



# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path


a_			=					Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))

import dataclasses  # noqa
import io  # noqa
import itertools  # noqa
import json  # noqa
import os  # noqa
import unittest  # noqa
from copy import deepcopy  # noqa

from parameterized import parameterized  # noqa
from transformers import TrainingArguments, is_torch_available  # noqa
from transformers.deepspeed import is_deepspeed_available  # noqa
from transformers.file_utils import WEIGHTS_NAME  # noqa
from transformers.testing_utils import (  # noqa
    CaptureLogger,
    ExtendSysPath,
    TestCasePlus,
    execute_subprocess_async,
    get_gpu_count,
    mockenv_context,
    require_deepspeed,
    require_torch_gpu,
    require_torch_multi_gpu,
    slow,
)
from transformers.trainer_utils import set_seed  # noqa


set_seed(42)

a_			=					{"""base""": """patrickvonplaten/wav2vec2_tiny_random""", """robust""": """patrickvonplaten/wav2vec2_tiny_random_robust"""}

a_			=					"""zero2"""
a_			=					"""zero3"""
a_			=					[ZEROa, ZEROa]





def 		a__			(		_UpperCamelCase			: Dict ,_UpperCamelCase			: Tuple ,_UpperCamelCase			: Any							):
   # customize the test name generator function as we want both params to appear in the sub-test
   # name, as by default it shows only the first param
   __lowerCamelCase													=    parameterized.to_safe_name('''_'''.join(str(_UpperCamelCase							) for x in param.args							)							)
   return F"""{func.__name__}_{param_based_name}"""


# Cartesian-product of zero stages with models to test
a_			=					list(itertools.product(stages, models.keys()))





@slow
@require_deepspeed
@require_torch_gpu
class  __lowerCAmelCase     (	lowerCAmelCase__   ):




 @parameterized.expand(__UpperCAmelCase	,				name_func=__UpperCAmelCase				)
 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



    '''simple docstring'''
    self.run_and_check(
        stage=__UpperCAmelCase	,				model=__UpperCAmelCase	,				distributed=__UpperCAmelCase	,				fpaa=__UpperCAmelCase	,				)




 @require_torch_multi_gpu
 @parameterized.expand(__UpperCAmelCase	,				name_func=__UpperCAmelCase				)
 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



    '''simple docstring'''
    self.run_and_check(
        stage=__UpperCAmelCase	,				model=__UpperCAmelCase	,				distributed=__UpperCAmelCase	,				fpaa=__UpperCAmelCase	,				)




 @parameterized.expand(__UpperCAmelCase	,				name_func=__UpperCAmelCase				)
 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



    '''simple docstring'''
    self.run_and_check(
        stage=__UpperCAmelCase	,				model=__UpperCAmelCase	,				distributed=__UpperCAmelCase	,				fpaa=__UpperCAmelCase	,				)




 @require_torch_multi_gpu
 @parameterized.expand(__UpperCAmelCase	,				name_func=__UpperCAmelCase				)
 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



    '''simple docstring'''
    self.run_and_check(
        stage=__UpperCAmelCase	,				model=__UpperCAmelCase	,				distributed=__UpperCAmelCase	,				fpaa=__UpperCAmelCase	,				)




 def        lowerCamelCase      (						self	,				__UpperCAmelCase				):



    '''simple docstring'''
    # XXX: run_asr is premature and doesn't save any results
    # so all we check for now is that the process didn't fail
    pass




 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase	,				__UpperCAmelCase = 10	,				__UpperCAmelCase = True	,				__UpperCAmelCase = True	,				__UpperCAmelCase = True	,				):



    '''simple docstring'''
    __lowerCamelCase													=    models[model]

    __lowerCamelCase													=    self.run_trainer(
        stage=__UpperCAmelCase	,				model_name=__UpperCAmelCase	,				eval_steps=__UpperCAmelCase	,				num_train_epochs=1	,				distributed=__UpperCAmelCase	,				fpaa=__UpperCAmelCase	,				)

    self.do_checks(__UpperCAmelCase				)

    return output_dir




 def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase	,				__UpperCAmelCase = 10	,				__UpperCAmelCase = 1	,				__UpperCAmelCase = True	,				__UpperCAmelCase = True	,				):



    '''simple docstring'''
    __lowerCamelCase													=    self.get_auto_remove_tmp_dir('''./xxx'''	,				after=__UpperCAmelCase				)
    __lowerCamelCase													=    F"""
            --model_name_or_path {model_name}
            --dataset_name hf-internal-testing/librispeech_asr_dummy
            --dataset_config_name clean
            --train_split_name validation
            --validation_split_name validation
            --output_dir {output_dir}
            --num_train_epochs {str(__UpperCAmelCase				)}
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 2
            --evaluation_strategy steps
            --learning_rate 5e-4
            --warmup_steps 8
            --orthography timit
            --preprocessing_num_workers 1
            --group_by_length
            --freeze_feature_extractor
            --report_to none
            --save_steps 0
            --eval_steps {eval_steps}
            --report_to none
        """.split()

    if fpaa:
       args.extend(['''--fp16''']				)

