"""simple docstring"""







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

import requests



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

     lowercase_			:       List[Any]									=			F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'''
     lowercase_			:       Tuple									=			requests.get(__SCREAMING_SNAKE_CASE  ,    headers=__SCREAMING_SNAKE_CASE   ).json()
     lowercase_			:       int									=			{}

     try:
          job_links.update({job['name']: job['html_url'] for job in result['jobs']}   )
          lowercase_			:       Dict									=			math.ceil((result['total_count'] - 1_00) / 1_00   )

          for i in range(__SCREAMING_SNAKE_CASE   ):
               lowercase_			:       Any									=			requests.get(url + F'''&page={i + 2}'''  ,    headers=__SCREAMING_SNAKE_CASE   ).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__( __SCREAMING_SNAKE_CASE							:  Union[str, Any]  ,    __SCREAMING_SNAKE_CASE							:  Tuple=None   ):
     lowercase_			:       Any									=			None
     if token is not None:
          lowercase_			:       Any									=			{'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

     lowercase_			:       Tuple									=			F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'''
     lowercase_			:       List[Any]									=			requests.get(__SCREAMING_SNAKE_CASE  ,    headers=__SCREAMING_SNAKE_CASE   ).json()
     lowercase_			:       str									=			{}

     try:
          artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}   )
          lowercase_			:       Tuple									=			math.ceil((result['total_count'] - 1_00) / 1_00   )

          for i in range(__SCREAMING_SNAKE_CASE   ):
               lowercase_			:       Any									=			requests.get(url + F'''&page={i + 2}'''  ,    headers=__SCREAMING_SNAKE_CASE   ).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__( __SCREAMING_SNAKE_CASE							:  Union[str, Any]  ,    __SCREAMING_SNAKE_CASE							:  Any  ,    __SCREAMING_SNAKE_CASE							:  Dict  ,    __SCREAMING_SNAKE_CASE							:  Dict   ):
     lowercase_			:       Tuple									=			None
     if token is not None:
          lowercase_			:       Tuple									=			{'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

     lowercase_			:       Optional[int]									=			requests.get(__SCREAMING_SNAKE_CASE  ,    headers=__SCREAMING_SNAKE_CASE  ,    allow_redirects=__SCREAMING_SNAKE_CASE   )
     lowercase_			:       Dict									=			result.headers['Location']
     lowercase_			:       List[str]									=			requests.get(__SCREAMING_SNAKE_CASE  ,    allow_redirects=__SCREAMING_SNAKE_CASE   )
     lowercase_			:       Optional[Any]									=			os.path.join(__SCREAMING_SNAKE_CASE  ,    F'''{artifact_name}.zip'''   )
     with open(__SCREAMING_SNAKE_CASE  ,    'wb'   ) as fp:
          fp.write(response.content   )



def     lowercase__( __SCREAMING_SNAKE_CASE							:  Optional[Any]  ,    __SCREAMING_SNAKE_CASE							:  str=None   ):
     lowercase_			:       str									=			[]
     lowercase_			:       Tuple									=			[]
     lowercase_			:       List[str]									=			None

     with zipfile.ZipFile(__SCREAMING_SNAKE_CASE   ) as z:
          for filename in z.namelist():
               if not os.path.isdir(__SCREAMING_SNAKE_CASE   ):
                    # read the file
                    if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
                         with z.open(__SCREAMING_SNAKE_CASE   ) as f:
                              for line in f:
                                   lowercase_			:       List[Any]									=			line.decode('UTF-8'   ).strip()
                                   if filename == "failures_line.txt":
                                        try:
                                             # `error_line` is the place where `error` occurs
                                             lowercase_			:       Union[str, Any]									=			line[: line.index(': '   )]
                                             lowercase_			:       Tuple									=			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
                                        lowercase_			:       Optional[Any]									=			line[len('FAILED '   ) :]
                                        failed_tests.append(__SCREAMING_SNAKE_CASE   )
                                   elif filename == "job_name.txt":
                                        lowercase_			:       Tuple									=			line

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

     lowercase_			:       str									=			None
     if job_name and job_links:
          lowercase_			:       Tuple									=			job_links.get(__SCREAMING_SNAKE_CASE  ,    __SCREAMING_SNAKE_CASE   )

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

     return result



def     lowercase__( __SCREAMING_SNAKE_CASE							:  Optional[int]  ,    __SCREAMING_SNAKE_CASE							:  Optional[Any]=None   ):
     lowercase_			:       Optional[Any]									=			[]

