
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import CLIPImageProcessor, CLIPProcessor




@require_vision
class      __A(    unittest.TestCase			):

		"""simple docstring"""







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    tempfile.mkdtemp()

							# fmt: off
							UpperCamelCase__				=    ["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
							# fmt: on
							UpperCamelCase__				=    dict(zip(SCREAMING_SNAKE_CASE_	,      range(len(SCREAMING_SNAKE_CASE_						)						)						)						)
							UpperCamelCase__				=    ["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
							UpperCamelCase__				=    {"""unk_token""": """<unk>"""}

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

							UpperCamelCase__				=    {
							    """do_resize""": True,
							    """size""": 20,
							    """do_center_crop""": True,
							    """crop_size""": 18,
							    """do_normalize""": True,
							    """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
							    """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
							}
							UpperCamelCase__				=    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	,      **SCREAMING_SNAKE_CASE_						):
							return CLIPTokenizer.from_pretrained(self.tmpdirname	,      **SCREAMING_SNAKE_CASE_						)







		def 	UpperCAmelCase_ (self	,      **SCREAMING_SNAKE_CASE_						):
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,      **SCREAMING_SNAKE_CASE_						)







		def 	UpperCAmelCase_ (self	,      **SCREAMING_SNAKE_CASE_						):
							return CLIPImageProcessor.from_pretrained(self.tmpdirname	,      **SCREAMING_SNAKE_CASE_						)







		def 	UpperCAmelCase_ (self						):
							shutil.rmtree(self.tmpdirname						)







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    [np.random.randint(2_55	,      size=(3, 30, 4_00)	,      dtype=np.uinta						)]

							UpperCamelCase__				=    [Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE_	,      0	,      -1						)						) for x in image_inputs]

							return image_inputs







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    self.get_tokenizer()
							UpperCamelCase__				=    self.get_rust_tokenizer()
							UpperCamelCase__				=    self.get_image_processor()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)
							processor_slow.save_pretrained(self.tmpdirname						)
							UpperCamelCase__				=    CLIPProcessor.from_pretrained(self.tmpdirname	,      use_fast=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)
							processor_fast.save_pretrained(self.tmpdirname						)
							UpperCamelCase__				=    CLIPProcessor.from_pretrained(self.tmpdirname						)

							self.assertEqual(processor_slow.tokenizer.get_vocab()	,      tokenizer_slow.get_vocab()						)
							self.assertEqual(processor_fast.tokenizer.get_vocab()	,      tokenizer_fast.get_vocab()						)
							self.assertEqual(tokenizer_slow.get_vocab()	,      tokenizer_fast.get_vocab()						)
							self.assertIsInstance(processor_slow.tokenizer	,      SCREAMING_SNAKE_CASE_						)
							self.assertIsInstance(processor_fast.tokenizer	,      SCREAMING_SNAKE_CASE_						)

							self.assertEqual(processor_slow.image_processor.to_json_string()	,      image_processor.to_json_string()						)
							self.assertEqual(processor_fast.image_processor.to_json_string()	,      image_processor.to_json_string()						)
							self.assertIsInstance(processor_slow.image_processor	,      SCREAMING_SNAKE_CASE_						)
							self.assertIsInstance(processor_fast.image_processor	,      SCREAMING_SNAKE_CASE_						)







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    CLIPProcessor(tokenizer=self.get_tokenizer()	,      image_processor=self.get_image_processor()						)
							processor.save_pretrained(self.tmpdirname						)

							UpperCamelCase__				=    self.get_tokenizer(bos_token="""(BOS)"""	,      eos_token="""(EOS)"""						)
							UpperCamelCase__				=    self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_	,      padding_value=1.0						)

							UpperCamelCase__				=    CLIPProcessor.from_pretrained(
							    self.tmpdirname	,      bos_token="""(BOS)"""	,      eos_token="""(EOS)"""	,      do_normalize=SCREAMING_SNAKE_CASE_	,      padding_value=1.0						)

							self.assertEqual(processor.tokenizer.get_vocab()	,      tokenizer_add_kwargs.get_vocab()						)
							self.assertIsInstance(processor.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						):
							UpperCamelCase__				=    self.get_image_processor()
							UpperCamelCase__				=    self.get_tokenizer()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    self.prepare_image_inputs()

							UpperCamelCase__				=    image_processor(SCREAMING_SNAKE_CASE_	,      return_tensors="""np"""						)
							UpperCamelCase__				=    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						):
							UpperCamelCase__				=    self.get_image_processor()
							UpperCamelCase__				=    self.get_tokenizer()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    """lower newer"""

							UpperCamelCase__				=    processor(text=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    tokenizer(SCREAMING_SNAKE_CASE_						)

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







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    self.get_image_processor()
							UpperCamelCase__				=    self.get_tokenizer()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    """lower newer"""
							UpperCamelCase__				=    self.prepare_image_inputs()

							UpperCamelCase__				=    processor(text=SCREAMING_SNAKE_CASE_	,      images=SCREAMING_SNAKE_CASE_						)

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

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







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    self.get_image_processor()
							UpperCamelCase__				=    self.get_tokenizer()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)

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

							UpperCamelCase__				=    processor.batch_decode(SCREAMING_SNAKE_CASE_						)
							UpperCamelCase__				=    tokenizer.batch_decode(SCREAMING_SNAKE_CASE_						)

							self.assertListEqual(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						)







		def 	UpperCAmelCase_ (self						):
							UpperCamelCase__				=    self.get_image_processor()
							UpperCamelCase__				=    self.get_tokenizer()

							UpperCamelCase__				=    CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_	,      image_processor=SCREAMING_SNAKE_CASE_						)

							UpperCamelCase__				=    """lower newer"""
							UpperCamelCase__				=    self.prepare_image_inputs()

							UpperCamelCase__				=    processor(text=SCREAMING_SNAKE_CASE_	,      images=SCREAMING_SNAKE_CASE_						)

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







from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowerCamelCase_						     =					{'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}


if TYPE_CHECKING:
    from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
    import sys

    lowerCamelCase_						     =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





