


"""simple docstring"""




import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests






def 							__lowercase       (			__lowerCAmelCase							:    Tuple ,   __lowerCAmelCase							:    List[str]=None       ):
							a__					=					None
							if token is not None:
														a__					=					{'Accept': 'application/vnd.github+json', 'Authorization': F'Bearer {token}'}

							a__					=					F'https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'
							a__					=					requests.get(__lowerCAmelCase ,   headers=__lowerCAmelCase       ).json()
							a__					=					{}

							try:
														job_links.update({job['name']: job['html_url'] for job in result['jobs']}       )
														a__					=					math.ceil((result['total_count'] - 1_0_0) / 1_0_0       )

														for i in range(__lowerCAmelCase       ):
																					a__					=					requests.get(url + F'&page={i + 2}' ,   headers=__lowerCAmelCase       ).json()
																					job_links.update({job['name']: job['html_url'] for job in result['jobs']}       )

														return job_links
							except Exception:
														print(F'Unknown error, could not fetch links:\n{traceback.format_exc()}'       )

							return {}






def 							__lowercase       (			__lowerCAmelCase							:    Union[str, Any] ,   __lowerCAmelCase							:    Optional[int]=None       ):
							a__					=					None
							if token is not None:
														a__					=					{'Accept': 'application/vnd.github+json', 'Authorization': F'Bearer {token}'}

							a__					=					F'https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'
							a__					=					requests.get(__lowerCAmelCase ,   headers=__lowerCAmelCase       ).json()
							a__					=					{}

							try:
														artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}       )
														a__					=					math.ceil((result['total_count'] - 1_0_0) / 1_0_0       )

														for i in range(__lowerCAmelCase       ):
																					a__					=					requests.get(url + F'&page={i + 2}' ,   headers=__lowerCAmelCase       ).json()
																					artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}       )

														return artifacts
							except Exception:
														print(F'Unknown error, could not fetch links:\n{traceback.format_exc()}'       )

							return {}






def 							__lowercase       (			__lowerCAmelCase							:    str ,   __lowerCAmelCase							:    Union[str, Any] ,   __lowerCAmelCase							:    int ,   __lowerCAmelCase							:    Dict       ):
							a__					=					None
							if token is not None:
														a__					=					{'Accept': 'application/vnd.github+json', 'Authorization': F'Bearer {token}'}

							a__					=					requests.get(__lowerCAmelCase ,   headers=__lowerCAmelCase ,   allow_redirects=__lowerCAmelCase       )
							a__					=					result.headers['Location']
							a__					=					requests.get(__lowerCAmelCase ,   allow_redirects=__lowerCAmelCase       )
							a__					=					os.path.join(__lowerCAmelCase ,   F'{artifact_name}.zip'       )
							with open(__lowerCAmelCase ,   'wb'       ) as fp:
														fp.write(response.content       )






def 							__lowercase       (			__lowerCAmelCase							:    Optional[Any] ,   __lowerCAmelCase							:    Union[str, Any]=None       ):
							a__					=					[]
							a__					=					[]
							a__					=					None

							with zipfile.ZipFile(__lowerCAmelCase       ) as z:
														for filename in z.namelist():
																					if not os.path.isdir(__lowerCAmelCase       ):
																												# read the file
																												if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
																																			with z.open(__lowerCAmelCase       ) as f:
																																										for line in f:
																																																	a__					=					line.decode('UTF-8'       ).strip()
																																																	if filename == "failures_line.txt":
																																																								try:
																																																															# `error_line` is the place where `error` occurs
																																																															a__					=					line[: line.index(': '       )]
																																																															a__					=					line[line.index(': '       ) + len(': '       ) :]
																																																															errors.append([error_line, error]       )
																																																								except Exception:
																																																															# skip un-related lines
																																																															pass
																																																	elif filename == "summary_short.txt" and line.startswith('FAILED '       ):
																																																								# `test` is the test method that failed
																																																								a__					=					line[len('FAILED '       ) :]
																																																								failed_tests.append(__lowerCAmelCase       )
																																																	elif filename == "job_name.txt":
																																																								a__					=					line

							if len(__lowerCAmelCase       ) != len(__lowerCAmelCase       ):
														raise ValueError(
														    F'`errors` and `failed_tests` should have the same number of elements. Got {len(__lowerCAmelCase       )} for `errors` '
														    F'and {len(__lowerCAmelCase       )} for `failed_tests` instead. The test reports in {artifact_zip_path} have some'
														    ' problem.'       )

							a__					=					None
							if job_name and job_links:
														a__					=					job_links.get(__lowerCAmelCase ,   __lowerCAmelCase       )