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

     return errors



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

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



def     lowercase__( __SCREAMING_SNAKE_CASE							:  int   ):
     lowercase_			:       List[Any]									=			test.split('::'   )[0]
     if test.startswith('tests/models/'   ):
          lowercase_			:       str									=			test.split('/'   )[2]
     else:
          lowercase_			:       Optional[int]									=			None

     return test



def     lowercase__( __SCREAMING_SNAKE_CASE							:  Union[str, Any]  ,    __SCREAMING_SNAKE_CASE							:  List[Any]=None   ):
     lowercase_			:       Optional[Any]									=			[(x[0], x[1], get_model(x[2]   )) for x in logs]
     lowercase_			:       str									=			[x for x in logs if x[2] is not None]
     lowercase_			:       Tuple									=			{x[2] for x in logs}

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

     lowercase_			:       List[str]									=			dict(sorted(r.items()  ,    key=lambda __SCREAMING_SNAKE_CASE   : item[1]["count"]  ,    reverse=__SCREAMING_SNAKE_CASE   )   )
     return r



def     lowercase__( __SCREAMING_SNAKE_CASE							:  Optional[Any]   ):
     lowercase_			:       int									=			'| no. | error | status |'
     lowercase_			:       Optional[Any]									=			'|-:|:-|:-|'
     lowercase_			:       Any									=			[header, sep]
     for error in reduced_by_error:
          lowercase_			:       List[str]									=			reduced_by_error[error]['count']
          lowercase_			:       int									=			F'''| {count} | {error[:1_00]} |  |'''
          lines.append(__SCREAMING_SNAKE_CASE   )

     return "\n".join(__SCREAMING_SNAKE_CASE   )



def     lowercase__( __SCREAMING_SNAKE_CASE							:  int   ):
     lowercase_			:       Union[str, Any]									=			'| model | no. of errors | major error | count |'
     lowercase_			:       Any									=			'|-:|-:|-:|-:|'
     lowercase_			:       Union[str, Any]									=			[header, sep]
     for model in reduced_by_model:
          lowercase_			:       Optional[Any]									=			reduced_by_model[model]['count']
          lowercase_			:       int									=			list(reduced_by_model[model]['errors'].items()   )[0]
          lowercase_			:       List[Any]									=			F'''| {model} | {count} | {error[:60]} | {_count} |'''
          lines.append(__SCREAMING_SNAKE_CASE   )

     return "\n".join(__SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
       __SCREAMING_SNAKE_CASE 			=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.")
       __SCREAMING_SNAKE_CASE 			=parser.parse_args()

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

       __SCREAMING_SNAKE_CASE 			=get_job_links(args.workflow_run_id, token=args.token)
       __SCREAMING_SNAKE_CASE 			={}
       # 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:
                            __SCREAMING_SNAKE_CASE 			=k.find(" / ")
                            __SCREAMING_SNAKE_CASE 			=k[index + len(" / ") :]
                     __SCREAMING_SNAKE_CASE 			=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)

       __SCREAMING_SNAKE_CASE 			=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)

       __SCREAMING_SNAKE_CASE 			=get_all_errors(args.output_dir, job_links=job_links)

       # `e[1]` is the error
       __SCREAMING_SNAKE_CASE 			=Counter()
       counter.update([e[1] for e in errors])

       # print the top 30 most common test errors
       __SCREAMING_SNAKE_CASE 			=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)

       __SCREAMING_SNAKE_CASE 			=reduce_by_error(errors)
       __SCREAMING_SNAKE_CASE 			=reduce_by_model(errors)

       __SCREAMING_SNAKE_CASE 			=make_github_table(reduced_by_error)
       __SCREAMING_SNAKE_CASE 			=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)


"""simple docstring"""







import os
import unittest
from tempfile import TemporaryDirectory

import torch
import torch.nn as nn

from accelerate.utils import (
    OffloadedWeightsLoader,
    extract_submodules_state_dict,
    load_offloaded_weight,
    offload_state_dict,
    offload_weight,
)







class  UpperCamelCase	(    nn.Module						):
   def __init__(    self    )			->   Any:


        '''simple docstring'''


        super().__init__()
        lowercase_			:       Dict									=			nn.Linear(3  ,4    )
        lowercase_			:       Union[str, Any]									=			nn.BatchNormad(4    )
        lowercase_			:       Union[str, Any]									=			nn.Linear(4  ,5    )







   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   int:


        '''simple docstring'''


        return self.lineara(self.batchnorm(self.lineara(__UpperCamelCase    )    )    )







class  UpperCamelCase	(    unittest.TestCase						):
   def     _UpperCAmelCase     (    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       int									=			ModelForTest()
        with TemporaryDirectory() as tmp_dir:
             offload_state_dict(__UpperCamelCase  ,model.state_dict()    )
             lowercase_			:       str									=			os.path.join(__UpperCamelCase  ,'index.json'    )
             self.assertTrue(os.path.isfile(__UpperCamelCase    )    )
             # TODO: add tests on what is inside the index

             for key in ["linear1.weight", "linear1.bias", "linear2.weight", "linear2.bias"]:
                  lowercase_			:       int									=			os.path.join(__UpperCamelCase  ,f'''{key}.dat'''    )
                  self.assertTrue(os.path.isfile(__UpperCamelCase    )    )
                  # TODO: add tests on the fact weights are properly loaded
   def     _UpperCAmelCase     (    self    )			->   Tuple:


