






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase   :   Optional[Any]      =    logging.get_logger(__name__)

__UpperCamelCase   :   int      =    {
    """caidas/swin2sr-classicalsr-x2-64""": (
        """https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"""
    ),
}


class 							__UpperCamelCase     (  _lowerCAmelCase ):
	__snake_case						:List[Any] =							'swin2sr'

	__snake_case						:Any =							{
	    'hidden_size': 'embed_dim',
	    'num_attention_heads': 'num_heads',
	    'num_hidden_layers': 'num_layers',
	}







	def __init__(	self   :				Union[str, Any]							,					_lowerCAmelCase   :				List[str]=64							,					_lowerCAmelCase   :				Any=1							,					_lowerCAmelCase   :				int=3							,					_lowerCAmelCase   :				str=180							,					_lowerCAmelCase   :				Dict=[6, 6, 6, 6, 6, 6]							,					_lowerCAmelCase   :				Optional[Any]=[6, 6, 6, 6, 6, 6]							,					_lowerCAmelCase   :				Any=8							,					_lowerCAmelCase   :				Any=2.0							,					_lowerCAmelCase   :				str=True							,					_lowerCAmelCase   :				Dict=0.0							,					_lowerCAmelCase   :				Dict=0.0							,					_lowerCAmelCase   :				str=0.1							,					_lowerCAmelCase   :				int="gelu"							,					_lowerCAmelCase   :				Union[str, Any]=False							,					_lowerCAmelCase   :				Optional[Any]=0.02							,					_lowerCAmelCase   :				Union[str, Any]=1e-5							,					_lowerCAmelCase   :				int=2							,					_lowerCAmelCase   :				Dict=1.0							,					_lowerCAmelCase   :				List[str]="1conv"							,					_lowerCAmelCase   :				Dict="pixelshuffle"							,					**_lowerCAmelCase   :				Optional[Any]							,					)		->			str:
		"""simple docstring"""







		super().__init__(**_lowerCAmelCase      )

		__lowercase   							=	image_size
		__lowercase   							=	patch_size
		__lowercase   							=	num_channels
		__lowercase   							=	embed_dim
		__lowercase   							=	depths
		__lowercase   							=	len(_lowerCAmelCase      )
		__lowercase   							=	num_heads
		__lowercase   							=	window_size
		__lowercase   							=	mlp_ratio
		__lowercase   							=	qkv_bias
		__lowercase   							=	hidden_dropout_prob
		__lowercase   							=	attention_probs_dropout_prob
		__lowercase   							=	drop_path_rate
		__lowercase   							=	hidden_act
		__lowercase   							=	use_absolute_embeddings
		__lowercase   							=	layer_norm_eps
		__lowercase   							=	initializer_range
		__lowercase   							=	upscale
		__lowercase   							=	img_range
		__lowercase   							=	resi_connection
		__lowercase   							=	upsampler






'''simple docstring'''





# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


__a  			=						"3"

print("Python version:", sys.version)
print("transformers version:", transformers.__version__)

try:
       import torch

       print("Torch version:", torch.__version__)
       print("Cuda available:", torch.cuda.is_available())
       print("Cuda version:", torch.version.cuda)
       print("CuDNN version:", torch.backends.cudnn.version())
       print("Number of GPUs available:", torch.cuda.device_count())
       print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
       print("Torch version:", None)

try:
       import deepspeed

       print("DeepSpeed version:", deepspeed.__version__)
except ImportError:
       print("DeepSpeed version:", None)

try:
       import tensorflow as tf

       print("TensorFlow version:", tf.__version__)
       print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
       print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
       print("TensorFlow version:", None)
