
"""simple docstring"""




import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCAmelCase__							=				{
    'facebook/mask2former-swin-small-coco-instance': (
        'https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

lowerCAmelCase__							=				logging.get_logger(__name__)





class  snake_case     (							__lowercase   ):
							UpperCAmelCase__						     =      '''mask2former'''
							UpperCAmelCase__						     =      ['''swin''']
							UpperCAmelCase__						     =      {'''hidden_size''': '''hidden_dim'''}

							def __init__(self       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = 2_56       ,       SCREAMING_SNAKE_CASE_ = 2_56       ,       SCREAMING_SNAKE_CASE_ = 2_56       ,       SCREAMING_SNAKE_CASE_ = 10_24       ,       SCREAMING_SNAKE_CASE_ = "relu"       ,       SCREAMING_SNAKE_CASE_ = 6       ,       SCREAMING_SNAKE_CASE_ = 10       ,       SCREAMING_SNAKE_CASE_ = 8       ,       SCREAMING_SNAKE_CASE_ = 0.0       ,       SCREAMING_SNAKE_CASE_ = 20_48       ,       SCREAMING_SNAKE_CASE_ = False       ,       SCREAMING_SNAKE_CASE_ = False       ,       SCREAMING_SNAKE_CASE_ = 4       ,       SCREAMING_SNAKE_CASE_ = 2_55       ,       SCREAMING_SNAKE_CASE_ = 1_00       ,       SCREAMING_SNAKE_CASE_ = 0.1       ,       SCREAMING_SNAKE_CASE_ = 2.0       ,       SCREAMING_SNAKE_CASE_ = 5.0       ,       SCREAMING_SNAKE_CASE_ = 5.0       ,       SCREAMING_SNAKE_CASE_ = 1_25_44       ,       SCREAMING_SNAKE_CASE_ = 3.0       ,       SCREAMING_SNAKE_CASE_ = 0.75       ,       SCREAMING_SNAKE_CASE_ = 0.02       ,       SCREAMING_SNAKE_CASE_ = 1.0       ,       SCREAMING_SNAKE_CASE_ = True       ,       SCREAMING_SNAKE_CASE_ = [4, 8, 16, 32]       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									if backbone_config is None:
											logger.info('''`backbone_config` is `None`. Initializing the config with the default `Swin` backbone.'''    )
											SCREAMING_SNAKE_CASE_						 = CONFIG_MAPPING['''swin'''](
											    image_size=2_24       ,       in_channels=3       ,       patch_size=4       ,       embed_dim=96       ,       depths=[2, 2, 18, 2]       ,       num_heads=[3, 6, 12, 24]       ,       window_size=7       ,       drop_path_rate=0.3       ,       use_absolute_embeddings=SCREAMING_SNAKE_CASE_       ,       out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']       ,       )

									if isinstance(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):
											SCREAMING_SNAKE_CASE_						 = backbone_config.pop('''model_type'''    )
											SCREAMING_SNAKE_CASE_						 = CONFIG_MAPPING[backbone_model_type]
											SCREAMING_SNAKE_CASE_						 = config_class.from_dict(SCREAMING_SNAKE_CASE_    )

									# verify that the backbone is supported
									if backbone_config.model_type not in self.backbones_supported:
											logger.warning_once(
											    f'Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '
											    f'Supported model types: {",".join(self.backbones_supported    )}'    )

									SCREAMING_SNAKE_CASE_						 = backbone_config
									SCREAMING_SNAKE_CASE_						 = feature_size
									SCREAMING_SNAKE_CASE_						 = mask_feature_size
									SCREAMING_SNAKE_CASE_						 = hidden_dim
									SCREAMING_SNAKE_CASE_						 = encoder_feedforward_dim
									SCREAMING_SNAKE_CASE_						 = activation_function
									SCREAMING_SNAKE_CASE_						 = encoder_layers
									SCREAMING_SNAKE_CASE_						 = decoder_layers
									SCREAMING_SNAKE_CASE_						 = num_attention_heads
									SCREAMING_SNAKE_CASE_						 = dropout
									SCREAMING_SNAKE_CASE_						 = dim_feedforward
									SCREAMING_SNAKE_CASE_						 = pre_norm
									SCREAMING_SNAKE_CASE_						 = enforce_input_projection
									SCREAMING_SNAKE_CASE_						 = common_stride
									SCREAMING_SNAKE_CASE_						 = ignore_value
									SCREAMING_SNAKE_CASE_						 = num_queries
									SCREAMING_SNAKE_CASE_						 = no_object_weight
									SCREAMING_SNAKE_CASE_						 = class_weight
									SCREAMING_SNAKE_CASE_						 = mask_weight
									SCREAMING_SNAKE_CASE_						 = dice_weight
									SCREAMING_SNAKE_CASE_						 = train_num_points
									SCREAMING_SNAKE_CASE_						 = oversample_ratio
									SCREAMING_SNAKE_CASE_						 = importance_sample_ratio
									SCREAMING_SNAKE_CASE_						 = init_std
									SCREAMING_SNAKE_CASE_						 = init_xavier_std
									SCREAMING_SNAKE_CASE_						 = use_auxiliary_loss
									SCREAMING_SNAKE_CASE_						 = feature_strides
									SCREAMING_SNAKE_CASE_						 = output_auxiliary_logits
									SCREAMING_SNAKE_CASE_						 = decoder_layers

