






"""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				):




						"""simple docstring"""




						__lowerCamelCase										=   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'''
												lowercase__							: Union[str, Any]=			(3, 32, 128)
												lowercase__							: str=			tempfile.mkdtemp()

												# fmt: off
												lowercase__							: Dict=			['''[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__							: List[str]=			dict(zip(SCREAMING_SNAKE_CASE__			,    range(len(SCREAMING_SNAKE_CASE__     )     )     )     )

												lowercase__							: Dict=			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(SCREAMING_SNAKE_CASE__     ) + "\n"     )

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




						def 						UpperCAmelCase_			(  self			,    **snake_case__     ):
												'''simple docstring'''
												return MgpstrTokenizer.from_pretrained(self.tmpdirname			,    **SCREAMING_SNAKE_CASE__     )




						def 						UpperCAmelCase_			(  self			,    **snake_case__     ):
												'''simple docstring'''
												return ViTImageProcessor.from_pretrained(self.tmpdirname			,    **SCREAMING_SNAKE_CASE__     )




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												shutil.rmtree(self.tmpdirname     )




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: Optional[Any]=			np.random.randint(255			,    size=(3, 30, 400)			,    dtype=np.uinta     )

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

												return image_input




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: Optional[int]=			self.get_tokenizer()
												lowercase__							: Any=			self.get_image_processor()

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

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

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




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: Dict=			self.get_tokenizer()
												lowercase__							: Optional[int]=			self.get_image_processor()

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

												lowercase__							: List[str]=			self.get_tokenizer(bos_token="(BOS)"			,    eos_token="(EOS)"     )
												lowercase__							: str=			self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE__			,    padding_value=1.0     )

												lowercase__							: Tuple=			MgpstrProcessor.from_pretrained(
												    self.tmpdirname			,    bos_token="(BOS)"			,    eos_token="(EOS)"			,    do_normalize=SCREAMING_SNAKE_CASE__			,    padding_value=1.0     )

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

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




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: int=			self.get_image_processor()
												lowercase__							: int=			self.get_tokenizer()

												lowercase__							: Optional[Any]=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: Dict=			self.prepare_image_inputs()

												lowercase__							: int=			image_processor(SCREAMING_SNAKE_CASE__			,    return_tensors="np"     )
												lowercase__							: List[Any]=			processor(images=SCREAMING_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'''
												lowercase__							: Dict=			self.get_image_processor()
												lowercase__							: Union[str, Any]=			self.get_tokenizer()

												lowercase__							: Optional[Any]=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: Any=			'''test'''

												lowercase__							: Union[str, Any]=			processor(text=SCREAMING_SNAKE_CASE__     )

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




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: List[Any]=			self.get_image_processor()
												lowercase__							: List[Any]=			self.get_tokenizer()

												lowercase__							: Optional[int]=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: Any=			'''test'''
												lowercase__							: Tuple=			self.prepare_image_inputs()

												lowercase__							: Optional[int]=			processor(text=SCREAMING_SNAKE_CASE__			,    images=SCREAMING_SNAKE_CASE__     )

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

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




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: List[str]=			self.get_image_processor()
												lowercase__							: Tuple=			self.get_tokenizer()

												lowercase__							: str=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: Union[str, Any]=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

												lowercase__							: Any=			processor.char_decode(SCREAMING_SNAKE_CASE__     )
												lowercase__							: Union[str, Any]=			tokenizer.batch_decode(SCREAMING_SNAKE_CASE__     )
												lowercase__							: List[Any]=			[seq.replace(" "			,    ""     ) for seq in decoded_tok]

												self.assertListEqual(SCREAMING_SNAKE_CASE__			,    SCREAMING_SNAKE_CASE__     )




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: List[str]=			self.get_image_processor()
												lowercase__							: Any=			self.get_tokenizer()

												lowercase__							: str=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: int=			None
												lowercase__							: Dict=			self.prepare_image_inputs()

												lowercase__							: Dict=			processor(text=SCREAMING_SNAKE_CASE__			,    images=SCREAMING_SNAKE_CASE__     )

