


import itertools
import os
import subprocess
from os.path import dirname

from parameterized import parameterized

from tests.trainer.test_trainer import TrainerIntegrationCommon  # noqa
from transformers import is_torch_available
from transformers.testing_utils import (
    TestCasePlus,
    execute_subprocess_async,
    get_gpu_count,
    get_tests_dir,
    require_deepspeed,
    require_torch_gpu,
    slow,
)
from transformers.trainer_utils import set_seed


if is_torch_available():
  from tests.trainer.test_trainer import (  # noqa
      RegressionModelConfig,
      RegressionPreTrainedModel,
      get_regression_trainer,
  )


set_seed(42)

UpperCAmelCase__        =				get_tests_dir('''fixtures''')
UpperCAmelCase__        =				os.path.join(dirname(get_tests_dir()))
UpperCAmelCase__        =				dirname(os.path.abspath(__file__))

# default torch.distributed port
UpperCAmelCase__        =				'''10999'''

UpperCAmelCase__        =				'''t5-small'''

# *** Working Models ***
UpperCAmelCase__        =				'''hf-internal-testing/tiny-albert'''
UpperCAmelCase__        =				'''sshleifer/bart-tiny-random'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-bert'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-bigbird_pegasus'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-big_bird'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-blenderbot'''
UpperCAmelCase__        =				'''bigscience/bigscience-small-testing'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-deberta'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-deberta-v2'''
UpperCAmelCase__        =				'''sshleifer/tiny-distilbert-base-cased'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-electra'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-flaubert'''
UpperCAmelCase__        =				'''stas/tiny-wmt19-en-de'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-funnel'''
UpperCAmelCase__        =				'''sshleifer/tiny-gpt2'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-gptj'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-gpt_neo'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-layoutlm'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-led'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-longformer'''
UpperCAmelCase__        =				'''stas/tiny-m2m_100'''  # hf tiny model is unsuitable
UpperCAmelCase__        =				'''sshleifer/tiny-marian-en-de'''
UpperCAmelCase__        =				'''sshleifer/tiny-mbart'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-mobilebert'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-mpnet'''
UpperCAmelCase__        =				'''stas/pegasus-cnn_dailymail-tiny-random'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-prophetnet'''
UpperCAmelCase__        =				'''sshleifer/tiny-distilroberta-base'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-squeezebert'''
UpperCAmelCase__        =				'''patrickvonplaten/t5-tiny-random'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-t5-v1.1'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-vit'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-xlm-roberta'''
UpperCAmelCase__        =				'''sshleifer/tiny-xlnet-base-cased'''


# *** To Fix ***


# *** tiny model issues ***
# missing model files:
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-mt5'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-camembert'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-openai-gpt'''

# missing tokenizer files
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-convbert'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-layoutlmv2'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-hubert'''

# issues with tokenizer
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-ctrl'''
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-transfo-xl'''  # same as ctrl

# other issues with tiny models
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-ibert'''  # multiple issues with either mlm/qa/clas
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-reformer'''  # multiple issues with either mlm/qa/clas

# *** Lacking official examples to test with ***
# or not working with examples
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-dpr'''
# - "dpr"  examples/research_projects/rag-end2end-retriever/
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-rag'''
# - "rag" research_projects
UpperCAmelCase__        =				''''''
# - "luke" Entities classes - no plan to make such example
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-lxmert'''
# - "lxmert" doesn't work with run_qa.py
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-clip'''
# - "clip" nothing under pytorch examples - XXX: Suraj is working on adding some - check by end of Sep
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-speech_to_text'''
# - "speech_to_text", nothing under pytorch examples


# *** Reactive mode ***
# models with low usage, unstable API, things about to change - do nothing about the following until someone runs into a problem
UpperCAmelCase__        =				'''hf-internal-testing/tiny-random-tapas'''
def 							UpperCAmelCase_   (				__snake_case=False		)	->     Dict:







