

"""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


_a							=							[
    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)

_a							=							logging.getLogger()




def   _A  (  )     ->						Any:
   '''simple docstring'''


   __lowercase								=						argparse.ArgumentParser()
   parser.add_argument("-f")
   __lowercase								=						parser.parse_args()
   return args.f




def   _A  (  UpperCamelCase_					:	List[Any],      UpperCamelCase_					:	Optional[int]="eval")     ->						List[str]:
   '''simple docstring'''


   __lowercase								=						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}""")


_a							=							logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)




class  _lowerCAmelCase  (     lowercase       ):







 """simple docstring"""







 def  _lowercase			(      self							:      Dict     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_flax_glue.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertGreaterEqual(result["eval_accuracy"], 0.75     )


 @slow
 def  _lowercase			(      self							:      str     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_clm_flax.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertLess(result["eval_perplexity"], 1_0_0     )


 @slow
 def  _lowercase			(      self							:      Any     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_summarization_flax.main()
       __lowercase								=						get_results(UpperCAmelCase__, 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  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_mlm_flax.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertLess(result["eval_perplexity"], 4_2     )


 @slow
 def  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_ta_mlm_flax.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertGreaterEqual(result["eval_accuracy"], 0.42     )


 @slow
 def  _lowercase			(      self							:      List[str]     ):
    # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
    __lowercase								=						7 if get_gpu_count() > 1 else 2

    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_flax_ner.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertGreaterEqual(result["eval_accuracy"], 0.75     )
       self.assertGreaterEqual(result["eval_f1"], 0.3     )



 @slow
 def  _lowercase			(      self							:      Any     ):
    __lowercase								=						self.get_auto_remove_tmp_dir()
    __lowercase								=						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(UpperCAmelCase__, "argv", UpperCAmelCase__     ):
       run_qa.main()
       __lowercase								=						get_results(UpperCAmelCase__     )
       self.assertGreaterEqual(result["eval_f1"], 3_0     )
       self.assertGreaterEqual(result["eval_exact"], 3_0     )







"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a							=							logging.get_logger(__name__)

_a							=							{
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}




class  _lowerCAmelCase  (     lowercase       ):







 """simple docstring"""







 __UpperCAmelCase     : List[Any]       		=     "swin2sr"

 __UpperCAmelCase     : List[Any]       		=     {
     "hidden_size": "embed_dim",
     "num_attention_heads": "num_heads",
     "num_hidden_layers": "num_layers",
 }


 def __init__(      self							:      Any, UpperCAmelCase__							:      Dict=6_4, UpperCAmelCase__							:      List[Any]=1, UpperCAmelCase__							:      Dict=3, UpperCAmelCase__							:      Optional[Any]=1_8_0, UpperCAmelCase__							:      Any=[6, 6, 6, 6, 6, 6], UpperCAmelCase__							:      Dict=[6, 6, 6, 6, 6, 6], UpperCAmelCase__							:      Tuple=8, UpperCAmelCase__							:      Optional[int]=2.0, UpperCAmelCase__							:      List[str]=True, UpperCAmelCase__							:      Tuple=0.0, UpperCAmelCase__							:      Optional[Any]=0.0, UpperCAmelCase__							:      List[str]=0.1, UpperCAmelCase__							:      Dict="gelu", UpperCAmelCase__							:      Dict=False, UpperCAmelCase__							:      Dict=0.02, UpperCAmelCase__							:      Tuple=1E-5, UpperCAmelCase__							:      str=2, UpperCAmelCase__							:      str=1.0, UpperCAmelCase__							:      Optional[int]="1conv", UpperCAmelCase__							:      Dict="pixelshuffle", **UpperCAmelCase__							:      List[Any], ):
    super().__init__(**UpperCAmelCase__     )

    __lowercase								=						image_size
    __lowercase								=						patch_size
    __lowercase								=						num_channels
    __lowercase								=						embed_dim
    __lowercase								=						depths
    __lowercase								=						len(UpperCAmelCase__     )
    __lowercase								=						num_heads
    __lowercase								=						window_size
    __lowercase								=						mlp_ratio
    __lowercase								=						qkv_bias
    __lowercase								=						hidden_dropout_prob
    __lowercase								=						attention_probs_dropout_prob
    __lowercase								=						drop_path_rate
    __lowercase								=						hidden_act
    __lowercase								=						use_absolute_embeddings
    __lowercase								=						layer_norm_eps
    __lowercase								=						initializer_range
    __lowercase								=						upscale
    __lowercase								=						img_range
    __lowercase								=						resi_connection
    __lowercase								=						upsampler