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




						def 						UpperCAmelCase_			(  self     ):
												'''simple docstring'''
												lowercase__							: List[str]=			self.get_image_processor()
												lowercase__							: Union[str, Any]=			self.get_tokenizer()

												lowercase__							: Optional[int]=			MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__			,    image_processor=SCREAMING_SNAKE_CASE__     )

												lowercase__							: Union[str, Any]=			torch.randn(1			,    27			,    38     )
												lowercase__							: str=			torch.randn(1			,    27			,    50257     )
												lowercase__							: List[Any]=			torch.randn(1			,    27			,    30522     )

												lowercase__							: Optional[Any]=			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"""






UpperCamelCase__				:Tuple			   =	frozenset(
    [
        """prompt""",
        """height""",
        """width""",
        """guidance_scale""",
        """negative_prompt""",
        """prompt_embeds""",
        """negative_prompt_embeds""",
        """cross_attention_kwargs""",
    ]
)

UpperCamelCase__				:List[str]			   =	frozenset(["""prompt""", """negative_prompt"""])

UpperCamelCase__				:Tuple			   =	frozenset([])

UpperCamelCase__				:Union[str, Any]			   =	frozenset(["""image"""])

UpperCamelCase__				:str			   =	frozenset(
    [
        """image""",
        """height""",
        """width""",
        """guidance_scale""",
    ]
)

UpperCamelCase__				:Any			   =	frozenset(["""image"""])

UpperCamelCase__				:Optional[int]			   =	frozenset(
    [
        """prompt""",
        """image""",
        """height""",
        """width""",
        """guidance_scale""",
        """negative_prompt""",
        """prompt_embeds""",
        """negative_prompt_embeds""",
    ]
)

UpperCamelCase__				:int			   =	frozenset(["""prompt""", """image""", """negative_prompt"""])

UpperCamelCase__				:Tuple			   =	frozenset(
    [
        # Text guided image variation with an image mask
        """prompt""",
        """image""",
        """mask_image""",
        """height""",
        """width""",
        """guidance_scale""",
        """negative_prompt""",
        """prompt_embeds""",
        """negative_prompt_embeds""",
    ]
)

UpperCamelCase__				:Any			   =	frozenset(["""prompt""", """image""", """mask_image""", """negative_prompt"""])

UpperCamelCase__				:Dict			   =	frozenset(
    [
        # image variation with an image mask
        """image""",
        """mask_image""",
        """height""",
        """width""",
        """guidance_scale""",
    ]
)

UpperCamelCase__				:Dict			   =	frozenset(["""image""", """mask_image"""])

UpperCamelCase__				:Tuple			   =	frozenset(
    [
        """example_image""",
        """image""",
        """mask_image""",
        """height""",
        """width""",
        """guidance_scale""",
    ]
)

UpperCamelCase__				:List[str]			   =	frozenset(["""example_image""", """image""", """mask_image"""])

UpperCamelCase__				:List[str]			   =	frozenset(["""class_labels"""])

UpperCamelCase__				:Union[str, Any]			   =	frozenset(["""class_labels"""])

UpperCamelCase__				:Any			   =	frozenset(["""batch_size"""])

UpperCamelCase__				:Optional[Any]			   =	frozenset([])

UpperCamelCase__				:Optional[Any]			   =	frozenset(["""batch_size"""])

UpperCamelCase__				:Optional[int]			   =	frozenset([])

UpperCamelCase__				:str			   =	frozenset(
    [
        """prompt""",
        """audio_length_in_s""",
        """guidance_scale""",
        """negative_prompt""",
        """prompt_embeds""",
        """negative_prompt_embeds""",
        """cross_attention_kwargs""",
    ]
)

UpperCamelCase__				:Union[str, Any]			   =	frozenset(["""prompt""", """negative_prompt"""])
UpperCamelCase__				:Tuple			   =	frozenset(["""input_tokens"""])

UpperCamelCase__				:int			   =	frozenset(["""input_tokens"""])