 """simple docstring"""


 _lowercase				 =min(2	,		get_gpu_count()		) if distributed else 1
 _lowercase				 =os.environ.get('''DS_TEST_PORT'''	,		lowercase_		)
 return F"deepspeed --num_nodes 1 --num_gpus {num_gpus} --master_port {master_port}".split()
def 							UpperCAmelCase_   (				)	->     Union[str, Any]:







 """simple docstring"""


 _lowercase				 =F"{FIXTURE_DIRECTORY}/tests_samples"
 _lowercase				 =F"{data_dir_samples}/wmt_en_ro"
 _lowercase				 =F"{data_dir_samples}/xsum"
 _lowercase				 ='''
        --do_train
        --max_train_samples 4
        --per_device_train_batch_size 2
        --num_train_epochs 1
        --fp16
        --report_to none
        --overwrite_output_dir
        '''.split()

 # try to cover as many models as possible once (it's enough to run on one task per model)
 # but need a tiny model for each
 #
 # should have "{model_type.upper()}_TINY" corresponding vars defined, e.g., T5_TINY, etc.
 _lowercase				 ={
     '''trans''': [
         '''bart''',
         '''fsmt''',
         '''m2m_100''',
         '''marian''',
         '''mbart''',
         '''t5''',
         '''t5_v1''',
         # "mt5", missing model files
     ],
     '''sum''': [
         '''pegasus''',
     ],
     '''clm''': [
         '''big_bird''',
         '''bigbird_pegasus''',
         '''blenderbot''',
         '''bloom''',
         '''gpt2''',
         '''gpt_neo''',
         '''gptj''',
         '''xlm-roberta''',
         '''prophetnet''',
         # "camembert", missing model files
     ],
     '''mlm''': [
         '''albert''',
         '''deberta''',
         '''deberta-v2''',
         '''distilbert''',
         '''electra''',
         '''flaubert''',
         '''funnel''',
         '''layoutlm''',
         # "reformer", # multiple issues with either mlm/qa/clas
     ],
     '''qa''': [
         '''led''',
         '''longformer''',
         '''mobilebert''',
         '''mpnet''',
         '''roberta''',
         '''squeezebert''',
         # "convbert", # missing tokenizer files
         # "layoutlmv2", missing model files
     ],
     '''clas''': [
         '''bert''',
         '''xlnet''',
         # "hubert", # missing tokenizer files
         # "ibert", # multiple issues with either mlm/qa/clas
         # "transfo-xl", # tokenizer issues as ctrl
         # "ctrl", # tokenizer issues
         # "openai-gpt", missing model files
         # "tapas", multiple issues
     ],
     '''img_clas''': [
         '''vit''',
     ],
 }

 _lowercase				 =F"{ROOT_DIRECTORY}/examples/pytorch"

 _lowercase				 ={
     '''trans''': F"\n        {scripts_dir}/translation/run_translation.py\n        --train_file {data_dir_wmt}/train.json\n        --source_lang en\n        --target_lang ro\n        ",
     '''sum''': F"\n        {scripts_dir}/summarization/run_summarization.py\n        --train_file {data_dir_xsum}/sample.json\n        --max_source_length 12\n        --max_target_length 12\n        --lang en\n        ",
     '''clm''': F"\n        {scripts_dir}/language-modeling/run_clm.py\n        --train_file {FIXTURE_DIRECTORY}/sample_text.txt\n        --block_size 8\n        ",
     '''mlm''': F"\n        {scripts_dir}/language-modeling/run_mlm.py\n        --train_file {FIXTURE_DIRECTORY}/sample_text.txt\n        ",
     '''qa''': F"\n        {scripts_dir}/question-answering/run_qa.py\n        --train_file {data_dir_samples}/SQUAD/sample.json\n        ",
     '''clas''': F"\n        {scripts_dir}/text-classification/run_glue.py\n        --train_file {data_dir_samples}/MRPC/train.csv\n        --max_seq_length 12\n        --task_name MRPC\n        ",
     '''img_clas''': F"\n        {scripts_dir}/image-classification/run_image_classification.py\n            --dataset_name hf-internal-testing/cats_vs_dogs_sample\n            --remove_unused_columns False\n            --max_steps 10\n            --image_processor_name {DS_TESTS_DIRECTORY}/vit_feature_extractor.json\n        ",
 }

