"""simple docstring"""


import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()






class    a__    (   unittest.TestCase	):


   @property
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        torch.manual_seed(0  )
        lowercase__				 =							UNetaDModel(
            block_out_channels=(32, 64),				layers_per_block=2,				sample_size=32,				in_channels=3,				out_channels=3,				down_block_types=("DownBlock2D", "AttnDownBlock2D"),				up_block_types=("AttnUpBlock2D", "UpBlock2D"),				)
        return model


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.dummy_uncond_unet
        lowercase__				 =							KarrasVeScheduler()

        lowercase__				 =							KarrasVePipeline(unet=snake_case_,				scheduler=snake_case_  )
        pipe.to(snake_case_  )
        pipe.set_progress_bar_config(disable=snake_case_  )

        lowercase__				 =							torch.manual_seed(0  )
        lowercase__				 =							pipe(num_inference_steps=2,				generator=snake_case_,				output_type="numpy"  ).images

        lowercase__				 =							torch.manual_seed(0  )
        lowercase__				 =							pipe(num_inference_steps=2,				generator=snake_case_,				output_type="numpy",				return_dict=snake_case_  )[0]

        lowercase__				 =							image[0, -3:, -3:, -1]
        lowercase__				 =							image_from_tuple[0, -3:, -3:, -1]

        assert image.shape == (1, 32, 32, 3)
        lowercase__				 =							np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]  )

        assert np.abs(image_slice.flatten() - expected_slice  ).max() < 1E-2
        assert np.abs(image_from_tuple_slice.flatten() - expected_slice  ).max() < 1E-2






@slow
@require_torch
class    a__    (   unittest.TestCase	):


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							"google/ncsnpp-celebahq-256"
        lowercase__				 =							UNetaDModel.from_pretrained(snake_case_  )
        lowercase__				 =							KarrasVeScheduler()

        lowercase__				 =							KarrasVePipeline(unet=snake_case_,				scheduler=snake_case_  )
        pipe.to(snake_case_  )
        pipe.set_progress_bar_config(disable=snake_case_  )

        lowercase__				 =							torch.manual_seed(0  )
        lowercase__				 =							pipe(num_inference_steps=20,				generator=snake_case_,				output_type="numpy"  ).images

        lowercase__				 =							image[0, -3:, -3:, -1]
        assert image.shape == (1, 256, 256, 3)
        lowercase__				 =							np.array([0.578, 0.5_811, 0.5_924, 0.5_809, 0.587, 0.5_886, 0.5_861, 0.5_802, 0.586]  )

        assert np.abs(image_slice.flatten() - expected_slice  ).max() < 1E-2





"""simple docstring"""


import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
 lowerCAmelCase_:					Dict     =					"pt"
elif is_tf_available():
 lowerCAmelCase_:					Dict     =					"tf"
else:
 lowerCAmelCase_:					str     =					"jax"






class    a__    (   _a					,					unittest.TestCase	):
   snake_case_							=      ByTaTokenizer
   snake_case_							=      False


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        super().setUp()
        lowercase__				 =							ByTaTokenizer()
        tokenizer.save_pretrained(self.tmpdirname  )


   @cached_property
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        return ByTaTokenizer.from_pretrained("google/byt5-small"  )


   def 	snake_case__	(     self,				**_UpperCAmelCase  ):
        '''simple docstring'''



        return self.tokenizer_class.from_pretrained(self.tmpdirname,				**_UpperCAmelCase  )


   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase=False,				_UpperCAmelCase=20,				_UpperCAmelCase=5  ):
        '''simple docstring'''



        lowercase__				 =							[]
        for i in range(len(_UpperCAmelCase  )  ):
             try:
                  lowercase__				 =							tokenizer.decode([i],				clean_up_tokenization_spaces=_UpperCAmelCase  )
             except UnicodeDecodeError:
                  pass
             toks.append((i, tok)  )

        lowercase__				 =							list(filter(lambda _UpperCAmelCase  : re.match(R"^[ a-zA-Z]+$",				t[1]  ),				_UpperCAmelCase  )  )
        lowercase__				 =							list(filter(lambda _UpperCAmelCase  : [t[0]] == tokenizer.encode(t[1],				add_special_tokens=_UpperCAmelCase  ),				_UpperCAmelCase  )  )
        if max_length is not None and len(_UpperCAmelCase  ) > max_length:
             lowercase__				 =							toks[:max_length]
        if min_length is not None and len(_UpperCAmelCase  ) < min_length and len(_UpperCAmelCase  ) > 0:
             while len(_UpperCAmelCase  ) < min_length:
                  lowercase__				 =							toks + toks
        # toks_str = [t[1] for t in toks]
        lowercase__				 =							[t[0] for t in toks]

