




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 			_UpperCamelCase      (				lowerCAmelCase	,       unittest.TestCase		):
      UpperCAmelCase_        =		CodeGenTokenizer
      UpperCAmelCase_        =		CodeGenTokenizerFast
      UpperCAmelCase_        =		True
      UpperCAmelCase_        =		{"""add_prefix_space""": True}
      UpperCAmelCase_        =		False
      def 	UpperCAmelCase_						(			self   :List[Any]      )     ->			List[Any]:
       super().setUp()

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

       UpperCAmelCase__							 =						os.path.join(self.tmpdirname ,      VOCAB_FILES_NAMES["vocab_file"]      )
       UpperCAmelCase__							 =						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(lowerCamelCase      ) + "\n"      )
       with open(self.merges_file ,      "w" ,      encoding="utf-8"      ) as fp:
        fp.write("\n".join(lowerCamelCase      )      )
      def 	UpperCAmelCase_						(			self   :Union[str, Any] ,      **lowerCamelCase   :Dict      )     ->			List[Any]:
       kwargs.update(self.special_tokens_map      )
       return CodeGenTokenizer.from_pretrained(self.tmpdirname ,      **lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Optional[Any] ,      **lowerCamelCase   :str      )     ->			int:
       kwargs.update(self.special_tokens_map      )
       return CodeGenTokenizerFast.from_pretrained(self.tmpdirname ,      **lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Tuple ,      lowerCamelCase   :Union[str, Any]      )     ->			str:
       UpperCAmelCase__							 =						"lower newer"
       UpperCAmelCase__							 =						"lower newer"
       return input_text, output_text
      def 	UpperCAmelCase_						(			self   :int      )     ->			Dict:
       UpperCAmelCase__							 =						CodeGenTokenizer(self.vocab_file ,      self.merges_file ,      **self.special_tokens_map      )
       UpperCAmelCase__							 =						"lower newer"
       UpperCAmelCase__							 =						["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
       UpperCAmelCase__							 =						tokenizer.tokenize(lowerCamelCase ,      add_prefix_space=lowerCamelCase      )
       self.assertListEqual(lowerCamelCase ,      lowerCamelCase      )

       UpperCAmelCase__							 =						tokens + [tokenizer.unk_token]
       UpperCAmelCase__							 =						[14, 15, 10, 9, 3, 2, 15, 19]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase      ) ,      lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :str      )     ->			List[str]:
       if not self.test_rust_tokenizer:
        return

       UpperCAmelCase__							 =						self.get_tokenizer()
       UpperCAmelCase__							 =						self.get_rust_tokenizer(add_prefix_space=lowerCamelCase      )

       UpperCAmelCase__							 =						"lower newer"

       # Testing tokenization
       UpperCAmelCase__							 =						tokenizer.tokenize(lowerCamelCase ,      add_prefix_space=lowerCamelCase      )
       UpperCAmelCase__							 =						rust_tokenizer.tokenize(lowerCamelCase      )
       self.assertListEqual(lowerCamelCase ,      lowerCamelCase      )

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

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

       # Testing the unknown token
       UpperCAmelCase__							 =						tokens + [rust_tokenizer.unk_token]
       UpperCAmelCase__							 =						[14, 15, 10, 9, 3, 2, 15, 19]
       self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowerCamelCase      ) ,      lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Tuple ,      *lowerCamelCase   :Optional[Any] ,      **lowerCamelCase   :Tuple      )     ->			str:
       # 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 	UpperCAmelCase_						(			self   :Tuple ,      lowerCamelCase   :int=15      )     ->			str:
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
         UpperCAmelCase__							 =						self.rust_tokenizer_class.from_pretrained(lowerCamelCase ,      **lowerCamelCase      )

         # Simple input
         UpperCAmelCase__							 =						"This is a simple input"
         UpperCAmelCase__							 =						["This is a simple input 1", "This is a simple input 2"]
         UpperCAmelCase__							 =						("This is a simple input", "This is a pair")
         UpperCAmelCase__							 =						[
             ("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(lowerCamelCase ,      tokenizer_r.encode ,      lowerCamelCase ,      max_length=lowerCamelCase ,      padding="max_length"      )

