
'''simple docstring'''


import os
import shutil
import unittest
from unittest.mock import patch

from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch

class 		__lowercase			(					unittest.TestCase      ):

			@patch('''sys.argv'''     ,				['''fakeprogrampath''', '''env'''] )
			def     UpperCAmelCase__	(self ):
								# test transformers-cli env
								import transformers.commands.transformers_cli

								with CaptureStd() as cs:
													transformers.commands.transformers_cli.main()
								self.assertIn('''Python version'''     ,				cs.out )
								self.assertIn('''Platform'''     ,				cs.out )
								self.assertIn('''Using distributed or parallel set-up in script?'''     ,				cs.out )

			@is_pt_tf_cross_test
			@patch(
			    '''sys.argv'''     ,				['''fakeprogrampath''', '''pt-to-tf''', '''--model-name''', '''hf-internal-testing/tiny-random-gptj''', '''--no-pr'''] )
			def     UpperCAmelCase__	(self ):
								import transformers.commands.transformers_cli

								shutil.rmtree('''/tmp/hf-internal-testing/tiny-random-gptj'''     ,				ignore_errors=A )  # cleans potential past runs
								transformers.commands.transformers_cli.main()

								# The original repo has no TF weights -- if they exist, they were created by the CLI
								self.assertTrue(os.path.exists('''/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5''' ) )

			@require_torch
			@patch('''sys.argv'''     ,				['''fakeprogrampath''', '''download''', '''hf-internal-testing/tiny-random-gptj''', '''--cache-dir''', '''/tmp'''] )
			def     UpperCAmelCase__	(self ):
								import transformers.commands.transformers_cli

								# # remove any previously downloaded model to start clean
								shutil.rmtree('''/tmp/models--hf-internal-testing--tiny-random-gptj'''     ,				ignore_errors=A )

								# run the command
								transformers.commands.transformers_cli.main()

								# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
								self.assertTrue(os.path.exists('''/tmp/models--hf-internal-testing--tiny-random-gptj/blobs''' ) )
								self.assertTrue(os.path.exists('''/tmp/models--hf-internal-testing--tiny-random-gptj/refs''' ) )
								self.assertTrue(os.path.exists('''/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots''' ) )






			@require_torch
			@patch(
			    '''sys.argv'''     ,				[
			        '''fakeprogrampath''',
			        '''download''',
			        '''hf-internal-testing/test_dynamic_model_with_tokenizer''',
			        '''--trust-remote-code''',
			        '''--cache-dir''',
			        '''/tmp''',
			    ]     ,				)
			def     UpperCAmelCase__	(self ):
								import transformers.commands.transformers_cli

								# # remove any previously downloaded model to start clean
								shutil.rmtree('''/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer'''     ,				ignore_errors=A )

								# run the command
								transformers.commands.transformers_cli.main()

								# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
								self.assertTrue(os.path.exists('''/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs''' ) )
								self.assertTrue(os.path.exists('''/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs''' ) )
								self.assertTrue(
								    os.path.exists('''/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots''' ) )




'''simple docstring'''


import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__lowercase							:				Optional[Any]					=       logging.getLogger()




def lowercase_		(				)       ->							Union[str, Any]:
					'''simple docstring'''

					lowerCamelCase_   : Any       =						argparse.ArgumentParser()
					parser.add_argument('''-f'''			)
					lowerCamelCase_   : Optional[int]       =						parser.parse_args()
					return args.f






class 		__lowercase			(					_lowercase      ):

			def     UpperCAmelCase__	(self ):
								lowerCamelCase_   : Dict       =						logging.StreamHandler(sys.stdout )
								logger.addHandler(A )

								lowerCamelCase_   : int       =						self.get_auto_remove_tmp_dir()
								lowerCamelCase_   : Dict       =						F"""
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

								with patch.object(A     ,				'''argv'''     ,				A ):
													lowerCamelCase_   : Optional[Any]       =						run_glue_with_pabee.main()
													for value in result.values():
																		self.assertGreaterEqual(A     ,				0.75 )


