



"""simple docstring"""





import json
import os
from datetime import date
from pathlib import Path

from tabulate import DataRow, TableFormat, tabulate


__lowerCAmelCase       :					List[str]      					=					TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow('''''', '''|''', '''|'''),
    datarow=DataRow('''''', '''|''', '''|'''),
    padding=1,
    with_header_hide=None,
)


__lowerCAmelCase       :					Optional[int]      					=					[]
__lowerCAmelCase       :					int      					=					[]

__lowerCAmelCase       :					Optional[int]      					=					{'''type''': '''section''', '''text''': {'''type''': '''plain_text''', '''text''': '''No failed tests! 🤗''', '''emoji''': True}}

__lowerCAmelCase       :					str      					=					[
    {
        '''type''': '''header''',
        '''text''': {
            '''type''': '''plain_text''',
            '''text''': F'''🤗 Accelerate nightly {os.environ.get("TEST_TYPE", "")} test results''',
            '''emoji''': True,
        },
    }
]

__lowerCAmelCase       :					Union[str, Any]      					=					0
for log in Path().glob('''*.log'''):
					__lowerCAmelCase       :					Dict      					=					0
					with open(log, '''r''') as f:
										for line in f:
															__lowerCAmelCase       :					Dict      					=					json.loads(line)
															if line.get('''nodeid''', '''''') != "":
																				__lowerCAmelCase       :					Optional[int]      					=					line['''nodeid''']
																				if line.get('''duration''', None) is not None:
																									__lowerCAmelCase       :					int      					=					F'''{line["duration"]:.4f}'''
																									if line.get('''outcome''', '''''') == "failed":
																														section_num_failed += 1
																														failed.append([test, duration, log.name.split('''_''')[0]])
																														total_num_failed += 1
					group_info.append([str(log), section_num_failed, failed])
					__lowerCAmelCase       :					Dict      					=					[]
					log.unlink()

__lowerCAmelCase       :					Union[str, Any]      					=					''''''
__lowerCAmelCase       :					Union[str, Any]      					=					[]
if total_num_failed > 0:
					for name, num_failed, failed_tests in group_info:
										if num_failed > 0:
															if num_failed == 1:
																				message += F"*{name[1:]}: {num_failed} failed test*\n"
															else:
																				message += F"*{name[1:]}: {num_failed} failed tests*\n"
															__lowerCAmelCase       :					List[str]      					=					[]
															__lowerCAmelCase       :					Optional[int]      					=					{}
															for test in failed_tests:
																				__lowerCAmelCase       :					Tuple      					=					test[0].split('''::''')
																				__lowerCAmelCase       :					Any      					=					data[0].split('''/''')[-1]
																				if data[0] not in filesafailed:
																									__lowerCAmelCase       :					Union[str, Any]      					=					[data[1:]]
																				else:
																									filesafailed[data[0]] += [data[1:]]
																				failed_table.append(data)

															__lowerCAmelCase       :					str      					=					[test[0] for test in failed_table]
															__lowerCAmelCase       :					Optional[int]      					=					list(set(files))
															# Count number of instances in failed_tests
															__lowerCAmelCase       :					Dict      					=					[]
															for file in individual_files:
																				table.append([file, len(filesafailed[file])])

															__lowerCAmelCase       :					List[Any]      					=					tabulate(
															    table,
															    headers=['''Test Location''', '''Num Failed'''],
															    tablefmt=hf_table_format,
															    stralign='''right''',
															)
															message += F"\n```\n{failed_table}\n```"
															all_filesafailed.append(filesafailed)
					if len(message) > 3000:
										__lowerCAmelCase       :					List[str]      					=					'''Too many failed tests, please see the full report in the Action results.'''
										__lowerCAmelCase       :					List[Any]      					=					len(err) + 10
										__lowerCAmelCase       :					int      					=					message[: 3000 - offset] + F'''\n...\n```\n{err}'''
					print(F'''### {message}''')
else:
					__lowerCAmelCase       :					Optional[Any]      					=					'''No failed tests! 🤗'''
					print(F'''## {message}''')
					payload.append(no_error_payload)

if os.environ.get('''TEST_TYPE''', '''''') != "":
					from slack_sdk import WebClient