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

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

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

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

         # Pair input
         self.assertRaises(
             lowerCamelCase ,      tokenizer_r.batch_encode_plus ,      lowerCamelCase ,      max_length=lowerCamelCase ,      padding="max_length" ,      )
      def 	UpperCAmelCase_						(			self   :str      )     ->			List[str]:
       UpperCAmelCase__							 =						CodeGenTokenizer.from_pretrained(self.tmpdirname ,      pad_token="<pad>"      )

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

       UpperCAmelCase__							 =						tokenizer.pad_token_id

       UpperCAmelCase__							 =						tokenizer(lowerCamelCase ,      padding="max_length" ,      max_length=30 ,      return_tensors="np"      )
       UpperCAmelCase__							 =						tokenizer(lowerCamelCase ,      padding=lowerCamelCase ,      truncate=lowerCamelCase ,      return_tensors="np"      )
       UpperCAmelCase__							 =						tokenizer(*lowerCamelCase ,      padding="max_length" ,      max_length=60 ,      return_tensors="np"      )
       UpperCAmelCase__							 =						tokenizer(lowerCamelCase ,      padding=lowerCamelCase ,      truncate=lowerCamelCase ,      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 	UpperCAmelCase_						(			self   :Dict      )     ->			Optional[int]:
       UpperCAmelCase__							 =						"$$$"
       UpperCAmelCase__							 =						CodeGenTokenizer.from_pretrained(self.tmpdirname ,      bos_token=lowerCamelCase ,      add_bos_token=lowerCamelCase      )

       UpperCAmelCase__							 =						"This is a simple input"
       UpperCAmelCase__							 =						["This is a simple input 1", "This is a simple input 2"]

       UpperCAmelCase__							 =						tokenizer.bos_token_id

       UpperCAmelCase__							 =						tokenizer(lowerCamelCase      )
       UpperCAmelCase__							 =						tokenizer(lowerCamelCase      )

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

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

       self.assertEqual(decode_s.split()[0] ,      lowerCamelCase      )
       self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )
      @slow
      def 	UpperCAmelCase_						(			self   :str      )     ->			Optional[Any]:
       UpperCAmelCase__							 =						CodeGenTokenizer.from_pretrained("Salesforce/codegen-350M-mono"      )

       UpperCAmelCase__							 =						"\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"
       UpperCAmelCase__							 =						"\nif len_a > len_b:      result = a\nelse:      result = b"

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







      def 	UpperCAmelCase_						(			self   :Dict      )     ->			int:
       pass











import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_lowerCAmelCase						:   List[Any]		=   ["small", "medium", "large"]

_lowerCAmelCase						:   List[Any]		=   "lm_head.decoder.weight"
_lowerCAmelCase						:   Optional[int]		=   "lm_head.weight"



def 						lowerCAmelCase		(		_lowerCAmelCase							:   str						,							_lowerCAmelCase							:   str	):




 """simple docstring"""







 UpperCAmelCase__							 =						torch.load(_lowerCAmelCase	)
 UpperCAmelCase__							 =						d.pop(_lowerCAmelCase	)
 os.makedirs(_lowerCAmelCase						,							exist_ok=_lowerCAmelCase	)
 torch.save(_lowerCAmelCase						,							os.path.join(_lowerCAmelCase						,							_lowerCAmelCase	)	)


if __name__ == "__main__":
  _lowerCAmelCase						:   Dict		=   argparse.ArgumentParser()
  parser.add_argument("--dialogpt_path", default=".", type=str)
  _lowerCAmelCase						:   Union[str, Any]		=   parser.parse_args()
  for MODEL in DIALOGPT_MODELS:
    _lowerCAmelCase						:   Union[str, Any]		=   os.path.join(args.dialogpt_path, F'''{MODEL}_ft.pkl''')
    _lowerCAmelCase						:   List[str]		=   F'''./DialoGPT-{MODEL}'''
    convert_dialogpt_checkpoint(
        checkpoint_path,
        pytorch_dump_folder_path,
    )





