






'''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        _UpperCAmelCase						(		unittest.TestCase			):
    __lowerCamelCase:   int		       =    ViTImageProcessor if is_vision_available() else None




    @property
    def 				lowerCAmelCase__				(			self  :       Union[str, Any]			):






       '''simple docstring'''






       return self.image_processor_tester.prepare_image_processor_dict()




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     (3, 3_2, 1_2_8)
       lowercase_	:    Optional[int]           =     tempfile.mkdtemp()

       # fmt: off
       lowercase_	:    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
       lowercase_	:    Any           =     dict(zip(a  ,     range(len(a			)			)			)			)

       lowercase_	:    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(a			) + "\n"			)

       lowercase_	:    Tuple           =     {
           "do_normalize": False,
           "do_resize": True,
           "image_processor_type": "ViTImageProcessor",
           "resample": 3,
           "size": {"height": 3_2, "width": 1_2_8},
       }
       lowercase_	:    Dict           =     os.path.join(self.tmpdirname  ,     a			)
       with open(self.image_processor_file  ,     "w"  ,     encoding="utf-8"			) as fp:
          json.dump(a  ,     a			)




    def 				lowerCAmelCase__				(			self  :       Dict  ,     **a  :       Optional[int]			):






       '''simple docstring'''






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




    def 				lowerCAmelCase__				(			self  :       Dict  ,     **a  :       Dict			):






       '''simple docstring'''






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




    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       shutil.rmtree(self.tmpdirname			)




    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






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

       lowercase_	:    Optional[int]           =     Image.fromarray(np.moveaxis(a  ,     0  ,     -1			)			)

       return image_input




    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       lowercase_	:    Dict           =     self.get_tokenizer()
       lowercase_	:    str           =     self.get_image_processor()

       lowercase_	:    int           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)
       processor.save_pretrained(self.tmpdirname			)
       lowercase_	:    Any           =     MgpstrProcessor.from_pretrained(self.tmpdirname  ,     use_fast=a			)

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

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




    def 				lowerCAmelCase__				(			self  :       Union[str, Any]			):






       '''simple docstring'''






       lowercase_	:    str           =     self.get_tokenizer()
       lowercase_	:    Union[str, Any]           =     self.get_image_processor()

       lowercase_	:    List[Any]           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)
       processor.save_pretrained(self.tmpdirname			)

       lowercase_	:    str           =     self.get_tokenizer(bos_token="(BOS)"  ,     eos_token="(EOS)"			)
       lowercase_	:    Optional[int]           =     self.get_image_processor(do_normalize=a  ,     padding_value=1.0			)

       lowercase_	:    Union[str, Any]           =     MgpstrProcessor.from_pretrained(
           self.tmpdirname  ,     bos_token="(BOS)"  ,     eos_token="(EOS)"  ,     do_normalize=a  ,     padding_value=1.0			)

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

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




    def 				lowerCAmelCase__				(			self  :       Optional[int]			):






       '''simple docstring'''






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

       lowercase_	:    List[Any]           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    Union[str, Any]           =     self.prepare_image_inputs()

       lowercase_	:    str           =     image_processor(a  ,     return_tensors="np"			)
       lowercase_	:    Optional[Any]           =     processor(images=a  ,     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 				lowerCAmelCase__				(			self  :       Union[str, Any]			):






       '''simple docstring'''






       lowercase_	:    Any           =     self.get_image_processor()
       lowercase_	:    Union[str, Any]           =     self.get_tokenizer()

       lowercase_	:    Optional[int]           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    str           =     "test"

       lowercase_	:    Union[str, Any]           =     processor(text=a			)

       lowercase_	:    Optional[int]           =     tokenizer(a			)
       for key in encoded_tok.keys():
          self.assertListEqual(encoded_tok[key]  ,     encoded_processor[key]			)




    def 				lowerCAmelCase__				(			self  :       List[Any]			):






       '''simple docstring'''






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

       lowercase_	:    Tuple           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    str           =     "test"
       lowercase_	:    Union[str, Any]           =     self.prepare_image_inputs()

       lowercase_	:    Any           =     processor(text=a  ,     images=a			)

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

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




    def 				lowerCAmelCase__				(			self  :       Optional[int]			):






       '''simple docstring'''






       lowercase_	:    Union[str, Any]           =     self.get_image_processor()
       lowercase_	:    List[str]           =     self.get_tokenizer()

       lowercase_	:    Optional[int]           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    Tuple           =     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

       lowercase_	:    Union[str, Any]           =     processor.char_decode(a			)
       lowercase_	:    Dict           =     tokenizer.batch_decode(a			)
       lowercase_	:    Any           =     [seq.replace(" "  ,     ""			) for seq in decoded_tok]

       self.assertListEqual(a  ,     a			)




    def 				lowerCAmelCase__				(			self  :       Any			):






       '''simple docstring'''






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

       lowercase_	:    Optional[Any]           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    Optional[int]           =     None
       lowercase_	:    List[str]           =     self.prepare_image_inputs()

       lowercase_	:    str           =     processor(text=a  ,     images=a			)

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





    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       lowercase_	:    Dict           =     self.get_image_processor()
       lowercase_	:    Dict           =     self.get_tokenizer()

       lowercase_	:    int           =     MgpstrProcessor(tokenizer=a  ,     image_processor=a			)

       lowercase_	:    List[str]           =     torch.randn(1  ,     2_7  ,     3_8			)
       lowercase_	:    Tuple           =     torch.randn(1  ,     2_7  ,     5_0_2_5_7			)
       lowercase_	:    int           =     torch.randn(1  ,     2_7  ,     3_0_5_2_2			)

       lowercase_	:    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'''
# limitations under the License.

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from .pipelines import DiffusionPipeline, ImagePipelineOutput  # noqa: F401
from .utils import deprecate


deprecate(
    'pipelines_utils',
    '0.22.0',
    'Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.',
    standard_warn=False,
    stacklevel=3,
)




