'''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 					__SCREAMING_SNAKE_CASE						(	unittest.TestCase	):







  '''simple docstring'''






  lowerCamelCase_		:Union[str, Any]						   =		ViTImageProcessor if is_vision_available() else None


  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       return self.image_processor_tester.prepare_image_processor_dict()


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				(3, 3_2, 1_2_8)
       UpperCAmelCase_							:       int       =				tempfile.mkdtemp()

       # fmt: off
       UpperCAmelCase_							:       Optional[int]       =				['[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
       UpperCAmelCase_							:       Optional[int]       =				dict(zip(snake_case_				,		range(len(snake_case_						)						)						)						)

       UpperCAmelCase_							:       Optional[Any]       =				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(snake_case_						) + '\n'						)

       UpperCAmelCase_							:       List[str]       =				{
           'do_normalize': False,
           'do_resize': True,
           'image_processor_type': 'ViTImageProcessor',
           'resample': 3,
           'size': {'height': 3_2, 'width': 1_2_8},
       }
       UpperCAmelCase_							:       Optional[int]       =				os.path.join(self.tmpdirname				,		snake_case_						)
       with open(self.image_processor_file				,		'w'				,		encoding='utf-8'						) as fp:
            json.dump(snake_case_				,		snake_case_						)


  def _UpperCamelCase					(			self				,		**snake_case_						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self				,		**snake_case_						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       shutil.rmtree(self.tmpdirname						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				np.random.randint(2_5_5				,		size=(3, 3_0, 4_0_0)				,		dtype=np.uinta						)

       UpperCAmelCase_							:       List[str]       =				Image.fromarray(np.moveaxis(snake_case_				,		0				,		-1						)						)

       return image_input


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				self.get_tokenizer()
       UpperCAmelCase_							:       Optional[int]       =				self.get_image_processor()

       UpperCAmelCase_							:       Optional[int]       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)
       processor.save_pretrained(self.tmpdirname						)
       UpperCAmelCase_							:       Optional[Any]       =				MgpstrProcessor.from_pretrained(self.tmpdirname				,		use_fast=snake_case_						)

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Any       =				self.get_tokenizer()
       UpperCAmelCase_							:       Optional[int]       =				self.get_image_processor()

       UpperCAmelCase_							:       Union[str, Any]       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)
       processor.save_pretrained(self.tmpdirname						)

       UpperCAmelCase_							:       Union[str, Any]       =				self.get_tokenizer(bos_token='(BOS)'				,		eos_token='(EOS)'						)
       UpperCAmelCase_							:       Union[str, Any]       =				self.get_image_processor(do_normalize=snake_case_				,		padding_value=1.0						)

       UpperCAmelCase_							:       str       =				MgpstrProcessor.from_pretrained(
           self.tmpdirname				,		bos_token='(BOS)'				,		eos_token='(EOS)'				,		do_normalize=snake_case_				,		padding_value=1.0						)

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				self.get_image_processor()
       UpperCAmelCase_							:       Optional[Any]       =				self.get_tokenizer()

       UpperCAmelCase_							:       Dict       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       Optional[Any]       =				self.prepare_image_inputs()

       UpperCAmelCase_							:       Union[str, Any]       =				image_processor(snake_case_				,		return_tensors='np'						)
       UpperCAmelCase_							:       Any       =				processor(images=snake_case_				,		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 _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				self.get_image_processor()
       UpperCAmelCase_							:       str       =				self.get_tokenizer()

       UpperCAmelCase_							:       List[str]       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       Optional[Any]       =				'test'

       UpperCAmelCase_							:       Union[str, Any]       =				processor(text=snake_case_						)

       UpperCAmelCase_							:       List[str]       =				tokenizer(snake_case_						)
       for key in encoded_tok.keys():
            self.assertListEqual(encoded_tok[key]				,		encoded_processor[key]						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Dict       =				self.get_image_processor()
       UpperCAmelCase_							:       List[Any]       =				self.get_tokenizer()

       UpperCAmelCase_							:       str       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       Dict       =				'test'
       UpperCAmelCase_							:       Optional[Any]       =				self.prepare_image_inputs()

       UpperCAmelCase_							:       Optional[Any]       =				processor(text=snake_case_				,		images=snake_case_						)

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				self.get_image_processor()
       UpperCAmelCase_							:       Optional[int]       =				self.get_tokenizer()

       UpperCAmelCase_							:       Union[str, Any]       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       List[str]       =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

       UpperCAmelCase_							:       int       =				processor.char_decode(snake_case_						)
       UpperCAmelCase_							:       Tuple       =				tokenizer.batch_decode(snake_case_						)
       UpperCAmelCase_							:       Optional[Any]       =				[seq.replace(' '				,		''						) for seq in decoded_tok]

       self.assertListEqual(snake_case_				,		snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Any       =				self.get_image_processor()
       UpperCAmelCase_							:       Tuple       =				self.get_tokenizer()