					__lowerCAmelCase       :					List[str]      					=					WebClient(token=os.environ['''SLACK_API_TOKEN'''])
					if message != "No failed tests! 🤗":
										__lowerCAmelCase       :					List[str]      					=					{
										    '''type''': '''section''',
										    '''text''': {
										        '''type''': '''mrkdwn''',
										        '''text''': message,
										    },
										}
										payload.append(md_report)
										__lowerCAmelCase       :					Optional[int]      					=					{
										    '''type''': '''section''',
										    '''text''': {
										        '''type''': '''mrkdwn''',
										        '''text''': '''*For more details:*''',
										    },
										    '''accessory''': {
										        '''type''': '''button''',
										        '''text''': {
										            '''type''': '''plain_text''',
										            '''text''': '''Check Action results''',
										            '''emoji''': True,
										        },
										        '''url''': F'''https://github.com/{os.environ["GITHUB_REPOSITORY"]}/actions/runs/{os.environ["GITHUB_RUN_ID"]}''',
										    },
										}
										payload.append(action_button)
										__lowerCAmelCase       :					List[str]      					=					{
										    '''type''': '''context''',
										    '''elements''': [
										        {
										            '''type''': '''plain_text''',
										            '''text''': F'''Nightly {os.environ.get("TEST_TYPE")} test results for {date.today()}''',
										        }
										    ],
										}
										payload.append(date_report)
					__lowerCAmelCase       :					Optional[Any]      					=					client.chat_postMessage(channel='''#accelerate-ci-daily''', text=message, blocks=payload)
					__lowerCAmelCase       :					Union[str, Any]      					=					response.data['''ts''']
					for failed_file in all_filesafailed:
										for test_location, test_failures in failed_file.items():
															# Keep only the first instance of the test name
															__lowerCAmelCase       :					int      					=					''''''
															for i, row in enumerate(test_failures):
																				if row[0] != test_class:
																									__lowerCAmelCase       :					List[str]      					=					row[0]
																				else:
																									__lowerCAmelCase       :					Optional[Any]      					=					''''''

															__lowerCAmelCase       :					Union[str, Any]      					=					{
															    '''type''': '''section''',
															    '''text''': {
															        '''type''': '''mrkdwn''',
															        '''text''': F'''Test location: {test_location}\n```\n{tabulate(test_failures, headers=["Class", "Test"], tablefmt=hf_table_format, stralign="right")}\n```''',
															    },
															}

															client.chat_postMessage(
															    channel='''#accelerate-ci-daily''',
															    thread_ts=ts,
															    blocks=[payload],
															)






"""simple docstring"""





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


__lowerCAmelCase       :					str      					=					logging.get_logger(__name__)

__lowerCAmelCase       :					Tuple      					=					{
    '''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    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase			  =       '''nat'''

		_lowerCamelCase			  =       {
		    '''num_attention_heads''': '''num_heads''',
		    '''num_hidden_layers''': '''num_layers''',
		}





		def __init__(					self							,    _lowercase=4							,    _lowercase=3							,    _lowercase=6_4							,    _lowercase=[3, 4, 6, 5]							,    _lowercase=[2, 4, 8, 1_6]							,    _lowercase=7							,    _lowercase=3.0							,    _lowercase=True							,    _lowercase=0.0							,    _lowercase=0.0							,    _lowercase=0.1							,    _lowercase="gelu"							,    _lowercase=0.02							,    _lowercase=1E-5							,    _lowercase=0.0							,    _lowercase=None							,    _lowercase=None							,    **_lowercase							,    ) ->						Optional[Any]:







								'''simple docstring'''

								super().__init__(**_lowercase   )

								snake_case_   : Any						=			patch_size
								snake_case_   : Optional[Any]						=			num_channels
								snake_case_   : Optional[Any]						=			embed_dim
								snake_case_   : Tuple						=			depths
								snake_case_   : int						=			len(_lowercase   )
								snake_case_   : Optional[int]						=			num_heads
								snake_case_   : List[str]						=			kernel_size
								snake_case_   : str						=			mlp_ratio
								snake_case_   : str						=			qkv_bias
								snake_case_   : str						=			hidden_dropout_prob
								snake_case_   : Tuple						=			attention_probs_dropout_prob
								snake_case_   : Tuple						=			drop_path_rate
								snake_case_   : Dict						=			hidden_act
								snake_case_   : Union[str, Any]						=			layer_norm_eps
								snake_case_   : Tuple						=			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
								snake_case_   : Union[str, Any]						=			int(embed_dim * 2 ** (len(_lowercase   ) - 1)   )
								snake_case_   : Union[str, Any]						=			layer_scale_init_value
								snake_case_   : Optional[Any]						=			["""stem"""] + [f'stage{idx}' for idx in range(1							,    len(_lowercase   ) + 1   )]
								snake_case_			,		snake_case_   : Any						=			get_aligned_output_features_output_indices(
								    out_features=_lowercase							,    out_indices=_lowercase							,    stage_names=self.stage_names   )

