"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
     import torch


if is_vision_available():
     from PIL import Image

     from transformers import MgpstrProcessor, ViTImageProcessor



@require_torch
@require_vision
class 					lowerCAmelCase_      (     unittest.TestCase   ):



    """simple docstring"""
    _lowerCAmelCase       :      Union[str, Any]     					=  ViTImageProcessor if is_vision_available() else None

    @property
    def 						snake_case	(			self      ):






          """simple docstring"""

          return self.image_processor_tester.prepare_image_processor_dict()

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     (3, 32, 1_28)
          snake_case        =     tempfile.mkdtemp()

          # fmt: off
          snake_case        =     ['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
          # fmt: on
          snake_case        =     dict(zip(lowerCAmelCase						,      range(len(lowerCAmelCase      )      )      )      )

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

          snake_case        =     {
              'do_normalize': False,
              'do_resize': True,
              'image_processor_type': 'ViTImageProcessor',
              'resample': 3,
              'size': {'height': 32, 'width': 1_28},
          }
          snake_case        =     os.path.join(self.tmpdirname						,      lowerCAmelCase      )
          with open(self.image_processor_file						,      'w'						,      encoding='utf-8'      ) as fp:
                json.dump(lowerCAmelCase						,      lowerCAmelCase      )

    def 						snake_case	(			self						,      **lowerCAmelCase      ):






          """simple docstring"""

          return MgpstrTokenizer.from_pretrained(self.tmpdirname						,      **lowerCAmelCase      )

    def 						snake_case	(			self						,      **lowerCAmelCase      ):






          """simple docstring"""

          return ViTImageProcessor.from_pretrained(self.tmpdirname						,      **lowerCAmelCase      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          shutil.rmtree(self.tmpdirname      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     np.random.randint(2_55						,      size=(3, 30, 4_00)						,      dtype=np.uinta      )

          snake_case        =     Image.fromarray(np.moveaxis(lowerCAmelCase						,      0						,      -1      )      )

          return image_input

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_tokenizer()
          snake_case        =     self.get_image_processor()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )
          processor.save_pretrained(self.tmpdirname      )
          snake_case        =     MgpstrProcessor.from_pretrained(self.tmpdirname						,      use_fast=lowerCAmelCase      )

          self.assertEqual(processor.char_tokenizer.get_vocab()						,      tokenizer.get_vocab()      )
          self.assertIsInstance(processor.char_tokenizer						,      lowerCAmelCase      )

          self.assertEqual(processor.image_processor.to_json_string()						,      image_processor.to_json_string()      )
          self.assertIsInstance(processor.image_processor						,      lowerCAmelCase      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_tokenizer()
          snake_case        =     self.get_image_processor()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )
          processor.save_pretrained(self.tmpdirname      )

          snake_case        =     self.get_tokenizer(bos_token='(BOS)'						,      eos_token='(EOS)'      )
          snake_case        =     self.get_image_processor(do_normalize=lowerCAmelCase						,      padding_value=1.0      )

          snake_case        =     MgpstrProcessor.from_pretrained(
              self.tmpdirname						,      bos_token='(BOS)'						,      eos_token='(EOS)'						,      do_normalize=lowerCAmelCase						,      padding_value=1.0      )

          self.assertEqual(processor.char_tokenizer.get_vocab()						,      tokenizer_add_kwargs.get_vocab()      )
          self.assertIsInstance(processor.char_tokenizer						,      lowerCAmelCase      )

          self.assertEqual(processor.image_processor.to_json_string()						,      image_processor_add_kwargs.to_json_string()      )
          self.assertIsInstance(processor.image_processor						,      lowerCAmelCase      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     self.prepare_image_inputs()

          snake_case        =     image_processor(lowerCAmelCase						,      return_tensors='np'      )
          snake_case        =     processor(images=lowerCAmelCase						,      return_tensors='np'      )

          for key in input_image_proc.keys():
                self.assertAlmostEqual(input_image_proc[key].sum()						,      input_processor[key].sum()						,      delta=1E-2      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     'test'

          snake_case        =     processor(text=lowerCAmelCase      )

          snake_case        =     tokenizer(lowerCAmelCase      )
          for key in encoded_tok.keys():
                self.assertListEqual(encoded_tok[key]						,      encoded_processor[key]      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     'test'
          snake_case        =     self.prepare_image_inputs()

          snake_case        =     processor(text=lowerCAmelCase						,      images=lowerCAmelCase      )

          self.assertListEqual(list(inputs.keys()      )						,      ['pixel_values', 'labels']      )

