




'''simple docstring'''

import os
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
		import torch

		from transformers import GPTaLMHeadModel





@require_torch
@require_sentencepiece
@require_tokenizers
class __magic_name__(						unittest.TestCase      ):






						@slow
						@unittest.skip("""Model is not available."""       )
						def       __lowerCAmelCase(   self						:						Union[str, Any]       ):



									'''simple docstring'''






									snake_case__          =						"""nvidia/megatron-gpt2-345m/"""
									if "MYDIR" in os.environ:
												snake_case__          =						os.path.join(os.environ["""MYDIR"""]					,   __UpperCamelCase       )
									snake_case__          =						GPTaLMHeadModel.from_pretrained(__UpperCamelCase       )
									model.to(__UpperCamelCase       )
									model.half()

									snake_case__          =						torch.tensor(
									    [[1_0_1, 7_1_1_0, 1_0_0_5, 1_0_5_6, 2_0_2_3, 1_1_3_3_3, 1_7_4_1_3, 1_0_2_9, 1_0_2]]					,   device=__UpperCamelCase					,   dtype=torch.long					,   )

									with torch.no_grad():
												snake_case__          =						model(__UpperCamelCase       ).logits

									snake_case__          =						torch.Size((1, 9, 5_0_2_5_7)       )
									self.assertEqual(output.shape					,   __UpperCamelCase       )

									snake_case__          =						torch.tensor(
									    [
									        4.94_14,
									        -0.29_20,
									        -1.21_48,
									        -4.02_73,
									        -0.51_61,
									        -5.21_09,
									        -1.24_12,
									        -1.83_01,
									        -1.77_34,
									        -4.71_48,
									        -0.23_17,
									        -1.08_11,
									        -2.17_77,
									        0.41_41,
									        -3.79_69,
									        -4.05_86,
									        -2.53_32,
									        -3.38_09,
									        4.38_67,
									    ]					,   device=__UpperCamelCase					,   dtype=torch.half					,   )

									for i in range(1_9       ):
												snake_case__    ,			snake_case__          =						8 * i // 1_7, 2_7_9_2 * i  # along the diagonal
												snake_case__    ,			snake_case__          =						output[0, r, c], expected_diag[i]
												snake_case__          =						f"""row={r} col={c} computed={computed} expected={expected}"""
												self.assertAlmostEqual(__UpperCamelCase					,   __UpperCamelCase					,   delta=1E-4					,   msg=__UpperCamelCase       )

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)

__snake_case					:							List[Any]           =							logging.getLogger()




def 		A						(  ):




			"""simple docstring"""


			UpperCAmelCase__		:Any 		=    argparse.ArgumentParser()
			parser.add_argument('-f'							)
			UpperCAmelCase__		:List[Any] 		=    parser.parse_args()
			return args.f




class 	UpperCamelCase__       (  UpperCAmelCase__):

						'''simple docstring'''



						def    A__       (  self	)  ->str:
									UpperCAmelCase__		:Optional[int] 		=    logging.StreamHandler(sys.stdout	)
									logger.addHandler(A	)

									UpperCAmelCase__		:List[str] 		=    self.get_auto_remove_tmp_dir()
									UpperCAmelCase__		:List[str] 		=    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	):
												UpperCAmelCase__		:Any 		=    run_glue_with_pabee.main()
												for value in result.values():
															self.assertGreaterEqual(A  , 0.75	)