									super().__init__(**SCREAMING_SNAKE_CASE_    )

							@classmethod
							def _lowercase					(cls       ,       SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									return cls(
									    backbone_config=SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_       ,       )







							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = copy.deepcopy(self.__dict__    )
									SCREAMING_SNAKE_CASE_						 = self.backbone_config.to_dict()
									SCREAMING_SNAKE_CASE_						 = self.__class__.model_type
									return output

"""simple docstring"""




import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
						from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
						import torch_xla.core.xla_model as xm



def        _lowerCamelCase ( __a    ):
		if is_torch_version('''<''',							'''2.0.0'''    ) or not hasattr(__a,							'''_dynamo'''    ):
				return False
		return isinstance(__a,							torch._dynamo.eval_frame.OptimizedModule    )



def        _lowerCamelCase ( __a,							__a = True    ):
		SCREAMING_SNAKE_CASE_						 = (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

		SCREAMING_SNAKE_CASE_						 = is_compiled_module(__a    )
		if is_compiled:
				SCREAMING_SNAKE_CASE_						 = model
				SCREAMING_SNAKE_CASE_						 = model._orig_mod

		if is_deepspeed_available():
				options += (DeepSpeedEngine,)

		while isinstance(__a,							__a    ):
				SCREAMING_SNAKE_CASE_						 = model.module

		if not keep_fpaa_wrapper:
				SCREAMING_SNAKE_CASE_						 = getattr(__a,							'''forward'''    )
				SCREAMING_SNAKE_CASE_						 = model.__dict__.pop('''_original_forward''',							__a    )
				if original_forward is not None:
						while hasattr(__a,							'''__wrapped__'''    ):
								SCREAMING_SNAKE_CASE_						 = forward.__wrapped__
								if forward == original_forward:
										break
						SCREAMING_SNAKE_CASE_						 = forward
				if getattr(__a,							'''_converted_to_transformer_engine''',							__a    ):
						convert_model(__a,							to_transformer_engine=__a    )

		if is_compiled:
				SCREAMING_SNAKE_CASE_						 = model
				SCREAMING_SNAKE_CASE_						 = compiled_model

		return model



def        _lowerCamelCase ( ):
		PartialState().wait_for_everyone()



def        _lowerCamelCase ( __a,							__a    ):
		if PartialState().distributed_type == DistributedType.TPU:
				xm.save(__a,							__a    )
		elif PartialState().local_process_index == 0:
				torch.save(__a,							__a    )



@contextmanager
def        _lowerCamelCase ( **__a    ):
		for key, value in kwargs.items():
				SCREAMING_SNAKE_CASE_						 = str(__a    )

		yield

		for key in kwargs:
				if key.upper() in os.environ:
						del os.environ[key.upper()]



def        _lowerCamelCase ( __a    ):
		if not hasattr(__a,							'''__qualname__'''    ) and not hasattr(__a,							'''__name__'''    ):
				SCREAMING_SNAKE_CASE_						 = getattr(__a,							'''__class__''',							__a    )
		if hasattr(__a,							'''__qualname__'''    ):
				return obj.__qualname__
		if hasattr(__a,							'''__name__'''    ):
				return obj.__name__
		return str(__a    )



def        _lowerCamelCase ( __a,							__a    ):
		for key, value in source.items():
				if isinstance(__a,							__a    ):
						SCREAMING_SNAKE_CASE_						 = destination.setdefault(__a,							{}    )
						merge_dicts(__a,							__a    )
				else:
						SCREAMING_SNAKE_CASE_						 = value

		return destination



def        _lowerCamelCase ( __a = None    ):
		if port is None:
				SCREAMING_SNAKE_CASE_						 = 29_500
		with socket.socket(socket.AF_INET,							socket.SOCK_STREAM    ) as s:
				return s.connect_ex(('''localhost''', port)    ) == 0