							# A list with elements of the form (line of error, error, failed test)
							a__					=					[x + [y] + [job_link] for x, y in zip(__lowerCAmelCase ,   __lowerCAmelCase       )]

							return result






def 							__lowercase       (			__lowerCAmelCase							:    List[str] ,   __lowerCAmelCase							:    Optional[int]=None       ):
							a__					=					[]

							a__					=					[os.path.join(__lowerCAmelCase ,   __lowerCAmelCase       ) for p in os.listdir(__lowerCAmelCase       ) if p.endswith('.zip'       )]
							for p in paths:
														errors.extend(get_errors_from_single_artifact(__lowerCAmelCase ,   job_links=__lowerCAmelCase       )       )

							return errors






def 							__lowercase       (			__lowerCAmelCase							:    Optional[Any] ,   __lowerCAmelCase							:    List[str]=None       ):
							a__					=					Counter()
							counter.update([x[1] for x in logs]       )
							a__					=					counter.most_common()
							a__					=					{}
							for error, count in counts:
														if error_filter is None or error not in error_filter:
																					a__					=					{'count': count, 'failed_tests': [(x[2], x[0]) for x in logs if x[1] == error]}

							a__					=					dict(sorted(r.items() ,   key=lambda __lowerCAmelCase       : item[1]["count"] ,   reverse=__lowerCAmelCase       )       )
							return r






def 							__lowercase       (			__lowerCAmelCase							:    int       ):
							a__					=					test.split('::'       )[0]
							if test.startswith('tests/models/'       ):
														a__					=					test.split('/'       )[2]
							else:
														a__					=					None

							return test






def 							__lowercase       (			__lowerCAmelCase							:    Any ,   __lowerCAmelCase							:    List[str]=None       ):
							a__					=					[(x[0], x[1], get_model(x[2]       )) for x in logs]
							a__					=					[x for x in logs if x[2] is not None]
							a__					=					{x[2] for x in logs}

							a__					=					{}
							for test in tests:
														a__					=					Counter()
														# count by errors in `test`
														counter.update([x[1] for x in logs if x[2] == test]       )
														a__					=					counter.most_common()
														a__					=					{error: count for error, count in counts if (error_filter is None or error not in error_filter)}
														a__					=					sum(error_counts.values()       )
														if n_errors > 0:
																					a__					=					{'count': n_errors, 'errors': error_counts}

							a__					=					dict(sorted(r.items() ,   key=lambda __lowerCAmelCase       : item[1]["count"] ,   reverse=__lowerCAmelCase       )       )
							return r






def 							__lowercase       (			__lowerCAmelCase							:    str       ):
							a__					=					'| no. | error | status |'
							a__					=					'|-:|:-|:-|'
							a__					=					[header, sep]
							for error in reduced_by_error:
														a__					=					reduced_by_error[error]['count']
														a__					=					F'| {count} | {error[:1_0_0]} |  |'
														lines.append(__lowerCAmelCase       )

							return "\n".join(__lowerCAmelCase       )






def 							__lowercase       (			__lowerCAmelCase							:    List[Any]       ):
							a__					=					'| model | no. of errors | major error | count |'
							a__					=					'|-:|-:|-:|-:|'
							a__					=					[header, sep]
							for model in reduced_by_model:
														a__					=					reduced_by_model[model]['count']
														a__				, a__					=					list(reduced_by_model[model]['errors'].items()       )[0]
														a__					=					F'| {model} | {count} | {error[:6_0]} | {_count} |'
														lines.append(__lowerCAmelCase       )

							return "\n".join(__lowerCAmelCase       )


if __name__ == "__main__":
						snake_case							:	Tuple					      =				argparse.ArgumentParser()
						# Required parameters
						parser.add_argument('''--workflow_run_id''', type=str, required=True, help='''A GitHub Actions workflow run id.''')
						parser.add_argument(
						    '''--output_dir''',
						    type=str,
						    required=True,
						    help='''Where to store the downloaded artifacts and other result files.''',
						)
						parser.add_argument('''--token''', default=None, type=str, help='''A token that has actions:read permission.''')
						snake_case							:	Optional[int]					      =				parser.parse_args()

						os.makedirs(args.output_dir, exist_ok=True)

						snake_case							:	Union[str, Any]					      =				get_job_links(args.workflow_run_id, token=args.token)
						snake_case							:	Optional[int]					      =				{}
						# To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
						# For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
						if _job_links:
												for k, v in _job_links.items():
																		# This is how GitHub actions combine job names.
																		if " / " in k:
																								snake_case							:	int					      =				k.find(''' / ''')
																								snake_case							:	Tuple					      =				k[index + len(''' / ''') :]
																		snake_case							:	Dict					      =				v
						with open(os.path.join(args.output_dir, '''job_links.json'''), '''w''', encoding='''UTF-8''') as fp:
												json.dump(job_links, fp, ensure_ascii=False, indent=4)

