



import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


A__     				=	logging.get_logger(__name__)  # pylint: disable=invalid-name


A__     				=	"""lfs-multipart-upload"""





class  __lowerCAmelCase			(					lowerCamelCase__	):




				@staticmethod
				def 							snake_case       (							_snake_case		):



									"""simple docstring"""





									_lowerCAmelCase      =   parser.add_parser(
									    """lfs-enable-largefiles"""						,    help=(
									        """Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB."""
									    )						,    )
									enable_parser.add_argument("""path"""						,    type=_snake_case						,    help="""Local path to repository you want to configure."""		)
									enable_parser.set_defaults(func=lambda _snake_case		: LfsEnableCommand(_snake_case		)		)

									_lowerCAmelCase      =   parser.add_parser(
									    _snake_case						,    help=(
									        """Deprecated: use `huggingface-cli` instead. """
									        """Command will get called by git-lfs, do not call it directly."""
									    )						,    )
									upload_parser.set_defaults(func=lambda _snake_case		: LfsUploadCommand(_snake_case		)		)





class  __lowerCAmelCase			:




				def __init__(							self						,    _snake_case		):



									"""simple docstring"""





									_lowerCAmelCase      =   args




				def 							snake_case       (							self		):



									"""simple docstring"""





									warnings.warn(
									    """Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead."""		)
									_lowerCAmelCase      =   os.path.abspath(self.args.path		)
									if not os.path.isdir(_snake_case		):
														print("""This does not look like a valid git repo."""		)
														exit(1		)
									subprocess.run(
									    """git config lfs.customtransfer.multipart.path transformers-cli""".split()						,    check=_snake_case						,    cwd=_snake_case		)
									subprocess.run(
									    F'git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'.split()						,    check=_snake_case						,    cwd=_snake_case						,    )
									print("""Local repo set up for largefiles"""		)


def 		_UpperCAmelCase    (				snake_case      ):





					"""simple docstring"""

					_lowerCAmelCase      =   json.dumps(snake_case      ) + """\n"""
					sys.stdout.write(snake_case      )
					sys.stdout.flush()


def 		_UpperCAmelCase    (				):





					"""simple docstring"""

					_lowerCAmelCase      =   json.loads(sys.stdin.readline().strip()      )

					if "terminate" in (msg.get("""type"""      ), msg.get("""event"""      )):
										# terminate message received
										return None

					if msg.get("""event"""      ) not in ("download", "upload"):
										logger.critical("""Received unexpected message"""      )
										sys.exit(1      )

					return msg





class  __lowerCAmelCase			(					lowerCamelCase__	):




				def __init__(							self						,    _snake_case						,    _snake_case						,    _snake_case		):



									"""simple docstring"""





									_lowerCAmelCase      =   filepath
									_lowerCAmelCase      =   seek_from
									_lowerCAmelCase      =   read_limit
									_lowerCAmelCase      =   0




				def __enter__(							self		):



									"""simple docstring"""





									_lowerCAmelCase      =   open(self.filepath						,    """rb"""		)
									self.f.seek(self.seek_from		)
									return self




				def __len__(							self		):



									"""simple docstring"""





									_lowerCAmelCase      =   os.fstat(self.f.fileno()		).st_size
									return min(self.read_limit						,    total_length - self.seek_from		)




				def 							snake_case       (							self						,    _snake_case=-1		):



									"""simple docstring"""





									if self.n_seen >= self.read_limit:
														return b""
									_lowerCAmelCase      =   self.read_limit - self.n_seen
									_lowerCAmelCase      =   self.f.read(remaining_amount if n < 0 else min(_snake_case						,    _snake_case		)		)
									self.n_seen += len(_snake_case		)
									return data




				def __iter__(							self		):



									"""simple docstring"""





									yield self.read(n=4 * 1024 * 1024		)




				def __exit__(							self						,    *_snake_case		):



									"""simple docstring"""





									self.f.close()





class  __lowerCAmelCase			:




				def __init__(							self						,    _snake_case		):



									"""simple docstring"""





									_lowerCAmelCase      =   args




				def 							snake_case       (							self		):



									"""simple docstring"""





									_lowerCAmelCase      =   json.loads(sys.stdin.readline().strip()		)
									if not (init_msg.get("""event"""		) == "init" and init_msg.get("""operation"""		) == "upload"):
														write_msg({"""error""": {"""code""": 32, """message""": """Wrong lfs init operation"""}}		)
														sys.exit(1		)

									# The transfer process should use the information it needs from the
									# initiation structure, and also perform any one-off setup tasks it
									# needs to do. It should then respond on stdout with a simple empty
									# confirmation structure, as follows:
									write_msg({}		)

