"""simple docstring"""


from dataclasses import dataclass
from typing import Optional, Tuple, Union

import torch
import torch.nn as nn

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, VectorQuantizer






@dataclass
class    a__    (   __SCREAMING_SNAKE_CASE	):
   snake_case_							=      42






class    a__    (   __SCREAMING_SNAKE_CASE					,					__SCREAMING_SNAKE_CASE	):


   @register_to_config
   def __init__(     self,				_UpperCAmelCase = 3,				_UpperCAmelCase = 3,				_UpperCAmelCase = ("DownEncoderBlock2D",),				_UpperCAmelCase = ("UpDecoderBlock2D",),				_UpperCAmelCase = (64,),				_UpperCAmelCase = 1,				_UpperCAmelCase = "silu",				_UpperCAmelCase = 3,				_UpperCAmelCase = 32,				_UpperCAmelCase = 256,				_UpperCAmelCase = 32,				_UpperCAmelCase = None,				_UpperCAmelCase = 0.18_215,				_UpperCAmelCase = "group",				):
        '''simple docstring'''



        super().__init__()

        # pass init params to Encoder
        lowercase__				 =							Encoder(
            in_channels=__snake_case,				out_channels=__snake_case,				down_block_types=__snake_case,				block_out_channels=__snake_case,				layers_per_block=__snake_case,				act_fn=__snake_case,				norm_num_groups=__snake_case,				double_z=__snake_case,				)

        lowercase__				 =							vq_embed_dim if vq_embed_dim is not None else latent_channels

        lowercase__				 =							nn.Convad(__snake_case,				__snake_case,				1  )
        lowercase__				 =							VectorQuantizer(__snake_case,				__snake_case,				beta=0.25,				remap=__snake_case,				sane_index_shape=__snake_case  )
        lowercase__				 =							nn.Convad(__snake_case,				__snake_case,				1  )

        # pass init params to Decoder
        lowercase__				 =							Decoder(
            in_channels=__snake_case,				out_channels=__snake_case,				up_block_types=__snake_case,				block_out_channels=__snake_case,				layers_per_block=__snake_case,				act_fn=__snake_case,				norm_num_groups=__snake_case,				norm_type=__snake_case,				)


   @apply_forward_hook
   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase = True  ):
        '''simple docstring'''



        lowercase__				 =							self.encoder(__snake_case  )
        lowercase__				 =							self.quant_conv(__snake_case  )

        if not return_dict:
             return (h,)

        return VQEncoderOutput(latents=__snake_case  )


   @apply_forward_hook
   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase = False,				_UpperCAmelCase = True  ):
        '''simple docstring'''



        if not force_not_quantize:
             lowercase__				 =							self.quantize(__snake_case  )
        else:
             lowercase__				 =							h
        lowercase__				 =							self.post_quant_conv(__snake_case  )
        lowercase__				 =							self.decoder(__snake_case,				quant if self.config.norm_type == "spatial" else None  )

        if not return_dict:
             return (dec,)

        return DecoderOutput(sample=__snake_case  )


   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase = True  ):
        '''simple docstring'''



        lowercase__				 =							sample
        lowercase__				 =							self.encode(__snake_case  ).latents
        lowercase__				 =							self.decode(__snake_case  ).sample

        if not return_dict:
             return (dec,)

        return DecoderOutput(sample=__snake_case  )





"""simple docstring"""


import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class    a__    (   _a					,					unittest.TestCase	):
   snake_case_							=      MgpstrTokenizer
   snake_case_							=      False
   snake_case_							=      {}
   snake_case_							=      False


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



        super().setUp()

        # fmt: off
        lowercase__				 =							["[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__				 =							dict(zip(_UpperCAmelCase,				range(len(_UpperCAmelCase  )  )  )  )

        lowercase__				 =							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(_UpperCAmelCase  ) + "\n"  )


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



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


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



        lowercase__				 =							"tester"
        lowercase__				 =							"tester"
        return input_text, output_text


   @unittest.skip("MGP-STR always lower cases letters."  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


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



        lowercase__				 =							self.get_tokenizers(do_lower_case=_UpperCAmelCase  )
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  lowercase__				 =							"[SPECIAL_TOKEN]"

                  tokenizer.add_special_tokens({"cls_token": special_token}  )
                  lowercase__				 =							tokenizer.encode([special_token],				add_special_tokens=_UpperCAmelCase  )
                  self.assertEqual(len(_UpperCAmelCase  ),				1  )

                  lowercase__				 =							tokenizer.decode(_UpperCAmelCase,				skip_special_tokens=_UpperCAmelCase  )
                  self.assertTrue(special_token not in decoded  )


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



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

                  lowercase__				 =							tokenizer.tokenize(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

                  lowercase__				 =							tokenizer.convert_ids_to_tokens(_UpperCAmelCase  )
                  self.assertNotEqual(len(_UpperCAmelCase  ),				0  )
                  lowercase__				 =							tokenizer.decode(_UpperCAmelCase  )
                  self.assertIsInstance(_UpperCAmelCase,				_UpperCAmelCase  )

                  self.assertEqual(text_a.replace(" ",				""  ),				_UpperCAmelCase  )


   @unittest.skip("MGP-STR tokenizer only handles one sequence."  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass




