"""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		( lowerCAmelCase			):
      snake_case__    :     torch.FloatTensor






class 				_A		( lowerCAmelCase						,					lowerCAmelCase			):

      @register_to_config
      def __init__(		self	, __lowerCAmelCase = 3	, __lowerCAmelCase = 3	, __lowerCAmelCase = ("DownEncoderBlock2D",)	, __lowerCAmelCase = ("UpDecoderBlock2D",)	, __lowerCAmelCase = (64,)	, __lowerCAmelCase = 1	, __lowerCAmelCase = "silu"	, __lowerCAmelCase = 3	, __lowerCAmelCase = 32	, __lowerCAmelCase = 256	, __lowerCAmelCase = 32	, __lowerCAmelCase = None	, __lowerCAmelCase = 0.1_8_2_1_5	, __lowerCAmelCase = "group"	, ):







            """simple docstring"""



            super().__init__()

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

            lowercase														=			vq_embed_dim if vq_embed_dim is not None else latent_channels

            lowercase														=			nn.Convad(__lowerCAmelCase	, __lowerCAmelCase	, 1		)
            lowercase														=			VectorQuantizer(__lowerCAmelCase	, __lowerCAmelCase	, beta=0.2_5	, remap=__lowerCAmelCase	, sane_index_shape=__lowerCAmelCase		)
            lowercase														=			nn.Convad(__lowerCAmelCase	, __lowerCAmelCase	, 1		)

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

      @apply_forward_hook
      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = True		):







            """simple docstring"""



            lowercase														=			self.encoder(__lowerCAmelCase		)
            lowercase														=			self.quant_conv(__lowerCAmelCase		)

            if not return_dict:
                  return (h,)

            return VQEncoderOutput(latents=__lowerCAmelCase		)

      @apply_forward_hook
      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = False	, __lowerCAmelCase = True		):







            """simple docstring"""



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

            if not return_dict:
                  return (dec,)

            return DecoderOutput(sample=__lowerCAmelCase		)







      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = True		):







            """simple docstring"""



            lowercase														=			sample
            lowercase														=			self.encode(__lowerCAmelCase		).latents
            lowercase														=			self.decode(__lowerCAmelCase		).sample

            if not return_dict:
                  return (dec,)

            return DecoderOutput(sample=__lowerCAmelCase		)




"""simple docstring"""






# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser


def     UpperCAmelCase__ (       )				->					Tuple:
      '''simple docstring'''


      lowercase														=			ArgumentParser("""Accelerate CLI tool"""      ,	usage="""accelerate <command> [<args>]"""      ,	allow_abbrev=lowerCAmelCase__	)
      lowercase														=			parser.add_subparsers(help="""accelerate command helpers"""	)

      # Register commands
      get_config_parser(subparsers=lowerCAmelCase__	)
      env_command_parser(subparsers=lowerCAmelCase__	)
      launch_command_parser(subparsers=lowerCAmelCase__	)
      tpu_command_parser(subparsers=lowerCAmelCase__	)
      test_command_parser(subparsers=lowerCAmelCase__	)

      # Let's go
      lowercase														=			parser.parse_args()

      if not hasattr(lowerCAmelCase__      ,	"""func"""	):
            parser.print_help()
            exit(1	)

      # Run
      args.func(lowerCAmelCase__	)


if __name__ == "__main__":
       main()