        # Ensure consistency
        lowercase__				 =							tokenizer.decode(_UpperCAmelCase,				clean_up_tokenization_spaces=_UpperCAmelCase  )
        if " " not in output_txt and len(_UpperCAmelCase  ) > 1:
             lowercase__				 =							(
                 tokenizer.decode([toks_ids[0]],				clean_up_tokenization_spaces=_UpperCAmelCase  )
                 + " "
                 + tokenizer.decode(toks_ids[1:],				clean_up_tokenization_spaces=_UpperCAmelCase  )
             )
        if with_prefix_space:
             lowercase__				 =							" " + output_txt
        lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
        return output_txt, output_ids


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]  )
        lowercase__				 =							tokenizer(["hi", "I went to the gym", ""]  )
        self.assertListEqual(batch_with_eos_added["input_ids"],				batch_without_eos_added["input_ids"]  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							"Unicode €."
        lowercase__				 =							tokenizer(_UpperCAmelCase  )
        lowercase__				 =							[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
        self.assertEqual(encoded["input_ids"],				_UpperCAmelCase  )

        # decoding
        lowercase__				 =							tokenizer.decode(_UpperCAmelCase  )
        self.assertEqual(_UpperCAmelCase,				"Unicode €.</s>"  )

        lowercase__				 =							tokenizer("e è é ê ë"  )
        lowercase__				 =							[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
        self.assertEqual(encoded["input_ids"],				_UpperCAmelCase  )
        # decoding
        lowercase__				 =							tokenizer.decode(_UpperCAmelCase  )
        self.assertEqual(_UpperCAmelCase,				"e è é ê ë</s>"  )

        # encode/decode, but with `encode` instead of `__call__`
        self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"  )  ),				"e è é ê ë</s>"  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							["A long paragraph for summarization.", "Another paragraph for summarization."]
        # fmt: off
        lowercase__				 =							[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
        # fmt: on
        lowercase__				 =							tokenizer(_UpperCAmelCase,				padding=_UpperCAmelCase,				return_tensors=_UpperCAmelCase  )
        self.assertIsInstance(_UpperCAmelCase,				_UpperCAmelCase  )

        if FRAMEWORK != "jax":
             lowercase__				 =							list(batch.input_ids.numpy()[0]  )
        else:
             lowercase__				 =							list(batch.input_ids.tolist()[0]  )

        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

        self.assertEqual((2, 37),				batch.input_ids.shape  )
        self.assertEqual((2, 37),				batch.attention_mask.shape  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							["A long paragraph for summarization.", "Another paragraph for summarization."]
        lowercase__				 =							tokenizer(_UpperCAmelCase,				padding=_UpperCAmelCase,				return_tensors=_UpperCAmelCase  )
        # check if input_ids are returned and no decoder_input_ids
        self.assertIn("input_ids",				_UpperCAmelCase  )
        self.assertIn("attention_mask",				_UpperCAmelCase  )
        self.assertNotIn("decoder_input_ids",				_UpperCAmelCase  )
        self.assertNotIn("decoder_attention_mask",				_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							[
            "Summary of the text.",
            "Another summary.",
        ]
        lowercase__				 =							tokenizer(
            text_target=_UpperCAmelCase,				max_length=32,				padding="max_length",				truncation=_UpperCAmelCase,				return_tensors=_UpperCAmelCase  )
        self.assertEqual(32,				targets["input_ids"].shape[1]  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.ta_base_tokenizer
        lowercase__				 =							["A long paragraph for summarization. </s>"]
        lowercase__				 =							["Summary of the text. </s>"]
        # fmt: off
        lowercase__				 =							[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
        lowercase__				 =							[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
        # fmt: on

        lowercase__				 =							tokenizer(_UpperCAmelCase,				text_target=_UpperCAmelCase  )

        self.assertEqual(_UpperCAmelCase,				batch["input_ids"][0]  )
        self.assertEqual(_UpperCAmelCase,				batch["labels"][0]  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  self.assertNotEqual(tokenizer.model_max_length,				42  )

        # Now let's start the test
        lowercase__				 =							self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  # Isolate this from the other tests because we save additional tokens/etc
                  lowercase__				 =							tempfile.mkdtemp()

                  lowercase__				 =							" He is very happy, UNwant\u00E9d,running"
                  lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  tokenizer.save_pretrained(_UpperCAmelCase  )

                  lowercase__				 =							tokenizer.__class__.from_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							after_tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

                  shutil.rmtree(_UpperCAmelCase  )

        lowercase__				 =							self.get_tokenizers(model_max_length=42  )
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  # Isolate this from the other tests because we save additional tokens/etc
                  lowercase__				 =							tempfile.mkdtemp()

                  lowercase__				 =							" He is very happy, UNwant\u00E9d,running"
                  tokenizer.add_tokens(["bim", "bambam"]  )
                  lowercase__				 =							tokenizer.additional_special_tokens
                  additional_special_tokens.append("new_additional_special_token"  )
                  tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}  )
                  lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  tokenizer.save_pretrained(_UpperCAmelCase  )

                  lowercase__				 =							tokenizer.__class__.from_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							after_tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )
                  self.assertIn("new_additional_special_token",				after_tokenizer.additional_special_tokens  )
                  self.assertEqual(after_tokenizer.model_max_length,				42  )

