




import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


lowercase__							:	Optional[int]											=		pytest.mark.integration


@pytest.mark.parametrize("path"	,      ["paws", "csv"]				)
def 		lowerCamelCase__       (						_A	,      _A				):







	'''simple docstring'''





	inspect_dataset(_A	,      _A				)
	snake_case_						       =	path + ".py"
	assert script_name in os.listdir(_A				)
	assert "__pycache__" not in os.listdir(_A				)


@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning"				)
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning"				)
@pytest.mark.parametrize("path"	,      ["accuracy"]				)
def 		lowerCamelCase__       (						_A	,      _A				):







	'''simple docstring'''





	inspect_metric(_A	,      _A				)
	snake_case_						       =	path + ".py"
	assert script_name in os.listdir(_A				)
	assert "__pycache__" not in os.listdir(_A				)


@pytest.mark.parametrize(
    "path, config_name, expected_splits"	,      [
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A	,      _A				):







	'''simple docstring'''





	snake_case_						       =	get_dataset_config_info(_A	,      config_name=_A				)
	assert info.config_name == config_name
	assert list(info.splits.keys()				) == expected_splits


@pytest.mark.parametrize(
    "path, config_name, expected_exception"	,      [
        ("paws", None, ValueError),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A	,      _A				):







	'''simple docstring'''





	with pytest.raises(_A				):
		get_dataset_config_info(_A	,      config_name=_A				)


@pytest.mark.parametrize(
    "path, expected"	,      [
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A				):







	'''simple docstring'''





	snake_case_						       =	get_dataset_config_names(_A				)
	assert expected in config_names


@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"	,      [
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A	,      _A				):







	'''simple docstring'''





	snake_case_						       =	get_dataset_infos(_A				)
	assert list(infos.keys()				) == expected_configs
	snake_case_						       =	expected_configs[0]
	assert expected_config in infos
	snake_case_						       =	infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()				) == expected_splits_in_first_config


@pytest.mark.parametrize(
    "path, expected_config, expected_splits"	,      [
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A	,      _A				):







	'''simple docstring'''





	snake_case_						       =	get_dataset_infos(_A				)
	assert expected_config in infos
	snake_case_						       =	infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()				) == expected_splits






@pytest.mark.parametrize(
    "path, config_name, expected_exception"	,      [
        ("paws", None, ValueError),
    ]	,      )
def 		lowerCamelCase__       (						_A	,      _A	,      _A				):







	'''simple docstring'''





	with pytest.raises(_A				):
		get_dataset_split_names(_A	,      config_name=_A				)






import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class 						UpperCAmelCase  (							UpperCAmelCase__			,  UpperCAmelCase__			,  UpperCAmelCase__     ):







						'''simple docstring'''





						@register_to_config
						def __init__(		self				:	Tuple			,      __lowercase				:	int			,      __lowercase				:	int			,      __lowercase				:	int			,      __lowercase				:	float			,      __lowercase				:	int			,      __lowercase				:	int			,      __lowercase				:	int			,      __lowercase				:	int			,      __lowercase				:	str			,      __lowercase				:	bool = False			,      ):






							"""simple docstring"""






							super().__init__()

							snake_case_						       =	nn.Embedding(__lowercase			,      __lowercase		)

							snake_case_						       =	nn.Embedding(__lowercase			,      __lowercase		)
							snake_case_						       =	False

							snake_case_						       =	nn.Dropout(p=__lowercase		)

							snake_case_						       =	TaConfig(
							    vocab_size=__lowercase			,      d_model=__lowercase			,      num_heads=__lowercase			,      d_kv=__lowercase			,      d_ff=__lowercase			,      dropout_rate=__lowercase			,      feed_forward_proj=__lowercase			,      is_decoder=__lowercase			,      is_encoder_decoder=__lowercase			,      )

							snake_case_						       =	nn.ModuleList()
							for lyr_num in range(__lowercase		):
								snake_case_						       =	TaBlock(__lowercase		)
								self.encoders.append(__lowercase		)

							snake_case_						       =	TaLayerNorm(__lowercase		)
							snake_case_						       =	nn.Dropout(p=__lowercase		)






						def 			snake_case__		(		self				:	str			,      __lowercase				:	Dict			,      __lowercase				:	str		):






							"""simple docstring"""






							snake_case_						       =	self.token_embedder(__lowercase		)

							snake_case_						       =	encoder_input_tokens.shape[1]
							snake_case_						       =	torch.arange(__lowercase			,      device=encoder_input_tokens.device		)
							x += self.position_encoding(__lowercase		)

							snake_case_						       =	self.dropout_pre(__lowercase		)

							# inverted the attention mask
							snake_case_						       =	encoder_input_tokens.size()
							snake_case_						       =	self.get_extended_attention_mask(__lowercase			,      __lowercase		)

							for lyr in self.encoders:
								snake_case_						       =	lyr(__lowercase			,      __lowercase		)[0]
							snake_case_						       =	self.layer_norm(__lowercase		)

							return self.dropout_post(__lowercase		), encoder_inputs_mask
