






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

import requests







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					Optional[int]=None		)  ->   Tuple:

						"""simple docstring"""



						lowerCAmelCase__    						=						None
						if token is not None:
												lowerCAmelCase__    						=						{'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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

						try:
												job_links.update({job['name']: job['html_url'] for job in result['jobs']}		)
												lowerCAmelCase__    						=						math.ceil((result['total_count'] - 100) / 100		)

												for i in range(UpperCamelCase_		):
																		lowerCAmelCase__    						=						requests.get(url + F"&page={i + 2}"    ,       headers=UpperCamelCase_		).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 	_UpperCamelCase   (    UpperCamelCase_       :					Tuple    ,       UpperCamelCase_       :					List[Any]=None		)  ->   Optional[Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						None
						if token is not None:
												lowerCAmelCase__    						=						{'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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

						try:
												artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}		)
												lowerCAmelCase__    						=						math.ceil((result['total_count'] - 100) / 100		)

												for i in range(UpperCamelCase_		):
																		lowerCAmelCase__    						=						requests.get(url + F"&page={i + 2}"    ,       headers=UpperCamelCase_		).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 	_UpperCamelCase   (    UpperCamelCase_       :					Dict    ,       UpperCamelCase_       :					Any    ,       UpperCamelCase_       :					Tuple    ,       UpperCamelCase_       :					List[Any]		)  ->   Tuple:

						"""simple docstring"""



						lowerCAmelCase__    						=						None
						if token is not None:
												lowerCAmelCase__    						=						{'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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







def 	_UpperCamelCase   (    UpperCamelCase_       :					Dict    ,       UpperCamelCase_       :					Optional[int]=None		)  ->   int:

						"""simple docstring"""



						lowerCAmelCase__    						=						[]
						lowerCAmelCase__    						=						[]
						lowerCAmelCase__    						=						None

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

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

						lowerCAmelCase__    						=						None
						if job_name and job_links:
												lowerCAmelCase__    						=						job_links.get(UpperCamelCase_    ,       UpperCamelCase_		)

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

						return result







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[Any]    ,       UpperCamelCase_       :					Optional[Any]=None		)  ->   Any:

						"""simple docstring"""



						lowerCAmelCase__    						=						[]

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

						return errors







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[str]    ,       UpperCamelCase_       :					List[str]=None		)  ->   int:

						"""simple docstring"""



						lowerCAmelCase__    						=						Counter()
						counter.update([x[1] for x in logs]		)
						lowerCAmelCase__    						=						counter.most_common()
						lowerCAmelCase__    						=						{}
						for error, count in counts:
												if error_filter is None or error not in error_filter:
																		lowerCAmelCase__    						=						{'count': count, 'failed_tests': [(x[2], x[0]) for x in logs if x[1] == error]}

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







def 	_UpperCamelCase   (    UpperCamelCase_       :					Any		)  ->   List[str]:

						"""simple docstring"""



						lowerCAmelCase__    						=						test.split('::'		)[0]
						if test.startswith('tests/models/'		):
												lowerCAmelCase__    						=						test.split('/'		)[2]
						else:
												lowerCAmelCase__    						=						None

						return test







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					int=None		)  ->   Optional[int]:

						"""simple docstring"""



						lowerCAmelCase__    						=						[(x[0], x[1], get_model(x[2]		)) for x in logs]
						lowerCAmelCase__    						=						[x for x in logs if x[2] is not None]
						lowerCAmelCase__    						=						{x[2] for x in logs}

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

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







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[int]		)  ->   Any:

						"""simple docstring"""



						lowerCAmelCase__    						=						'| no. | error | status |'
						lowerCAmelCase__    						=						'|-:|:-|:-|'
						lowerCAmelCase__    						=						[header, sep]
						for error in reduced_by_error:
												lowerCAmelCase__    						=						reduced_by_error[error]['count']
												lowerCAmelCase__    						=						F"| {count} | {error[:100]} |  |"
												lines.append(UpperCamelCase_		)

						return "\n".join(UpperCamelCase_		)







def 	_UpperCamelCase   (    UpperCamelCase_       :					Dict		)  ->   Union[str, Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						'| model | no. of errors | major error | count |'
						lowerCAmelCase__    						=						'|-:|-:|-:|-:|'
						lowerCAmelCase__    						=						[header, sep]
						for model in reduced_by_model:
												lowerCAmelCase__    						=						reduced_by_model[model]['count']
												lowerCAmelCase__						,       lowerCAmelCase__    						=						list(reduced_by_model[model]['errors'].items()		)[0]
												lowerCAmelCase__    						=						F"| {model} | {count} | {error[:60]} | {_count} |"
												lines.append(UpperCamelCase_		)

						return "\n".join(UpperCamelCase_		)


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    :    List[str]         =     parser.parse_args()

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

					__snake_case    :    Any         =     get_job_links(args.workflow_run_id, token=args.token)
					__snake_case    :    Tuple         =     {}
					# 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    :    Tuple         =     k.find(""" / """)
																				__snake_case    :    Any         =     k[index + len(""" / """) :]
															__snake_case    :    List[Any]         =     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    :    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    :    Union[str, Any]         =     get_all_errors(args.output_dir, job_links=job_links)

					# `e[1]` is the error
					__snake_case    :    Optional[int]         =     Counter()
					counter.update([e[1] for e in errors])

					# print the top 30 most common test errors
					__snake_case    :    Optional[int]         =     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[str]         =     reduce_by_error(errors)
					__snake_case    :    Optional[Any]         =     reduce_by_model(errors)

					__snake_case    :    Any         =     make_github_table(reduced_by_error)
					__snake_case    :    List[Any]         =     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)













# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# full vocab, merges file, and thus also resulting in a larger model due to a large vocab size.
# This gives ~3MB in total for all files.
#
# If you want a 50 times smaller than this see `fsmt-make-super-tiny-model.py`, which is slightly more complicated
#
#
# It will be used then as "stas/tiny-wmt19-en-de"

# Build
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration

__snake_case    :    Optional[int]         =     """facebook/wmt19-en-de"""
__snake_case    :    Optional[Any]         =     FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master model
__snake_case    :    List[str]         =     FSMTConfig.from_pretrained(mname)
config.update(
    dict(
        d_model=4,
        encoder_layers=1,
        decoder_layers=1,
        encoder_ffn_dim=4,
        decoder_ffn_dim=4,
        encoder_attention_heads=1,
        decoder_attention_heads=1,
    )
)

__snake_case    :    Optional[Any]         =     FSMTForConditionalGeneration(config)
print(f'num of params {tiny_model.num_parameters()}')

# Test
__snake_case    :    List[Any]         =     tokenizer(["""Making tiny model"""], return_tensors="""pt""")
__snake_case    :    Any         =     tiny_model(**batch)

print("""test output:""", len(outputs.logits[0]))

# Save
__snake_case    :    Any         =     """tiny-wmt19-en-de"""
tiny_model.half()  # makes it smaller
tiny_model.save_pretrained(mname_tiny)
tokenizer.save_pretrained(mname_tiny)

print(f'Generated {mname_tiny}')

# Upload
# transformers-cli upload tiny-wmt19-en-de