          # test if it raises when no input is passed
          with pytest.raises(lowerCAmelCase      ):
                processor()

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

          snake_case        =     processor.char_decode(lowerCAmelCase      )
          snake_case        =     tokenizer.batch_decode(lowerCAmelCase      )
          snake_case        =     [seq.replace(' '						,      ''      ) for seq in decoded_tok]

          self.assertListEqual(lowerCAmelCase						,      lowerCAmelCase      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     None
          snake_case        =     self.prepare_image_inputs()

          snake_case        =     processor(text=lowerCAmelCase						,      images=lowerCAmelCase      )

          self.assertListEqual(list(inputs.keys()      )						,      processor.model_input_names      )

    def 						snake_case	(			self      ):






          """simple docstring"""

          snake_case        =     self.get_image_processor()
          snake_case        =     self.get_tokenizer()

          snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

          snake_case        =     torch.randn(1						,      27						,      38      )
          snake_case        =     torch.randn(1						,      27						,      5_02_57      )
          snake_case        =     torch.randn(1						,      27						,      3_05_22      )

          snake_case        =     processor.batch_decode([char_input, bpe_input, wp_input]      )

          self.assertListEqual(list(results.keys()      )						,      ['generated_text', 'scores', 'char_preds', 'bpe_preds', 'wp_preds']      )



"""simple docstring"""
import os
import sys
import unittest


SCREAMING_SNAKE_CASE__   =					os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
SCREAMING_SNAKE_CASE__   =					os.path.join(git_repo_path, "src", "transformers")

SCREAMING_SNAKE_CASE__   =					"\n{0} = None\n"

SCREAMING_SNAKE_CASE__   =					"\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"


SCREAMING_SNAKE_CASE__   =					"\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"



class 					lowerCAmelCase_      (     unittest.TestCase   ):



				"""simple docstring"""

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     find_backend('    _import_structure["models.albert"].append("AlbertTokenizerFast")'      )
										self.assertIsNone(lowerCAmelCase      )

										snake_case        =     find_backend('    if not is_tokenizers_available():'      )
										self.assertEqual(lowerCAmelCase						,      'tokenizers'      )

										snake_case        =     find_backend('    if not is_tensorflow_text_available():'      )
										self.assertEqual(lowerCAmelCase						,      'tensorflow_text'      )

										snake_case        =     find_backend('    if not (is_sentencepiece_available() and is_tokenizers_available()):'      )
										self.assertEqual(lowerCAmelCase						,      'sentencepiece_and_tokenizers'      )

										snake_case        =     find_backend(
										    '    if not (is_sentencepiece_available() and is_tensorflow_text_available()):'      )
										self.assertEqual(lowerCAmelCase						,      'sentencepiece_and_tensorflow_text'      )

										snake_case        =     find_backend(
										    '    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):'      )
										self.assertEqual(lowerCAmelCase						,      'sentencepiece_and_tokenizers_and_vision'      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     read_init()
										# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
										self.assertIn('torch'						,      lowerCAmelCase      )
										self.assertIn('tensorflow_text'						,      lowerCAmelCase      )
										self.assertIn('sentencepiece_and_tokenizers'						,      lowerCAmelCase      )

										# Likewise, we can't assert on the exact content of a key
										self.assertIn('BertModel'						,      objects['torch']      )
										self.assertIn('TFBertModel'						,      objects['tf']      )
										self.assertIn('FlaxBertModel'						,      objects['flax']      )
										self.assertIn('BertModel'						,      objects['torch']      )
										self.assertIn('TFBertTokenizer'						,      objects['tensorflow_text']      )
										self.assertIn('convert_slow_tokenizer'						,      objects['sentencepiece_and_tokenizers']      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     create_dummy_object('CONSTANT'						,      '\'torch\''      )
										self.assertEqual(lowerCAmelCase						,      '\nCONSTANT = None\n'      )

										snake_case        =     create_dummy_object('function'						,      '\'torch\''      )
										self.assertEqual(
										    lowerCAmelCase						,      '\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'      )

										snake_case        =     '\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n'
										snake_case        =     create_dummy_object('FakeClass'						,      '\'torch\''      )
										self.assertEqual(lowerCAmelCase						,      lowerCAmelCase      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     '# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n'
										snake_case        =     create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']}      )
										self.assertEqual(dummy_files['torch']						,      lowerCAmelCase      )