 _lowercase				 =get_launcher(distributed=lowercase_		)

 _lowercase				 ={}
 for task, args in tasks.items():
  _lowercase				 =args.split()
  for model in tasksamodels[task]:
   _lowercase				 =globals()[F"{model.upper().replace('-'	,		'_'		)}_TINY"]
   _lowercase				 =F"--model_name_or_path {model_name}".split()
   _lowercase				 =launcher + args + args_model + args_main

   # # generation special case
   # if task == "gen":
   #     launcher = f"deepspeed --num_nodes 1 --num_gpus 1".split()
   #     args_model += f"--model_type {model}".split()
   #     cmds[f"{task}_{model}"] = launcher + args + args_model
   # else:

 return cmds


UpperCAmelCase__        =				make_task_cmds()

UpperCAmelCase__        =				'''zero2'''
UpperCAmelCase__        =				'''zero3'''

UpperCAmelCase__        =				[ZEROa, ZEROa]
def 							UpperCAmelCase_   (				__snake_case	,		__snake_case	,		__snake_case		)	->     Union[str, Any]:







 """simple docstring"""


 _lowercase				 =parameterized.to_safe_name('''_'''.join(str(lowercase_		) for x in param.args		)		)
 return F"{func.__name__}_{param_based_name}"


# Cartesian-product of zero stages with models to test
UpperCAmelCase__        =				list(itertools.product(stages, task_cmds.keys()))







@slow
@require_deepspeed
@require_torch_gpu
class  lowerCamelCase__  (			__snake_case):





     def 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase			)	->  Tuple:
      # return a ready to run train cmd
      if task not in task_cmds:
       raise ValueError(f"don\'t know of task {task}, have {task_cmds.keys()}"			)

      _lowercase				 =task_cmds[task]
      _lowercase				 =f"--deepspeed {self.test_file_dir_str}/ds_config_{stage}.json".split()

      _lowercase				 =self.get_auto_remove_tmp_dir()
      _lowercase				 =f"--output_dir {output_dir}".split()

      cmd += args_ds + args_out

      return cmd, output_dir





     @parameterized.expand(UpperCAmelCase						,	name_func=UpperCAmelCase			)
     def 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase			)	->  List[str]:
      # testing the ability to do a run followed by recovery of full fp32 weights

      _lowercase ,       _lowercase				 =self.get_task_cmd(UpperCAmelCase						,	UpperCAmelCase			)

      # 1. generate the checkpoint
      cmd += "--save_steps 1".split()
      # keep for quick debug
      # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] + cmd)); die
      execute_subprocess_async(UpperCAmelCase						,	env=self.get_env()			)

      # 2. test that the fp32 weights get reconsolidated
      _lowercase				 =f"{output_dir}/checkpoint-1"
      _lowercase				 =f"{chkpt_dir}/out.bin"
      _lowercase				 =f"{chkpt_dir}/zero_to_fp32.py {chkpt_dir} {recovered_model_path}"
      # keep for quick debug
      # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
      subprocess.check_call(UpperCAmelCase						,	shell=UpperCAmelCase			)
      assert os.path.exists(UpperCAmelCase			), f"{recovered_model_path} was not found"

      # possibly could also test that the resulting saved model is usable but given that we use
      # random models we won't know if it's any good




from math import pi



def   UpperCamelCase(   lowercase_				)      ->							float:





  '''simple docstring'''





  return degree / (180 / pi)


if __name__ == "__main__":
    from doctest import testmod

    testmod()