





import builtins
import sys

from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP


a__:      Union[str, Any]									=		False
try:
       a__:      List[Any]									=		_is_package_available('google.colab')
except ModuleNotFoundError:
       pass




@input.register
class     SCREAMING_SNAKE_CASE__ :



 def __init__(							self,__lowerCamelCase = None,__lowerCamelCase = [] ):
        A__											=						0
        A__											=						choices
        A__											=						prompt
        if sys.platform == "win32":
               A__											=						'''*'''
        else:
               A__											=						'''➔ '''



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = "" ):
        if sys.platform != "win32":
               writeColor(self.choices[index],32,__lowerCamelCase )
        else:
               forceWrite(self.choices[index],__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        if index == self.position:
               forceWrite(f" {self.arrow_char} " )
               self.write_choice(__lowerCamelCase )
        else:
               forceWrite(f"    {self.choices[index]}" )
        reset_cursor()



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = 1 ):
        A__											=						self.position
        if direction == Direction.DOWN:
               if self.position + 1 >= len(self.choices ):
                      return
               self.position += num_spaces
        else:
               if self.position - 1 < 0:
                      return
               self.position -= num_spaces
        clear_line()
        self.print_choice(__lowerCamelCase )
        move_cursor(__lowerCamelCase,direction.name )
        self.print_choice(self.position )



 @input.mark(KEYMAP['''up'''] )
 def 				UpperCamelCase			(							self ):
        self.move_direction(Direction.UP )



 @input.mark(KEYMAP['''down'''] )
 def 				UpperCamelCase			(							self ):
        self.move_direction(Direction.DOWN )



 @input.mark(KEYMAP['''newline'''] )
 def 				UpperCamelCase			(							self ):
        move_cursor(len(self.choices ) - self.position,'''DOWN''' )
        return self.position



 @input.mark(KEYMAP['''interrupt'''] )
 def 				UpperCamelCase			(							self ):
        move_cursor(len(self.choices ) - self.position,'''DOWN''' )
        raise KeyboardInterrupt



 @input.mark_multiple(*[KEYMAP[str(__lowerCamelCase )] for number in range(10 )] )
 def 				UpperCamelCase			(							self ):
        A__											=						int(chr(self.current_selection ) )
        A__											=						index - self.position
        if index == self.position:
               return
        if index < len(self.choices ):
               if self.position > index:
                      self.move_direction(Direction.UP,-movement )
               elif self.position < index:
                      self.move_direction(Direction.DOWN,__lowerCamelCase )
               else:
                      return
        else:
               return




 def 				UpperCamelCase			(							self,__lowerCamelCase = 0 ):
        if self.prompt:
               linebreak()
               forceWrite(self.prompt,'''\n''' )
               if in_colab:
                      forceWrite('''Please input a choice index (starting from 0), and press enter''','''\n''' )
               else:
                      forceWrite('''Please select a choice using the arrow or number keys, and selecting with enter''','''\n''' )
        A__											=						default_choice
        for i in range(len(self.choices ) ):
               self.print_choice(__lowerCamelCase )
               forceWrite('''\n''' )
        move_cursor(len(self.choices ) - self.position,'''UP''' )
        with cursor.hide():
               while True:
                      if in_colab:
                             try:
                                    A__											=						int(builtins.input() )
                             except ValueError:
                                    A__											=						default_choice
                      else:
                             A__											=						self.handle_input()
                      if choice is not None:
                             reset_cursor()
                             for _ in range(len(self.choices ) + 1 ):
                                    move_cursor(1,'''UP''' )
                                    clear_line()
                             self.write_choice(__lowerCamelCase,'''\n''' )
                             return choice












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

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

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


def 	UpperCamelCase__(       )->Union[str, Any]:
       A__											=						argparse.ArgumentParser()
       parser.add_argument('''-f'''  )
       A__											=						parser.parse_args()
       return args.f




class     SCREAMING_SNAKE_CASE__ (						UpperCamelCase__      ):



 def 				UpperCamelCase			(							self ):
        A__											=						logging.StreamHandler(sys.stdout )
        logger.addHandler(__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						get_gpu_count()

        if n_gpu > 1:
               pass
               # XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
               # script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
               # distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
               # cmd = [sys.executable] + distributed_args + args
               # execute_subprocess_async(cmd, env=self.get_env())
               # XXX: test the results - need to save them first into .json file
        else:
               args.insert(0,'''run_glue_deebert.py''' )
               with patch.object(__lowerCamelCase,'''argv''',__lowerCamelCase ):
                      A__											=						run_glue_deebert.main()
                      for value in result.values():
                             self.assertGreaterEqual(__lowerCamelCase,0.666 )




 @slow
 @require_torch_non_multi_gpu
 def 				UpperCamelCase			(							self ):
        A__											=						'''
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            '''.split()
        self.run_and_check(__lowerCamelCase )

        A__											=						'''
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            '''.split()
        self.run_and_check(__lowerCamelCase )

        A__											=						'''
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            '''.split()
        self.run_and_check(__lowerCamelCase )