       UpperCAmelCase_							:       List[Any]       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       Union[str, Any]       =				None
       UpperCAmelCase_							:       Dict       =				self.prepare_image_inputs()

       UpperCAmelCase_							:       str       =				processor(text=snake_case_				,		images=snake_case_						)

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






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				self.get_image_processor()
       UpperCAmelCase_							:       str       =				self.get_tokenizer()

       UpperCAmelCase_							:       str       =				MgpstrProcessor(tokenizer=snake_case_				,		image_processor=snake_case_						)

       UpperCAmelCase_							:       Any       =				torch.randn(1				,		2_7				,		3_8						)
       UpperCAmelCase_							:       str       =				torch.randn(1				,		2_7				,		5_0_2_5_7						)
       UpperCAmelCase_							:       Optional[int]       =				torch.randn(1				,		2_7				,		3_0_5_2_2						)

       UpperCAmelCase_							:       Optional[int]       =				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 unittest

from transformers.utils.backbone_utils import (
    BackboneMixin,
    get_aligned_output_features_output_indices,
    verify_out_features_out_indices,
)






class 					__SCREAMING_SNAKE_CASE						(	unittest.TestCase	):







  '''simple docstring'''






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				['a', 'b', 'c']

       # Defaults to last layer if both are None
       UpperCAmelCase_       ,      UpperCAmelCase_							:       List[str]       =				get_aligned_output_features_output_indices(snake_case_				,		snake_case_				,		snake_case_						)
       self.assertEqual(snake_case_				,		['c']						)
       self.assertEqual(snake_case_				,		[2]						)

       # Out indices set to match out features
       UpperCAmelCase_       ,      UpperCAmelCase_							:       int       =				get_aligned_output_features_output_indices(['a', 'c']				,		snake_case_				,		snake_case_						)
       self.assertEqual(snake_case_				,		['a', 'c']						)
       self.assertEqual(snake_case_				,		[0, 2]						)

       # Out features set to match out indices
       UpperCAmelCase_       ,      UpperCAmelCase_							:       List[Any]       =				get_aligned_output_features_output_indices(snake_case_				,		[0, 2]				,		snake_case_						)
       self.assertEqual(snake_case_				,		['a', 'c']						)
       self.assertEqual(snake_case_				,		[0, 2]						)

       # Out features selected from negative indices
       UpperCAmelCase_       ,      UpperCAmelCase_							:       int       =				get_aligned_output_features_output_indices(snake_case_				,		[-3, -1]				,		snake_case_						)
       self.assertEqual(snake_case_				,		['a', 'c']						)
       self.assertEqual(snake_case_				,		[-3, -1]						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(['a', 'b']				,		(0, 1)				,		snake_case_						)

       # Out features must be a list
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(('a', 'b')				,		(0, 1)				,		['a', 'b']						)

       # Out features must be a subset of stage names
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(['a', 'b']				,		(0, 1)				,		['a']						)

       # Out indices must be a list or tuple
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(snake_case_				,		0				,		['a', 'b']						)

       # Out indices must be a subset of stage names
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(snake_case_				,		(0, 1)				,		['a']						)

       # Out features and out indices must be the same length
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(['a', 'b']				,		(0,)				,		['a', 'b', 'c']						)

       # Out features should match out indices
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(['a', 'b']				,		(0, 2)				,		['a', 'b', 'c']						)

       # Out features and out indices should be in order
       with self.assertRaises(snake_case_						):
            verify_out_features_out_indices(['b', 'a']				,		(0, 1)				,		['a', 'b']						)

       # Check passes with valid inputs
       verify_out_features_out_indices(['a', 'b', 'd']				,		(0, 1, -1)				,		['a', 'b', 'c', 'd']						)






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				BackboneMixin()

       UpperCAmelCase_							:       Any       =				['a', 'b', 'c']
       UpperCAmelCase_							:       str       =				['a', 'c']
       UpperCAmelCase_							:       str       =				[0, 2]

       # Check that the output features and indices are set correctly
       self.assertEqual(backbone.out_features				,		['a', 'c']						)
       self.assertEqual(backbone.out_indices				,		[0, 2]						)

       # Check out features and indices are updated correctly
       UpperCAmelCase_							:       str       =				['a', 'b']
       self.assertEqual(backbone.out_features				,		['a', 'b']						)
       self.assertEqual(backbone.out_indices				,		[0, 1]						)

       UpperCAmelCase_							:       Optional[int]       =				[-3, -1]
       self.assertEqual(backbone.out_features				,		['a', 'c']						)
       self.assertEqual(backbone.out_indices				,		[-3, -1]						)