									# After the initiation exchange, git-lfs will send any number of
									# transfer requests to the stdin of the transfer process, in a serial sequence.
									while True:
														_lowerCAmelCase      =   read_msg()
														if msg is None:
																			# When all transfers have been processed, git-lfs will send
																			# a terminate event to the stdin of the transfer process.
																			# On receiving this message the transfer process should
																			# clean up and terminate. No response is expected.
																			sys.exit(0		)

														_lowerCAmelCase      =   msg["""oid"""]
														_lowerCAmelCase      =   msg["""path"""]
														_lowerCAmelCase      =   msg["""action"""]["""href"""]
														_lowerCAmelCase      =   msg["""action"""]["""header"""]
														_lowerCAmelCase      =   int(header.pop("""chunk_size"""		)		)
														_lowerCAmelCase      =   list(header.values()		)

														_lowerCAmelCase      =   []
														for i, presigned_url in enumerate(_snake_case		):
																			with FileSlice(_snake_case						,    seek_from=i * chunk_size						,    read_limit=_snake_case		) as data:
																								_lowerCAmelCase      =   requests.put(_snake_case						,    data=_snake_case		)
																								r.raise_for_status()
																								parts.append(
																								    {
																								        """etag""": r.headers.get("""etag"""		),
																								        """partNumber""": i + 1,
																								    }		)
																								# In order to support progress reporting while data is uploading / downloading,
																								# the transfer process should post messages to stdout
																								write_msg(
																								    {
																								        """event""": """progress""",
																								        """oid""": oid,
																								        """bytesSoFar""": (i + 1) * chunk_size,
																								        """bytesSinceLast""": chunk_size,
																								    }		)
																								# Not precise but that's ok.

														_lowerCAmelCase      =   requests.post(
														    _snake_case						,    json={
														        """oid""": oid,
														        """parts""": parts,
														    }						,    )
														r.raise_for_status()

														write_msg({"""event""": """complete""", """oid""": oid}		)








import os
import sys
from pathlib import Path

import torch

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, require_torch_multi_gpu
from utils import load_json


A__     				=	torch.cuda.is_available()
A__     				=	[""" Sam ate lunch today.""", """Sams lunch ingredients."""]
A__     				=	["""A very interesting story about what I ate for lunch.""", """Avocado, celery, turkey, coffee"""]
A__     				=	{
    """max_tokens_per_batch""": None,
    """supervise_forward""": True,
    """normalize_hidden""": True,
    """label_smoothing""": 0.2,
    """eval_max_gen_length""": None,
    """eval_beams""": 1,
    """val_metric""": """loss""",
    """save_top_k""": 1,
    """adafactor""": True,
    """early_stopping_patience""": 2,
    """logger_name""": """default""",
    """length_penalty""": 0.5,
    """cache_dir""": """""",
    """task""": """summarization""",
    """num_workers""": 2,
    """alpha_hid""": 0,
    """freeze_embeds""": True,
    """enc_only""": False,
    """tgt_suffix""": """""",
    """resume_from_checkpoint""": None,
    """sortish_sampler""": True,
    """student_decoder_layers""": 1,
    """val_check_interval""": 1.0,
    """output_dir""": """""",
    """fp16""": False,  # TODO(SS): set this to CUDA_AVAILABLE if ci installs apex or start using native amp
    """no_teacher""": False,
    """fp16_opt_level""": """O1""",
    """gpus""": 1 if CUDA_AVAILABLE else 0,
    """n_tpu_cores""": 0,
    """max_grad_norm""": 1.0,
    """do_train""": True,
    """do_predict""": True,
    """accumulate_grad_batches""": 1,
    """server_ip""": """""",
    """server_port""": """""",
    """seed""": 42,
    """model_name_or_path""": """sshleifer/bart-tiny-random""",
    """config_name""": """""",
    """tokenizer_name""": """facebook/bart-large""",
    """do_lower_case""": False,
    """learning_rate""": 0.3,
    """lr_scheduler""": """linear""",
    """weight_decay""": 0.0,
    """adam_epsilon""": 1e-0_8,
    """warmup_steps""": 0,
    """max_epochs""": 1,
    """train_batch_size""": 2,
    """eval_batch_size""": 2,
    """max_source_length""": 12,
    """max_target_length""": 12,
    """val_max_target_length""": 12,
    """test_max_target_length""": 12,
    """fast_dev_run""": False,
    """no_cache""": False,
    """n_train""": -1,
    """n_val""": -1,
    """n_test""": -1,
    """student_encoder_layers""": 1,
    """freeze_encoder""": False,
    """auto_scale_batch_size""": False,
    """overwrite_output_dir""": False,
    """student""": None,
}


def 		_UpperCAmelCase    (				snake_case     ,						snake_case      ):





