





"""simple docstring"""




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

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


lowerCamelCase_     :						List[str]						=					[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        'text-classification',
        'language-modeling',
        'summarization',
        'token-classification',
        'question-answering',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
   import run_clm_flax
   import run_flax_glue
   import run_flax_ner
   import run_mlm_flax
   import run_qa
   import run_summarization_flax
   import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

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





def 						UpperCAmelCase__		(     ):






  """simple docstring"""





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





def 						UpperCAmelCase__		(     _UpperCAmelCase ,					_UpperCAmelCase="eval"					):






  """simple docstring"""





  A_  :       List[Any]										=  os.path.join(_UpperCAmelCase ,					f"""{split}_results.json"""					)
  if os.path.exists(_UpperCAmelCase					):
    with open(_UpperCAmelCase ,					'r'					) as f:
      return json.load(_UpperCAmelCase					)
  raise ValueError(f"""can't find {path}"""					)


lowerCamelCase_     :						str						=					logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''

      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       Any										=  self.get_auto_remove_tmp_dir()
        A_  :       int										=  F"""
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_flax_glue.main()
          A_  :       Optional[int]										=  get_results(snake_case_  )
          self.assertGreaterEqual(result['eval_accuracy']					,      0.75  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       Optional[int]										=  self.get_auto_remove_tmp_dir()
        A_  :       List[str]										=  F"""
            run_clm_flax.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_clm_flax.main()
          A_  :       Tuple										=  get_results(snake_case_  )
          self.assertLess(result['eval_perplexity']					,      1_0_0  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       str										=  self.get_auto_remove_tmp_dir()
        A_  :       Optional[Any]										=  F"""
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_summarization_flax.main()
          A_  :       str										=  get_results(snake_case_					,      split='test'  )
          self.assertGreaterEqual(result['test_rouge1']					,      1_0  )
          self.assertGreaterEqual(result['test_rouge2']					,      2  )
          self.assertGreaterEqual(result['test_rougeL']					,      7  )
          self.assertGreaterEqual(result['test_rougeLsum']					,      7  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       List[Any]										=  self.get_auto_remove_tmp_dir()
        A_  :       Optional[Any]										=  F"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_mlm_flax.main()
          A_  :       int										=  get_results(snake_case_  )
          self.assertLess(result['eval_perplexity']					,      4_2  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       Any										=  self.get_auto_remove_tmp_dir()
        A_  :       List[str]										=  F"""
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_ta_mlm_flax.main()
          A_  :       Tuple										=  get_results(snake_case_  )
          self.assertGreaterEqual(result['eval_accuracy']					,      0.42  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       Dict										=  7 if get_gpu_count() > 1 else 2

        A_  :       int										=  self.get_auto_remove_tmp_dir()
        A_  :       List[Any]										=  F"""
            run_flax_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --logging_steps 2 --eval_steps 2
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_flax_ner.main()
          A_  :       int										=  get_results(snake_case_  )
          self.assertGreaterEqual(result['eval_accuracy']					,      0.75  )
          self.assertGreaterEqual(result['eval_f1']					,      0.3  )

      @slow
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       Dict										=  self.get_auto_remove_tmp_dir()
        A_  :       Dict										=  F"""
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

        with patch.object(snake_case_					,      'argv'					,      snake_case_  ):
          run_qa.main()
          A_  :       Any										=  get_results(snake_case_  )
          self.assertGreaterEqual(result['eval_f1']					,      3_0  )
          self.assertGreaterEqual(result['eval_exact']					,      3_0  )






"""simple docstring"""




from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin

class  _UpperCAmelCase  (   UpperCAmelCase__			,   UpperCAmelCase__		):



      '''simple docstring'''

      @register_to_config
      def __init__(     self					,      snake_case_ = 7_6_8					,      ):

        """simple docstring"""

        super().__init__()

        A_  :       Optional[int]										=  nn.Parameter(torch.zeros(1					,      snake_case_  )  )
        A_  :       Optional[int]										=  nn.Parameter(torch.ones(1					,      snake_case_  )  )

      def 					lowerCamelCase_			(     self					,      snake_case_ = None					,      snake_case_ = None					,      ):

        """simple docstring"""

        A_  :       str										=  nn.Parameter(self.mean.to(snake_case_  ).to(snake_case_  )  )
        A_  :       Optional[int]										=  nn.Parameter(self.std.to(snake_case_  ).to(snake_case_  )  )
        return self

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        A_  :       Tuple										=  (embeds - self.mean) * 1.0 / self.std
        return embeds

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        A_  :       List[str]										=  (embeds * self.std) + self.mean
        return embeds