'''simple docstring'''

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 							lowercase						(						unittest.TestCase ):


   def __UpperCAmelCase       (   self				:	int)      ->					Dict:
         lowercase_     =      tempfile.mkdtemp()

         # fmt: off
         lowercase_     =      ["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
         lowercase_     =      dict(zip(__lowerCAmelCase   ,		range(len(__lowerCAmelCase))))
         lowercase_     =      ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
         lowercase_     =      {"unk_token": "<unk>"}

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

         lowercase_     =      {
             "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],
         }
         lowercase_     =      os.path.join(self.tmpdirname   ,		__lowerCAmelCase)
         with open(self.image_processor_file   ,		"w"   ,		encoding="utf-8") as fp:
               json.dump(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		**__lowerCAmelCase				:	Optional[Any])      ->					List[str]:
         return CLIPTokenizer.from_pretrained(self.tmpdirname   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		**__lowerCAmelCase				:	Dict)      ->					Dict:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		**__lowerCAmelCase				:	Optional[int])      ->					Any:
         return CLIPImageProcessor.from_pretrained(self.tmpdirname   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					str:
         shutil.rmtree(self.tmpdirname)


   def __UpperCAmelCase       (   self				:	List[Any])      ->					Optional[int]:
         lowercase_     =      [np.random.randint(255   ,		size=(3, 30, 400)   ,		dtype=np.uinta)]

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

         return image_inputs


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					Any:
         lowercase_     =      self.get_tokenizer()
         lowercase_     =      self.get_rust_tokenizer()
         lowercase_     =      self.get_image_processor()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)
         processor_slow.save_pretrained(self.tmpdirname)
         lowercase_     =      CLIPProcessor.from_pretrained(self.tmpdirname   ,		use_fast=__lowerCAmelCase)

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)
         processor_fast.save_pretrained(self.tmpdirname)
         lowercase_     =      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   ,		__lowerCAmelCase)
         self.assertIsInstance(processor_fast.tokenizer   ,		__lowerCAmelCase)

         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   ,		__lowerCAmelCase)
         self.assertIsInstance(processor_fast.image_processor   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	int)      ->					List[Any]:
         lowercase_     =      CLIPProcessor(tokenizer=self.get_tokenizer()   ,		image_processor=self.get_image_processor())
         processor.save_pretrained(self.tmpdirname)

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

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

         self.assertEqual(processor.tokenizer.get_vocab()   ,		tokenizer_add_kwargs.get_vocab())
         self.assertIsInstance(processor.tokenizer   ,		__lowerCAmelCase)

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


   def __UpperCAmelCase       (   self				:	List[Any])      ->					Optional[Any]:
         lowercase_     =      self.get_image_processor()
         lowercase_     =      self.get_tokenizer()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)

         lowercase_     =      self.prepare_image_inputs()

         lowercase_     =      image_processor(__lowerCAmelCase   ,		return_tensors="np")
         lowercase_     =      processor(images=__lowerCAmelCase   ,		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				:	Dict)      ->					Optional[int]:
         lowercase_     =      self.get_image_processor()
         lowercase_     =      self.get_tokenizer()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)

         lowercase_     =      "lower newer"

         lowercase_     =      processor(text=__lowerCAmelCase)

         lowercase_     =      tokenizer(__lowerCAmelCase)

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


   def __UpperCAmelCase       (   self				:	List[Any])      ->					List[Any]:
         lowercase_     =      self.get_image_processor()
         lowercase_     =      self.get_tokenizer()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)

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

         lowercase_     =      processor(text=__lowerCAmelCase   ,		images=__lowerCAmelCase)

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

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


   def __UpperCAmelCase       (   self				:	int)      ->					Optional[Any]:
         lowercase_     =      self.get_image_processor()
         lowercase_     =      self.get_tokenizer()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)

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

         lowercase_     =      processor.batch_decode(__lowerCAmelCase)
         lowercase_     =      tokenizer.batch_decode(__lowerCAmelCase)

         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	List[str])      ->					List[str]:
         lowercase_     =      self.get_image_processor()
         lowercase_     =      self.get_tokenizer()

         lowercase_     =      CLIPProcessor(tokenizer=__lowerCAmelCase   ,		image_processor=__lowerCAmelCase)

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

         lowercase_     =      processor(text=__lowerCAmelCase   ,		images=__lowerCAmelCase)

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







'''simple docstring'''

from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream





class 							lowercase						(						__lowerCamelCase ):


   def __init__(   self				:	str   ,		__lowerCAmelCase				:	Callable   ,		__lowerCAmelCase				:	Optional[Features] = None   ,		__lowerCAmelCase				:	str = None   ,		__lowerCAmelCase				:	bool = False   ,		__lowerCAmelCase				:	bool = False   ,		__lowerCAmelCase				:	Optional[dict] = None   ,		__lowerCAmelCase				:	Optional[int] = None   ,		**__lowerCAmelCase				:	Union[str, Any]   ,		)      ->					List[Any]:
         super().__init__(
             features=__lowerCAmelCase   ,		cache_dir=__lowerCAmelCase   ,		keep_in_memory=__lowerCAmelCase   ,		streaming=__lowerCAmelCase   ,		num_proc=__lowerCAmelCase   ,		**__lowerCAmelCase   ,		)
         lowercase_     =      Generator(
             cache_dir=__lowerCAmelCase   ,		features=__lowerCAmelCase   ,		generator=__lowerCAmelCase   ,		gen_kwargs=__lowerCAmelCase   ,		**__lowerCAmelCase   ,		)


   def __UpperCAmelCase       (   self				:	Optional[int])      ->					List[str]:
         # Build iterable dataset
         if self.streaming:
               lowercase_     =      self.builder.as_streaming_dataset(split="train")
         # Build regular (map-style) dataset
         else:
               lowercase_     =      None
               lowercase_     =      None
               lowercase_     =      None
               lowercase_     =      None

               self.builder.download_and_prepare(
                   download_config=__lowerCAmelCase   ,		download_mode=__lowerCAmelCase   ,		verification_mode=__lowerCAmelCase   ,		base_path=__lowerCAmelCase   ,		num_proc=self.num_proc   ,		)
               lowercase_     =      self.builder.as_dataset(
                   split="train"   ,		verification_mode=__lowerCAmelCase   ,		in_memory=self.keep_in_memory)
         return dataset