					"""simple docstring"""

					_lowerCAmelCase      =   """\n""".join(snake_case      )
					Path(snake_case      ).open("""w"""      ).writelines(snake_case      )


def 		_UpperCAmelCase    (				snake_case      ):





					"""simple docstring"""

					for split in ["train", "val", "test"]:
										_dump_articles(os.path.join(snake_case     ,						F'{split}.source'      )     ,						snake_case      )
										_dump_articles(os.path.join(snake_case     ,						F'{split}.target'      )     ,						snake_case      )
					return tmp_dir





class  __lowerCAmelCase			(					lowerCamelCase__	):




				@classmethod
				def 							snake_case       (							cls		):



									"""simple docstring"""





									return cls




				@require_torch_multi_gpu
				def 							snake_case       (							self		):



									"""simple docstring"""





									_lowerCAmelCase      =   {
									    """no_teacher""": True,
									    """freeze_encoder""": True,
									    """gpus""": 2,
									    """overwrite_output_dir""": True,
									    """sortish_sampler""": True,
									}
									self._test_distiller_cli_fork(_snake_case						,    check_contents=_snake_case		)




				def 							snake_case       (							self						,    _snake_case						,    _snake_case=True		):



									"""simple docstring"""





									_lowerCAmelCase      =   {
									    """label_smoothing""": 0.0,
									    """early_stopping_patience""": -1,
									    """train_batch_size""": 1,
									    """eval_batch_size""": 2,
									    """max_epochs""": 2,
									    """alpha_mlm""": 0.2,
									    """alpha_ce""": 0.8,
									    """do_predict""": True,
									    """model_name_or_path""": """sshleifer/tinier_bart""",
									    """teacher""": CHEAP_ARGS["""model_name_or_path"""],
									    """val_check_interval""": 0.5,
									}
									default_updates.update(_snake_case		)
									_lowerCAmelCase      =   CHEAP_ARGS.copy()
									_lowerCAmelCase      =   make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()		)
									_lowerCAmelCase      =   self.get_auto_remove_tmp_dir()
									args_d.update(data_dir=_snake_case						,    output_dir=_snake_case						,    **_snake_case		)

									def convert(_snake_case						,    _snake_case		):
														if k in ["tgt_suffix", "server_ip", "server_port", "out", "n_tpu_cores"]:
																			return ""
														if v is False or v is None:
																			return ""
														if v is True:  # or len(str(v))==0:
																			return F'--{k}'
														return F'--{k}={v}'

									_lowerCAmelCase      =   [x for x in (convert(_snake_case						,    _snake_case		) for k, v in args_d.items()) if len(_snake_case		)]
									_lowerCAmelCase      =   [sys.executable, F'{self.test_file_dir}/distillation.py'] + cli_args
									execute_subprocess_async(_snake_case						,    env=self.get_env()		)

									_lowerCAmelCase      =   os.listdir(_snake_case		)
									_lowerCAmelCase      =   {os.path.basename(_snake_case		) for p in contents}
									_lowerCAmelCase      =   [p for p in contents if p.endswith("""ckpt"""		)]
									assert len(_snake_case		) > 0

									self.assertIn("""test_generations.txt"""						,    _snake_case		)
									self.assertIn("""test_results.txt"""						,    _snake_case		)

									# get the following from the module, (we don't have access to `model` here)
									_lowerCAmelCase      =   os.path.join(_snake_case						,    """metrics.json"""		)
									_lowerCAmelCase      =   """rouge2"""

									_lowerCAmelCase      =   load_json(_snake_case		)
									# {'test': [{'test_avg_loss': 10.63731575012207, 'test_avg_rouge1': 0.0, 'test_avg_rouge2': 0.0, 'test_avg_rougeL': 0.0, 'test_avg_gen_time': 0.1822289228439331, 'test_avg_gen_len': 142.0, 'step_count': 1}]}
									print(_snake_case		)
									_lowerCAmelCase      =   metrics["""val"""][-1]
									self.assertGreaterEqual(last_step_stats["""val_avg_gen_time"""]						,    0.01		)
									self.assertIsInstance(last_step_stats[F'val_avg_{val_metric}']						,    _snake_case		)
									self.assertEqual(len(metrics["""test"""]		)						,    1		)
									_lowerCAmelCase      =   int(args_d["""max_epochs"""] * (1 / args_d["""val_check_interval"""]) / 2 + 1		)
									self.assertEqual(len(metrics["""val"""]		)						,    _snake_case		)