						snake_case							:	List[Any]					      =				get_artifacts_links(args.workflow_run_id, token=args.token)
						with open(os.path.join(args.output_dir, '''artifacts.json'''), '''w''', encoding='''UTF-8''') as fp:
												json.dump(artifacts, fp, ensure_ascii=False, indent=4)

						for idx, (name, url) in enumerate(artifacts.items()):
												download_artifact(name, url, args.output_dir, args.token)
												# Be gentle to GitHub
												time.sleep(1)

						snake_case							:	List[Any]					      =				get_all_errors(args.output_dir, job_links=job_links)

						# `e[1]` is the error
						snake_case							:	Union[str, Any]					      =				Counter()
						counter.update([e[1] for e in errors])

						# print the top 30 most common test errors
						snake_case							:	Optional[Any]					      =				counter.most_common(30)
						for item in most_common:
												print(item)

						with open(os.path.join(args.output_dir, '''errors.json'''), '''w''', encoding='''UTF-8''') as fp:
												json.dump(errors, fp, ensure_ascii=False, indent=4)

						snake_case							:	List[Any]					      =				reduce_by_error(errors)
						snake_case							:	str					      =				reduce_by_model(errors)

						snake_case							:	List[Any]					      =				make_github_table(reduced_by_error)
						snake_case							:	Tuple					      =				make_github_table_per_model(reduced_by_model)

						with open(os.path.join(args.output_dir, '''reduced_by_error.txt'''), '''w''', encoding='''UTF-8''') as fp:
												fp.write(sa)
						with open(os.path.join(args.output_dir, '''reduced_by_model.txt'''), '''w''', encoding='''UTF-8''') as fp:
												fp.write(sa)








import argparse
import json
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import (
    SwiftFormerConfig,
    SwiftFormerForImageClassification,
    ViTImageProcessor,
)
from transformers.utils import logging


logging.set_verbosity_info()
snake_case							:	Union[str, Any]					      =				logging.get_logger(__name__)

snake_case							:	Tuple					      =				torch.device('''cpu''')






def 							__lowercase       (			):
							a__					=					'http://images.cocodataset.org/val2017/000000039769.jpg'
							a__					=					Image.open(requests.get(__lowerCAmelCase ,   stream=__lowerCAmelCase       ).raw       )
							return im






def 							__lowercase       (			__lowerCAmelCase							:    List[str]       ):
							if swiftformer_name == "swiftformer_xs":
														return torch.tensor([-2.1_7_0_3E0_0, 2.1_1_0_7E0_0, -2.0_8_1_1E0_0, 8.8_6_8_5E-0_1, 2.4_3_6_0E-0_1]       )

							elif swiftformer_name == "swiftformer_s":
														return torch.tensor([3.9_6_3_6E-0_1, 2.3_4_7_8E-0_1, -1.6_9_6_3E0_0, -1.7_3_8_1E0_0, -8.6_3_3_7E-0_1]       )

							elif swiftformer_name == "swiftformer_l1":
														return torch.tensor([-4.2_7_6_8E-0_1, -4.7_4_2_9E-0_1, -1.0_8_9_7E0_0, -1.0_2_4_8E0_0, 3.5_5_2_3E-0_2]       )

							elif swiftformer_name == "swiftformer_l3":
														return torch.tensor([-2.5_3_3_0E-0_1, 2.4_2_1_1E-0_1, -6.0_1_8_5E-0_1, -8.2_7_8_9E-0_1, -6.0_4_4_6E-0_2]       )






def 							__lowercase       (			__lowerCAmelCase							:    List[Any] ,   __lowerCAmelCase							:    Optional[int] ,   __lowerCAmelCase							:    str       ):
							a__					=					dct.pop(__lowerCAmelCase       )
							a__					=					val






def 							__lowercase       (			__lowerCAmelCase							:    int       ):
							a__					=					[]
							for k in state_dict.keys():
														a__					=					k
														if ".pwconv" in k:
																					a__					=					k_new.replace('.pwconv' ,   '.point_wise_conv'       )
														if ".dwconv" in k:
																					a__					=					k_new.replace('.dwconv' ,   '.depth_wise_conv'       )
														if ".Proj." in k:
																					a__					=					k_new.replace('.Proj.' ,   '.proj.'       )
														if "patch_embed" in k_new:
																					a__					=					k_new.replace('patch_embed' ,   'swiftformer.patch_embed.patch_embedding'       )
														if "network" in k_new:
																					a__					=					k_new.split('.'       )
																					if ls[2].isdigit():
																												a__					=					'swiftformer.encoder.network.' + ls[1] + '.blocks.' + ls[2] + '.' + '.'.join(ls[3:]       )
																					else:
																												a__					=					k_new.replace('network' ,   'swiftformer.encoder.network'       )
														rename_keys.append((k, k_new)       )
							return rename_keys






