






"""simple docstring"""
import os
import sys
import unittest


lowerCamelCase_       			=   os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


lowerCamelCase_       			=   os.path.join('''tests''', '''models''', '''bert''', '''test_modeling_bert.py''')
lowerCamelCase_       			=   os.path.join('''tests''', '''models''', '''blip''', '''test_modeling_blip.py''')







class     UpperCamelCase_ (unittest.TestCase  ):





	def   _SCREAMING_SNAKE_CASE   (   self      :				List[str]		)		->    Any:
				UpperCAmelCase_  :				Optional[Any]      =      get_test_to_tester_mapping(lowerCAmelCase_		)
				UpperCAmelCase_  :				Optional[Any]      =      get_test_to_tester_mapping(lowerCAmelCase_		)

				UpperCAmelCase_  :				Optional[int]      =      {"""BertModelTest""": """BertModelTester"""}

				UpperCAmelCase_  :				Tuple      =      {
				    """BlipModelTest""": """BlipModelTester""",
				    """BlipTextImageModelTest""": """BlipTextImageModelsModelTester""",
				    """BlipTextModelTest""": """BlipTextModelTester""",
				    """BlipTextRetrievalModelTest""": """BlipTextRetrievalModelTester""",
				    """BlipVQAModelTest""": """BlipVQAModelTester""",
				    """BlipVisionModelTest""": """BlipVisionModelTester""",
				}

				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)
				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Tuple		)		->    List[Any]:
				UpperCAmelCase_  :				List[str]      =      get_model_to_test_mapping(lowerCAmelCase_		)
				UpperCAmelCase_  :				Optional[Any]      =      get_model_to_test_mapping(lowerCAmelCase_		)

				UpperCAmelCase_  :				Any      =      {
				    """BertForMaskedLM""": ["""BertModelTest"""],
				    """BertForMultipleChoice""": ["""BertModelTest"""],
				    """BertForNextSentencePrediction""": ["""BertModelTest"""],
				    """BertForPreTraining""": ["""BertModelTest"""],
				    """BertForQuestionAnswering""": ["""BertModelTest"""],
				    """BertForSequenceClassification""": ["""BertModelTest"""],
				    """BertForTokenClassification""": ["""BertModelTest"""],
				    """BertLMHeadModel""": ["""BertModelTest"""],
				    """BertModel""": ["""BertModelTest"""],
				}

				UpperCAmelCase_  :				Tuple      =      {
				    """BlipForConditionalGeneration""": ["""BlipTextImageModelTest"""],
				    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTest"""],
				    """BlipForQuestionAnswering""": ["""BlipVQAModelTest"""],
				    """BlipModel""": ["""BlipModelTest"""],
				    """BlipTextModel""": ["""BlipTextModelTest"""],
				    """BlipVisionModel""": ["""BlipVisionModelTest"""],
				}

				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)
				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				str		)		->    str:
				UpperCAmelCase_  :				Any      =      get_model_to_tester_mapping(lowerCAmelCase_		)
				UpperCAmelCase_  :				int      =      get_model_to_tester_mapping(lowerCAmelCase_		)

				UpperCAmelCase_  :				Union[str, Any]      =      {
				    """BertForMaskedLM""": ["""BertModelTester"""],
				    """BertForMultipleChoice""": ["""BertModelTester"""],
				    """BertForNextSentencePrediction""": ["""BertModelTester"""],
				    """BertForPreTraining""": ["""BertModelTester"""],
				    """BertForQuestionAnswering""": ["""BertModelTester"""],
				    """BertForSequenceClassification""": ["""BertModelTester"""],
				    """BertForTokenClassification""": ["""BertModelTester"""],
				    """BertLMHeadModel""": ["""BertModelTester"""],
				    """BertModel""": ["""BertModelTester"""],
				}

				UpperCAmelCase_  :				Any      =      {
				    """BlipForConditionalGeneration""": ["""BlipTextImageModelsModelTester"""],
				    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTester"""],
				    """BlipForQuestionAnswering""": ["""BlipVQAModelTester"""],
				    """BlipModel""": ["""BlipModelTester"""],
				    """BlipTextModel""": ["""BlipTextModelTester"""],
				    """BlipVisionModel""": ["""BlipVisionModelTester"""],
				}

				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)
				self.assertEqual(get_test_info.to_json(lowerCAmelCase_		)			,			lowerCAmelCase_		)











"""simple docstring"""
import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
			# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
			# setup instructions, if using on-demand hardware

			# If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
			# If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
			# Throw an error if user passes both BYO and on-demand cluster args
			# Otherwise, use default values
			lowerCamelCase_       			=   argparse.ArgumentParser()
			parser.add_argument('''--user''', type=str, default='''ubuntu''')
			parser.add_argument('''--host''', type=str, default='''localhost''')
			parser.add_argument('''--key_path''', type=str, default=None)
			parser.add_argument('''--instance''', type=str, default='''V100:1''')
			parser.add_argument('''--provider''', type=str, default='''cheapest''')
			parser.add_argument('''--use_spot''', type=bool, default=False)
			parser.add_argument('''--example''', type=str, default='''pytorch/text-generation/run_generation.py''')
			lowerCamelCase_			,	lowerCamelCase_       			=   parser.parse_known_args()
			if args.host != "localhost":
						if args.instance != "V100:1" or args.provider != "cheapest":
									raise ValueError('''Cannot specify both BYO and on-demand cluster args''')
						lowerCamelCase_       			=   rh.cluster(
						    name='''rh-cluster''', ips=[args.host], ssh_creds={'''ssh_user''': args.user, '''ssh_private_key''': args.key_path}
						)
			else:
						lowerCamelCase_       			=   rh.cluster(
						    name='''rh-cluster''', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
						)
			lowerCamelCase_       			=   args.example.rsplit('''/''', 1)[0]

			# Set up remote environment
			cluster.install_packages(['''pip:./'''])  # Installs transformers from local source
			# Note transformers is copied into the home directory on the remote machine, so we can install from there
			cluster.run([f'pip install -r transformers/examples/{example_dir}/requirements.txt'])
			cluster.run(['''pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117'''])

			# Run example. You can bypass the CLI wrapper and paste your own code here.
			cluster.run([f'python transformers/examples/{args.example} {" ".join(shlex.quote(arg) for arg in unknown)}'])

			# Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
			# from my_script... import train
			# reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
			# launch_train_gpu = rh.function(fn=train,
			#                                system=gpu,
			#                                reqs=reqs,
			#                                name='train_bert_glue')
			#
			# We can pass in arguments just like we would to a function:
			# launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
			#                  stream_logs=True)



