






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


a_							=    logging.get_logger(__name__)

a_							=    {
    '''shi-labs/nat-mini-in1k-224''': '''https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json''',
    # See all Nat models at https://huggingface.co/models?filter=nat
}


class      lowercase__     (			_UpperCAmelCase				,					_UpperCAmelCase	):
	a_         ="""nat"""

	a_         ={
	    """num_attention_heads""": """num_heads""",
	    """num_hidden_layers""": """num_layers""",
	}

	def __init__(							self		,    __UpperCAmelCase=4		,    __UpperCAmelCase=3		,    __UpperCAmelCase=64		,    __UpperCAmelCase=[3, 4, 6, 5]		,    __UpperCAmelCase=[2, 4, 8, 16]		,    __UpperCAmelCase=7		,    __UpperCAmelCase=3.0		,    __UpperCAmelCase=True		,    __UpperCAmelCase=0.0		,    __UpperCAmelCase=0.0		,    __UpperCAmelCase=0.1		,    __UpperCAmelCase="gelu"		,    __UpperCAmelCase=0.02		,    __UpperCAmelCase=1E-5		,    __UpperCAmelCase=0.0		,    __UpperCAmelCase=None		,    __UpperCAmelCase=None		,    **__UpperCAmelCase		,    )->					int:







							'''simple docstring'''





							super().__init__(**__UpperCAmelCase       )

							lowerCAmelCase__       =						patch_size
							lowerCAmelCase__       =						num_channels
							lowerCAmelCase__       =						embed_dim
							lowerCAmelCase__       =						depths
							lowerCAmelCase__       =						len(__UpperCAmelCase       )
							lowerCAmelCase__       =						num_heads
							lowerCAmelCase__       =						kernel_size
							lowerCAmelCase__       =						mlp_ratio
							lowerCAmelCase__       =						qkv_bias
							lowerCAmelCase__       =						hidden_dropout_prob
							lowerCAmelCase__       =						attention_probs_dropout_prob
							lowerCAmelCase__       =						drop_path_rate
							lowerCAmelCase__       =						hidden_act
							lowerCAmelCase__       =						layer_norm_eps
							lowerCAmelCase__       =						initializer_range
							# we set the hidden_size attribute in order to make Nat work with VisionEncoderDecoderModel
							# this indicates the channel dimension after the last stage of the model
							lowerCAmelCase__       =						int(embed_dim * 2 ** (len(__UpperCAmelCase       ) - 1)       )
							lowerCAmelCase__       =						layer_scale_init_value
							lowerCAmelCase__       =						["stem"] + [F"stage{idx}" for idx in range(1		,    len(__UpperCAmelCase       ) + 1       )]
							lowerCAmelCase__      ,							lowerCAmelCase__       =						get_aligned_output_features_output_indices(
							    out_features=__UpperCAmelCase		,    out_indices=__UpperCAmelCase		,    stage_names=self.stage_names       )














# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


a_							=    subprocess.check_output('''git merge-base main HEAD'''.split()).decode('''utf-8''')
a_							=    subprocess.check_output(F"git diff --name-only {fork_point_sha}".split()).decode('''utf-8''').split()

a_							=    '''|'''.join(sys.argv[1:])
a_							=    re.compile(rF"^({joined_dirs}).*?\.py$")

a_							=    [x for x in modified_files if regex.match(x)]
print(''' '''.join(relevant_modified_files), end='''''')






