snake_case__			:				Optional[Any]       =  current_time.strftime("%H:%M:%S"       )
	return timestamp



