





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        SCREAMING_SNAKE_CASE     (unittest.TestCase   ):
   _UpperCamelCase					:	Optional[Any]				      = ViTImageProcessor if is_vision_available() else None


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int] )->     Optional[Any]:





      """simple docstring"""







      return self.image_processor_tester.prepare_image_processor_dict()


   def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     Optional[int]:





      """simple docstring"""







      lowercase__			    =						(3, 32, 128)
      lowercase__			    =						tempfile.mkdtemp()

      # fmt: off
      lowercase__			    =						["""[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
      lowercase__			    =						dict(zip(lowercase__    ,  range(len(lowercase__ ) ) ) )

      lowercase__			    =						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(lowercase__ ) + '\n' )

      lowercase__			    =						{
          """do_normalize""": False,
          """do_resize""": True,
          """image_processor_type""": """ViTImageProcessor""",
          """resample""": 3,
          """size""": {"""height""": 32, """width""": 128},
      }
      lowercase__			    =						os.path.join(self.tmpdirname    ,  lowercase__ )
      with open(self.image_processor_file    ,  'w'    ,  encoding='utf-8' ) as fp:
         json.dump(lowercase__    ,  lowercase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[Any]    ,  **a    :       List[Any] )->     int:





      """simple docstring"""







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


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any]    ,  **a    :       Optional[int] )->     Optional[int]:





      """simple docstring"""







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


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[Any] )->     List[Any]:





      """simple docstring"""







      shutil.rmtree(self.tmpdirname )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int] )->     str:





      """simple docstring"""







      lowercase__			    =						np.random.randint(255    ,  size=(3, 30, 400)    ,  dtype=np.uinta )

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

      return image_input


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any] )->     Union[str, Any]:





      """simple docstring"""







      lowercase__			    =						self.get_tokenizer()
      lowercase__			    =						self.get_image_processor()

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

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

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


   def  SCREAMING_SNAKE_CASE_							(					self    :       Tuple )->     Tuple:





      """simple docstring"""







      lowercase__			    =						self.get_tokenizer()
      lowercase__			    =						self.get_image_processor()

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

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

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

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

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


   def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any] )->     List[Any]:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

      lowercase__			    =						self.prepare_image_inputs()

      lowercase__			    =						image_processor(lowercase__    ,  return_tensors='np' )
      lowercase__			    =						processor(images=lowercase__    ,  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  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     Union[str, Any]:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

      lowercase__			    =						"""test"""

      lowercase__			    =						processor(text=lowercase__ )

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


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[Any] )->     Union[str, Any]:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

      lowercase__			    =						"""test"""
      lowercase__			    =						self.prepare_image_inputs()

      lowercase__			    =						processor(text=lowercase__    ,  images=lowercase__ )

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

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


   def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     List[Any]:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

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

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

      self.assertListEqual(lowercase__    ,  lowercase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int] )->     Any:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

      lowercase__			    =						None
      lowercase__			    =						self.prepare_image_inputs()

      lowercase__			    =						processor(text=lowercase__    ,  images=lowercase__ )

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


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[Any] )->     Union[str, Any]:





      """simple docstring"""







      lowercase__			    =						self.get_image_processor()
      lowercase__			    =						self.get_tokenizer()

      lowercase__			    =						MgpstrProcessor(tokenizer=lowercase__    ,  image_processor=lowercase__ )

      lowercase__			    =						torch.randn(1    ,  27    ,  38 )
      lowercase__			    =						torch.randn(1    ,  27    ,  50_257 )
      lowercase__			    =						torch.randn(1    ,  27    ,  30_522 )

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

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









from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_					     =	logging.get_logger(__name__)

lowercase_					     =	{
    """facebook/deit-base-distilled-patch16-224""": (
        """https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json"""
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	Any				      = 'deit'


   def __init__(					self    :       Any    ,  a    :       Union[str, Any]=768    ,  a    :       Optional[Any]=12    ,  a    :       Union[str, Any]=12    ,  a    :       Optional[int]=3_072    ,  a    :       Optional[int]="gelu"    ,  a    :       Optional[Any]=0.0    ,  a    :       List[Any]=0.0    ,  a    :       int=0.02    ,  a    :       List[str]=1E-1_2    ,  a    :       Optional[int]=224    ,  a    :       Tuple=16    ,  a    :       List[Any]=3    ,  a    :       List[str]=True    ,  a    :       Any=16    ,  **a    :       Union[str, Any]    ,  )->     int:





     """simple docstring"""







     super().__init__(**a )

     lowercase__			    =						hidden_size
     lowercase__			    =						num_hidden_layers
     lowercase__			    =						num_attention_heads
     lowercase__			    =						intermediate_size
     lowercase__			    =						hidden_act
     lowercase__			    =						hidden_dropout_prob
     lowercase__			    =						attention_probs_dropout_prob
     lowercase__			    =						initializer_range
     lowercase__			    =						layer_norm_eps
     lowercase__			    =						image_size
     lowercase__			    =						patch_size
     lowercase__			    =						num_channels
     lowercase__			    =						qkv_bias
     lowercase__			    =						encoder_stride






class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	List[Any]				      = version.parse('1.11'   )


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     Mapping[str, Mapping[int, str]]:





     """simple docstring"""







     return OrderedDict(
         [
             ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
         ] )


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     float:





     """simple docstring"""







     return 1E-4


