






"""simple docstring"""







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  lowerCamelCase__ (	lowerCamelCase__   ,					unittest.TestCase			):
				SCREAMING_SNAKE_CASE		=      CodeGenTokenizer
				SCREAMING_SNAKE_CASE		=      CodeGenTokenizerFast
				SCREAMING_SNAKE_CASE		=      True
				SCREAMING_SNAKE_CASE		=      {'''add_prefix_space''': True}
				SCREAMING_SNAKE_CASE		=      False






				def     _UpperCamelCase							(			self ):
										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(__snake_case     ,range(len(__snake_case ) ) ) )
										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(__snake_case ) + """\n""" )
										with open(self.merges_file     ,"""w"""     ,encoding="""utf-8""" ) as fp:
																fp.write("""\n""".join(__snake_case ) )






				def     _UpperCamelCase							(			self     ,**A ):
										kwargs.update(self.special_tokens_map )
										return CodeGenTokenizer.from_pretrained(self.tmpdirname     ,**__snake_case )






				def     _UpperCamelCase							(			self     ,**A ):
										kwargs.update(self.special_tokens_map )
										return CodeGenTokenizerFast.from_pretrained(self.tmpdirname     ,**__snake_case )






				def     _UpperCamelCase							(			self     ,A ):
										UpperCAmelCase          =	'lower newer'
										UpperCAmelCase          =	'lower newer'
										return input_text, output_text






				def     _UpperCamelCase							(			self ):
										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(__snake_case     ,add_prefix_space=__snake_case )
										self.assertListEqual(__snake_case     ,__snake_case )

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






				def     _UpperCamelCase							(			self ):
										if not self.test_rust_tokenizer:
																return

										UpperCAmelCase          =	self.get_tokenizer()
										UpperCAmelCase          =	self.get_rust_tokenizer(add_prefix_space=__snake_case )

										UpperCAmelCase          =	'lower newer'

										# Testing tokenization
										UpperCAmelCase          =	tokenizer.tokenize(__snake_case     ,add_prefix_space=__snake_case )
										UpperCAmelCase          =	rust_tokenizer.tokenize(__snake_case )
										self.assertListEqual(__snake_case     ,__snake_case )

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

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

										# 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(__snake_case )     ,__snake_case )






				def     _UpperCamelCase							(			self     ,*A     ,**A ):
										# 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     ,A=15 ):
										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(__snake_case     ,**__snake_case )

																						# 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(__snake_case     ,tokenizer_r.encode     ,__snake_case     ,max_length=__snake_case     ,padding="""max_length""" )

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

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

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

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

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






				def     _UpperCamelCase							(			self ):
										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(__snake_case     ,padding="""max_length"""     ,max_length=30     ,return_tensors="""np""" )
										UpperCAmelCase          =	tokenizer(__snake_case     ,padding=__snake_case     ,truncate=__snake_case     ,return_tensors="""np""" )
										UpperCAmelCase          =	tokenizer(*__snake_case     ,padding="""max_length"""     ,max_length=60     ,return_tensors="""np""" )
										UpperCAmelCase          =	tokenizer(__snake_case     ,padding=__snake_case     ,truncate=__snake_case     ,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 ):
										UpperCAmelCase          =	'$$$'
										UpperCAmelCase          =	CodeGenTokenizer.from_pretrained(self.tmpdirname     ,bos_token=__snake_case     ,add_bos_token=__snake_case )

										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(__snake_case )
										UpperCAmelCase          =	tokenizer(__snake_case )

										self.assertEqual(out_s.input_ids[0]     ,__snake_case )
										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]     ,__snake_case )
										self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa ) )






				@slow
				def     _UpperCamelCase							(			self ):
										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(__snake_case )
										UpperCAmelCase          =	['^#', re.escape("""<|endoftext|>""" ), '^\'\'\'', '^"""', '\n\n\n']
										UpperCAmelCase          =	tokenizer.decode(__snake_case     ,truncate_before_pattern=__snake_case )
										self.assertEqual(__snake_case     ,__snake_case )






				def     _UpperCamelCase							(			self ):
										pass











"""simple docstring"""







from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image


_UpperCamelCase					      =  ["""text""", """image""", """audio"""]

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]

      for input_type in input_types:
            if input_type == "text":
                  inputs.append("""Text input"""							)
            elif input_type == "image":
                  inputs.append(
                      Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""							)							) / """000000039769.png"""							).resize((512, 512)							)							)
            elif input_type == "audio":
                  inputs.append(torch.ones(3000							)							)
            elif isinstance(_snake_case				,	_snake_case							):
                  inputs.append(create_inputs(_snake_case							)							)
            else:
                  raise ValueError(F'''Invalid type requested: {input_type}'''							)

      return inputs

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]

      for output in outputs:
            if isinstance(_snake_case				,	(str, AgentText)							):
                  output_types.append("""text"""							)
            elif isinstance(_snake_case				,	(Image.Image, AgentImage)							):
                  output_types.append("""image"""							)
            elif isinstance(_snake_case				,	(torch.Tensor, AgentAudio)							):
                  output_types.append("""audio"""							)
            else:
                  raise ValueError(F'''Invalid output: {output}'''							)

      return output_types







@is_tool_test
class  lowerCamelCase__ :






    def     _UpperCamelCase							(			self ):
          self.assertTrue(hasattr(self.tool     ,"""inputs""" ) )
          self.assertTrue(hasattr(self.tool     ,"""outputs""" ) )

          UpperCAmelCase          =	self.tool.inputs
          for _input in inputs:
                if isinstance(_input     ,A ):
                      for __input in _input:
                            self.assertTrue(__input in authorized_types )
                else:
                      self.assertTrue(_input in authorized_types )

          UpperCAmelCase          =	self.tool.outputs
          for _output in outputs:
                self.assertTrue(_output in authorized_types )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )
          UpperCAmelCase          =	self.tool(*A )

          # There is a single output
          if len(self.tool.outputs ) == 1:
                UpperCAmelCase          =	[outputs]

          self.assertListEqual(output_types(A )     ,self.tool.outputs )






    def     _UpperCamelCase							(			self ):
          self.assertTrue(hasattr(self.tool     ,"""description""" ) )
          self.assertTrue(hasattr(self.tool     ,"""default_checkpoint""" ) )
          self.assertTrue(self.tool.description.startswith("""This is a tool that""" ) )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )
          UpperCAmelCase          =	self.tool(*A )

          if not isinstance(A     ,A ):
                UpperCAmelCase          =	[outputs]

          self.assertEqual(len(A )     ,len(self.tool.outputs ) )

          for output, output_type in zip(A     ,self.tool.outputs ):
                UpperCAmelCase          =	AGENT_TYPE_MAPPING[output_type]
                self.assertTrue(isinstance(A     ,A ) )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )

          UpperCAmelCase          =	[]

          for _input, input_type in zip(A     ,self.tool.inputs ):
                if isinstance(A     ,A ):
                      _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input ) for _input_type in input_type] )
                else:
                      _inputs.append(AGENT_TYPE_MAPPING[input_type](_input ) )

        # Should not raise an error
          UpperCAmelCase          =	self.tool(*A )

          if not isinstance(A     ,A ):
                UpperCAmelCase          =	[outputs]

          self.assertEqual(len(A )     ,len(self.tool.outputs ) )