@torch.no_grad()
def 							__lowercase       (			__lowerCAmelCase							:    Optional[Any] ,   __lowerCAmelCase							:    str ,   __lowerCAmelCase							:    str       ):
							a__					=					SwiftFormerConfig()

							# dataset (ImageNet-21k only or also fine-tuned on ImageNet 2012), patch_size and image_size
							a__					=					1_0_0_0
							a__					=					'huggingface/label-files'
							a__					=					'imagenet-1k-id2label.json'
							a__					=					json.load(open(hf_hub_download(__lowerCAmelCase ,   __lowerCAmelCase ,   repo_type='dataset'       ) ,   'r'       )       )
							a__					=					{int(__lowerCAmelCase       ): v for k, v in idalabel.items()}
							a__					=					idalabel
							a__					=					{v: k for k, v in idalabel.items()}

							# size of the architecture
							if swiftformer_name == "swiftformer_xs":
														a__					=					[3, 3, 6, 4]
														a__					=					[4_8, 5_6, 1_1_2, 2_2_0]

							elif swiftformer_name == "swiftformer_s":
														a__					=					[3, 3, 9, 6]
														a__					=					[4_8, 6_4, 1_6_8, 2_2_4]

							elif swiftformer_name == "swiftformer_l1":
														a__					=					[4, 3, 1_0, 5]
														a__					=					[4_8, 9_6, 1_9_2, 3_8_4]

							elif swiftformer_name == "swiftformer_l3":
														a__					=					[4, 4, 1_2, 6]
														a__					=					[6_4, 1_2_8, 3_2_0, 5_1_2]

							# load state_dict of original model, remove and rename some keys
							if original_ckpt:
														if original_ckpt.startswith('https'       ):
																					a__					=					torch.hub.load_state_dict_from_url(__lowerCAmelCase ,   map_location='cpu' ,   check_hash=__lowerCAmelCase       )
														else:
																					a__					=					torch.load(__lowerCAmelCase ,   map_location='cpu'       )
							a__					=					checkpoint

							a__					=					create_rename_keys(__lowerCAmelCase       )
							for rename_key_src, rename_key_dest in rename_keys:
														rename_key(__lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase       )

							# load HuggingFace model
							a__					=					SwiftFormerForImageClassification(__lowerCAmelCase       ).eval()
							hf_model.load_state_dict(__lowerCAmelCase       )

							# prepare test inputs
							a__					=					prepare_img()
							a__					=					ViTImageProcessor.from_pretrained('preprocessor_config'       )
							a__					=					processor(images=__lowerCAmelCase ,   return_tensors='pt'       )

							# compare outputs from both models
							a__					=					get_expected_output(__lowerCAmelCase       )
							a__					=					hf_model(inputs['pixel_values']       ).logits

							assert hf_logits.shape == torch.Size([1, 1_0_0_0]       )
							assert torch.allclose(hf_logits[0, 0:5] ,   __lowerCAmelCase ,   atol=1E-3       )

							Path(__lowerCAmelCase       ).mkdir(exist_ok=__lowerCAmelCase       )
							print(F'Saving model {swiftformer_name} to {pytorch_dump_folder_path}'       )
							hf_model.save_pretrained(__lowerCAmelCase       )


if __name__ == "__main__":
						snake_case							:	int					      =				argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    '''--swiftformer_name''',
						    default='''swiftformer_xs''',
						    choices=['''swiftformer_xs''', '''swiftformer_s''', '''swiftformer_l1''', '''swiftformer_l3'''],
						    type=str,
						    help='''Name of the SwiftFormer model you\'d like to convert.''',
						)
						parser.add_argument(
						    '''--pytorch_dump_folder_path''',
						    default='''./converted_outputs/''',
						    type=str,
						    help='''Path to the output PyTorch model directory.''',
						)
						parser.add_argument('''--original_ckpt''', default=None, type=str, help='''Path to the original model checkpoint.''')

						snake_case							:	Optional[int]					      =				parser.parse_args()
						convert_swiftformer_checkpoint(args.swiftformer_name, args.pytorch_dump_folder_path, args.original_ckpt)