        '''simple docstring'''


        lowercase_			:       List[str]									=			[torch.floataa, torch.floataa, torch.bfloataa]

        for dtype in dtypes:
             lowercase_			:       Tuple									=			torch.randn(2  ,3  ,dtype=__UpperCamelCase    )
             with TemporaryDirectory() as tmp_dir:
                  lowercase_			:       List[str]									=			offload_weight(__UpperCamelCase  ,'weight'  ,__UpperCamelCase  ,{}    )
                  lowercase_			:       str									=			os.path.join(__UpperCamelCase  ,'weight.dat'    )
                  self.assertTrue(os.path.isfile(__UpperCamelCase    )    )
                  self.assertDictEqual(__UpperCamelCase  ,{'weight': {'shape': [2, 3], 'dtype': str(__UpperCamelCase    ).split('.'    )[1]}}    )

                  lowercase_			:       Optional[Any]									=			load_offloaded_weight(__UpperCamelCase  ,index['weight']    )
                  self.assertTrue(torch.equal(__UpperCamelCase  ,__UpperCamelCase    )    )
   def     _UpperCAmelCase     (    self    )			->   List[Any]:


        '''simple docstring'''


        lowercase_			:       List[str]									=			ModelForTest()
        lowercase_			:       Optional[int]									=			model.state_dict()
        lowercase_			:       int									=			{k: v for k, v in state_dict.items() if 'linear2' not in k}
        lowercase_			:       Optional[Any]									=			{k: v for k, v in state_dict.items() if 'linear2' in k}

        with TemporaryDirectory() as tmp_dir:
             offload_state_dict(__UpperCamelCase  ,__UpperCamelCase    )
             lowercase_			:       Tuple									=			OffloadedWeightsLoader(state_dict=__UpperCamelCase  ,save_folder=__UpperCamelCase    )

             # Every key is there with the right value
             self.assertEqual(sorted(__UpperCamelCase    )  ,sorted(state_dict.keys()    )    )
             for key, param in state_dict.items():
                  self.assertTrue(torch.allclose(__UpperCamelCase  ,weight_map[key]    )    )

        lowercase_			:       int									=			{k: v for k, v in state_dict.items() if 'weight' in k}
        lowercase_			:       int									=			{k: v for k, v in state_dict.items() if 'weight' not in k}

        with TemporaryDirectory() as tmp_dir:
             offload_state_dict(__UpperCamelCase  ,__UpperCamelCase    )
             lowercase_			:       int									=			OffloadedWeightsLoader(state_dict=__UpperCamelCase  ,save_folder=__UpperCamelCase    )

             # Every key is there with the right value
             self.assertEqual(sorted(__UpperCamelCase    )  ,sorted(state_dict.keys()    )    )
             for key, param in state_dict.items():
                  self.assertTrue(torch.allclose(__UpperCamelCase  ,weight_map[key]    )    )

        with TemporaryDirectory() as tmp_dir:
             offload_state_dict(__UpperCamelCase  ,__UpperCamelCase    )
             # Duplicates are removed
             lowercase_			:       Tuple									=			OffloadedWeightsLoader(state_dict=__UpperCamelCase  ,save_folder=__UpperCamelCase    )

             # Every key is there with the right value
             self.assertEqual(sorted(__UpperCamelCase    )  ,sorted(state_dict.keys()    )    )
             for key, param in state_dict.items():
                  self.assertTrue(torch.allclose(__UpperCamelCase  ,weight_map[key]    )    )







   def     _UpperCAmelCase     (    self    )			->   Union[str, Any]:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			{'a.1': 0, 'a.10': 1, 'a.2': 2}
        lowercase_			:       int									=			extract_submodules_state_dict(__UpperCamelCase  ,['a.1', 'a.2']    )
        self.assertDictEqual(__UpperCamelCase  ,{'a.1': 0, 'a.2': 2}    )

        lowercase_			:       Union[str, Any]									=			{'a.1.a': 0, 'a.10.a': 1, 'a.2.a': 2}
        lowercase_			:       Optional[int]									=			extract_submodules_state_dict(__UpperCamelCase  ,['a.1', 'a.2']    )
        self.assertDictEqual(__UpperCamelCase  ,{'a.1.a': 0, 'a.2.a': 2}    )

