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'''

import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_ : List[Any]						  =      get_tests_dir("fixtures/test_sentencepiece.model")





@require_sentencepiece
@require_tokenizers
class 							lowercase						(						__lowerCamelCase ,				unittest.TestCase ):
   lowerCamelCase_    					=ReformerTokenizer
   lowerCamelCase_    					=ReformerTokenizerFast
   lowerCamelCase_    					=True
   lowerCamelCase_    					=False
   lowerCamelCase_    					=True


   def __UpperCAmelCase       (   self				:	Optional[Any])      ->					Optional[Any]:
         super().setUp()

         lowercase_     =      ReformerTokenizer(__lowerCAmelCase   ,		keep_accents=__lowerCAmelCase)
         tokenizer.save_pretrained(self.tmpdirname)


   def __UpperCAmelCase       (   self				:	int)      ->					int:
         lowercase_     =      "<s>"
         lowercase_     =      1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCAmelCase)   ,		__lowerCAmelCase)
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCAmelCase)   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Optional[int]:
         lowercase_     =      list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]   ,		"<unk>")
         self.assertEqual(vocab_keys[1]   ,		"<s>")
         self.assertEqual(vocab_keys[-1]   ,		"j")
         self.assertEqual(len(__lowerCAmelCase)   ,		1000)


   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Optional[Any]:
         self.assertEqual(self.get_tokenizer().vocab_size   ,		1000)


   def __UpperCAmelCase       (   self				:	List[Any])      ->					List[Any]:
         if not self.test_rust_tokenizer:
               return

         lowercase_     =      self.get_tokenizer()
         lowercase_     =      self.get_rust_tokenizer()

         lowercase_     =      "I was born in 92000, and this is falsé."

         lowercase_     =      tokenizer.tokenize(__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.tokenize(__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)

         lowercase_     =      tokenizer.encode(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.encode(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)

         lowercase_     =      self.get_rust_tokenizer()
         lowercase_     =      tokenizer.encode(__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.encode(__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	List[str]=15)      ->					Tuple:
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
                     lowercase_     =      self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase   ,		**__lowerCAmelCase)

                     # Simple input
                     lowercase_     =      "This is a simple input"
                     lowercase_     =      ["This is a simple input 1", "This is a simple input 2"]
                     lowercase_     =      ("This is a simple input", "This is a pair")
                     lowercase_     =      [
                         ("This is a simple input 1", "This is a simple input 2"),
                         ("This is a simple pair 1", "This is a simple pair 2"),
                     ]

                     # Simple input tests
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Simple input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Simple input
                     self.assertRaises(
                         __lowerCAmelCase   ,		tokenizer_r.batch_encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length"   ,		)

                     # Pair input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Pair input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Pair input
                     self.assertRaises(
                         __lowerCAmelCase   ,		tokenizer_r.batch_encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length"   ,		)


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Tuple:
         pass


   def __UpperCAmelCase       (   self				:	Any)      ->					Optional[Any]:
         lowercase_     =      ReformerTokenizer(__lowerCAmelCase   ,		keep_accents=__lowerCAmelCase)

         lowercase_     =      tokenizer.tokenize("This is a test")
         self.assertListEqual(__lowerCAmelCase   ,		["▁This", "▁is", "▁a", "▁t", "est"])

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__lowerCAmelCase)   ,		[285, 46, 10, 170, 382]   ,		)

         lowercase_     =      tokenizer.tokenize("I was born in 92000, and this is falsé.")
         self.assertListEqual(
             __lowerCAmelCase   ,		[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "9",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "é",
                 ".",
             ]   ,		)
         lowercase_     =      tokenizer.convert_tokens_to_ids(__lowerCAmelCase)
         self.assertListEqual(
             __lowerCAmelCase   ,		[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]   ,		)

         lowercase_     =      tokenizer.convert_ids_to_tokens(__lowerCAmelCase)
         self.assertListEqual(
             __lowerCAmelCase   ,		[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "<unk>",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "<unk>",
                 ".",
             ]   ,		)


   @cached_property
   def __UpperCAmelCase       (   self				:	List[str])      ->					Any:
         return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment")


   @slow
   def __UpperCAmelCase       (   self				:	Tuple)      ->					str:
         lowercase_     =      "Hello World!"
         lowercase_     =      [126, 32, 262, 152, 38, 72, 287]

         self.assertListEqual(__lowerCAmelCase   ,		self.big_tokenizer.encode(__lowerCAmelCase))


   @slow
   def __UpperCAmelCase       (   self				:	Any)      ->					Dict:
         lowercase_     =      (
             "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
             " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
         )
         lowercase_     =      [
             108,
             265,
             24,
             111,
             4,
             258,
             156,
             35,
             28,
             275,
             3,
             259,
             297,
             260,
             84,
             4,
             35,
             110,
             44,
             8,
             259,
             91,
             268,
             21,
             11,
             209,
             274,
             109,
             266,
             277,
             117,
             86,
             93,
             315,
             258,
             278,
             258,
             277,
             258,
             0,
             258,
             288,
             258,
             319,
             258,
             0,
             258,
             0,
             258,
             0,
             258,
             0,
             258,
             287,
             258,
             315,
             258,
             289,
             258,
             278,
             99,
             269,
             266,
             262,
             8,
             259,
             241,
             4,
             217,
             230,
             268,
             266,
             55,
             168,
             106,
             75,
             193,
             266,
             223,
             27,
             49,
             26,
             282,
             25,
             264,
             299,
             19,
             26,
             0,
             258,
             277,
             117,
             86,
             93,
             176,
             183,
             270,
             11,
             262,
             42,
             61,
             265,
         ]

         self.assertListEqual(__lowerCAmelCase   ,		self.big_tokenizer.encode(__lowerCAmelCase))


   @require_torch
   @slow
   def __UpperCAmelCase       (   self				:	Any)      ->					Tuple:
         import torch

         from transformers import ReformerConfig, ReformerModel

         # Build sequence
         lowercase_     =      list(self.big_tokenizer.get_vocab().keys())[:10]
         lowercase_     =      " ".join(__lowerCAmelCase)
         lowercase_     =      self.big_tokenizer.encode_plus(__lowerCAmelCase   ,		return_tensors="pt")
         lowercase_     =      self.big_tokenizer.batch_encode_plus([sequence, sequence]   ,		return_tensors="pt")

         lowercase_     =      ReformerConfig()
         # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
         lowercase_     =      encoded_sequence["input_ids"].shape
         lowercase_     =      ReformerModel(__lowerCAmelCase)

         # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
         assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

         with torch.no_grad():
               model(**__lowerCAmelCase)
               model(**__lowerCAmelCase)


   @slow
   def __UpperCAmelCase       (   self				:	List[Any])      ->					Tuple:
         # fmt: off
         lowercase_     =      {"input_ids": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
         # fmt: on

         # This tokenizer does not know some characters like ")".
         # That is the reason why we use very simple texts here.
         # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
         lowercase_     =      [
             "This is a very simple sentence.",
             "The quick brown fox jumps over the lazy dog.",
         ]

         self.tokenizer_integration_test_util(
             expected_encoding=__lowerCAmelCase   ,		model_name="google/reformer-crime-and-punishment"   ,		revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"   ,		padding=__lowerCAmelCase   ,		sequences=__lowerCAmelCase   ,		)