    # currently ds_config_wav2vec2_zero.json requires "zero_optimization.find_unused_parameters": true,
    # hence the separate config files
    __lowerCamelCase													=    F"""--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json""".split()
    __lowerCamelCase													=    [F"""{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"""]
    __lowerCamelCase													=    self.get_launcher(__UpperCAmelCase				)

    __lowerCamelCase													=    launcher + script + args + ds_args
    # keep for quick debug
    # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
    execute_subprocess_async(__UpperCAmelCase	,				env=self.get_env()				)

    return output_dir




 def        lowerCamelCase      (						self	,				__UpperCAmelCase=False				):



    '''simple docstring'''
    # 1. explicitly set --num_nodes=1 just in case these tests end up run on a multi-node setup
    # - it won't be able to handle that
    # 2. for now testing with just 2 gpus max (since some quality tests may give different
    # results with mode gpus because we use very little data)
    __lowerCamelCase													=    min(2	,				get_gpu_count()				) if distributed else 1
    return F"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()











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


a_			=					logging.get_logger(__name__)

a_			=					{
    """uclanlp/visualbert-vqa""": """https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json""",
    """uclanlp/visualbert-vqa-pre""": """https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/config.json""",
    """uclanlp/visualbert-vqa-coco-pre""": (
        """https://huggingface.co/uclanlp/visualbert-vqa-coco-pre/resolve/main/config.json"""
    ),
    """uclanlp/visualbert-vcr""": """https://huggingface.co/uclanlp/visualbert-vcr/resolve/main/config.json""",
    """uclanlp/visualbert-vcr-pre""": """https://huggingface.co/uclanlp/visualbert-vcr-pre/resolve/main/config.json""",
    """uclanlp/visualbert-vcr-coco-pre""": (
        """https://huggingface.co/uclanlp/visualbert-vcr-coco-pre/resolve/main/config.json"""
    ),
    """uclanlp/visualbert-nlvr2""": """https://huggingface.co/uclanlp/visualbert-nlvr2/resolve/main/config.json""",
    """uclanlp/visualbert-nlvr2-pre""": """https://huggingface.co/uclanlp/visualbert-nlvr2-pre/resolve/main/config.json""",
    """uclanlp/visualbert-nlvr2-coco-pre""": (
        """https://huggingface.co/uclanlp/visualbert-nlvr2-coco-pre/resolve/main/config.json"""
    )
    # See all VisualBERT models at https://huggingface.co/models?filter=visual_bert
}



class  __lowerCAmelCase     (	lowerCAmelCase__   ):
 lowerCAmelCase__       					=  """visual_bert"""




 def __init__(						self	,				__UpperCAmelCase=30522	,				__UpperCAmelCase=768	,				__UpperCAmelCase=512	,				__UpperCAmelCase=12	,				__UpperCAmelCase=12	,				__UpperCAmelCase=3072	,				__UpperCAmelCase="gelu"	,				__UpperCAmelCase=0.1	,				__UpperCAmelCase=0.1	,				__UpperCAmelCase=512	,				__UpperCAmelCase=2	,				__UpperCAmelCase=0.02	,				__UpperCAmelCase=1E-1_2	,				__UpperCAmelCase=False	,				__UpperCAmelCase=True	,				__UpperCAmelCase=1	,				__UpperCAmelCase=0	,				__UpperCAmelCase=2	,				**__UpperCAmelCase	,				):



    '''simple docstring'''
    super().__init__(pad_token_id=__UpperCAmelCase	,				bos_token_id=__UpperCAmelCase	,				eos_token_id=__UpperCAmelCase	,				**__UpperCAmelCase				)

    __lowerCamelCase													=    vocab_size
    __lowerCamelCase													=    max_position_embeddings
    __lowerCamelCase													=    hidden_size
    __lowerCamelCase													=    visual_embedding_dim
    __lowerCamelCase													=    num_hidden_layers
    __lowerCamelCase													=    num_attention_heads
    __lowerCamelCase													=    intermediate_size
    __lowerCamelCase													=    hidden_act
    __lowerCamelCase													=    hidden_dropout_prob
    __lowerCamelCase													=    attention_probs_dropout_prob
    __lowerCamelCase													=    initializer_range
    __lowerCamelCase													=    type_vocab_size
    __lowerCamelCase													=    layer_norm_eps
    __lowerCamelCase													=    bypass_transformer
    __lowerCamelCase													=    special_visual_initialize