                  lowercase__				 =							tokenizer.__class__.from_pretrained(_UpperCAmelCase,				model_max_length=43  )
                  self.assertEqual(tokenizer.model_max_length,				43  )

                  shutil.rmtree(_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							[]
        if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())  )

        if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())  )

        for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                  tokenizer_utils.save_pretrained(_UpperCAmelCase  )

                  with open(os.path.join(_UpperCAmelCase,				"special_tokens_map.json"  ),				encoding="utf-8"  ) as json_file:
                       lowercase__				 =							json.load(_UpperCAmelCase  )

                  with open(os.path.join(_UpperCAmelCase,				"tokenizer_config.json"  ),				encoding="utf-8"  ) as json_file:
                       lowercase__				 =							json.load(_UpperCAmelCase  )

                  lowercase__				 =							[F'''<extra_id_{i}>''' for i in range(125  )]

                  lowercase__				 =							added_tokens_extra_ids + [
                      "an_additional_special_token"
                  ]
                  lowercase__				 =							added_tokens_extra_ids + [
                      "an_additional_special_token"
                  ]

                  with open(os.path.join(_UpperCAmelCase,				"special_tokens_map.json"  ),				"w",				encoding="utf-8"  ) as outfile:
                       json.dump(_UpperCAmelCase,				_UpperCAmelCase  )
                  with open(os.path.join(_UpperCAmelCase,				"tokenizer_config.json"  ),				"w",				encoding="utf-8"  ) as outfile:
                       json.dump(_UpperCAmelCase,				_UpperCAmelCase  )

                  # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                  # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                  # "special_tokens_map.json" files
                  lowercase__				 =							tokenizer_class.from_pretrained(
                      _UpperCAmelCase,				)
                  self.assertIn(
                      "an_additional_special_token",				tokenizer_without_change_in_init.additional_special_tokens  )
                  # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                  self.assertEqual(
                      ["an_additional_special_token"],				tokenizer_without_change_in_init.convert_ids_to_tokens(
                          tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]  )  ),				)

                  # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                  lowercase__				 =							added_tokens_extra_ids + [AddedToken("a_new_additional_special_token",				lstrip=_UpperCAmelCase  )]
                  lowercase__				 =							tokenizer_class.from_pretrained(
                      _UpperCAmelCase,				additional_special_tokens=_UpperCAmelCase,				)

                  self.assertIn("a_new_additional_special_token",				tokenizer.additional_special_tokens  )
                  self.assertEqual(
                      ["a_new_additional_special_token"],				tokenizer.convert_ids_to_tokens(
                          tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]  )  ),				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							[]
        if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())  )

        if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())  )

        for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                  tokenizer_utils.save_pretrained(_UpperCAmelCase  )

                  lowercase__				 =							tokenizer_class.from_pretrained(_UpperCAmelCase  )

                  self.assertTrue(tokenizer.decode([255]  ) == ""  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_tokenizers(fast=_UpperCAmelCase,				do_lower_case=_UpperCAmelCase  )
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  lowercase__				 =							["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
                  lowercase__				 =							tokenizer.convert_tokens_to_string(_UpperCAmelCase  )

                  self.assertIsInstance(_UpperCAmelCase,				_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  lowercase__				 =							[
                      "bos_token",
                      "eos_token",
                      "unk_token",
                      "sep_token",
                      "pad_token",
                      "cls_token",
                      "mask_token",
                  ]

                  lowercase__				 =							0
                  lowercase__				 =							tokenizer.convert_ids_to_tokens(
                      _UpperCAmelCase,				skip_special_tokens=_UpperCAmelCase  )

                  for attr in attributes_list:
                       setattr(_UpperCAmelCase,				attr + "_id",				_UpperCAmelCase  )
                       self.assertEqual(getattr(_UpperCAmelCase,				_UpperCAmelCase  ),				_UpperCAmelCase  )
                       self.assertEqual(getattr(_UpperCAmelCase,				attr + "_id"  ),				_UpperCAmelCase  )

                       setattr(_UpperCAmelCase,				attr + "_id",				_UpperCAmelCase  )
                       self.assertEqual(getattr(_UpperCAmelCase,				_UpperCAmelCase  ),				_UpperCAmelCase  )
                       self.assertEqual(getattr(_UpperCAmelCase,				attr + "_id"  ),				_UpperCAmelCase  )

                  setattr(_UpperCAmelCase,				"additional_special_tokens_ids",				[]  )
                  self.assertListEqual(getattr(_UpperCAmelCase,				"additional_special_tokens"  ),				[]  )
                  self.assertListEqual(getattr(_UpperCAmelCase,				"additional_special_tokens_ids"  ),				[]  )

                  setattr(_UpperCAmelCase,				"additional_special_tokens_ids",				[token_id_to_test_setters]  )
                  self.assertListEqual(getattr(_UpperCAmelCase,				"additional_special_tokens"  ),				[token_to_test_setters]  )
                  self.assertListEqual(getattr(_UpperCAmelCase,				"additional_special_tokens_ids"  ),				[token_id_to_test_setters]  )




