import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
from datasets import Dataset

from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriever
from transformers.models.realm.tokenization_realm import VOCAB_FILES_NAMES, RealmTokenizer



class        lowercase_   (					__snake_case		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Any    =   tempfile.mkdtemp()
													_snake_case						:					List[Any]    =   5

													# Realm tok
													_snake_case						:					Dict    =   [
													    "[UNK]",
													    "[CLS]",
													    "[SEP]",
													    "[PAD]",
													    "[MASK]",
													    "test",
													    "question",
													    "this",
													    "is",
													    "the",
													    "first",
													    "second",
													    "third",
													    "fourth",
													    "fifth",
													    "record",
													    "want",
													    "##want",
													    "##ed",
													    "wa",
													    "un",
													    "runn",
													    "##ing",
													    ",",
													    "low",
													    "lowest",
													]
													_snake_case						:					List[Any]    =   os.path.join(self.tmpdirname				,    "realm_tokenizer"    )
													os.makedirs(lowercase_				,    exist_ok=lowercase_    )
													_snake_case						:					str    =   os.path.join(lowercase_				,    VOCAB_FILES_NAMES["vocab_file"]    )
													with open(self.vocab_file				,    "w"				,    encoding="utf-8"    ) as vocab_writer:
																			vocab_writer.write("".join([x + "\n" for x in vocab_tokens]    )    )

													_snake_case						:					Dict    =   os.path.join(self.tmpdirname				,    "realm_block_records"    )
													os.makedirs(lowercase_				,    exist_ok=lowercase_    )



							def 	UpperCamelCase	(						self    ):
													return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname				,    "realm_tokenizer"    )    )



							def 	UpperCamelCase	(						self    ):
													shutil.rmtree(self.tmpdirname    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Tuple    =   RealmConfig(num_block_records=self.num_block_records    )
													return config



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Dict    =   Dataset.from_dict(
													    {
													        "id": ["0", "1"],
													        "question": ["foo", "bar"],
													        "answers": [["Foo", "Bar"], ["Bar"]],
													    }    )
													return dataset



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Tuple    =   np.array(
													    [
													        B"This is the first record",
													        B"This is the second record",
													        B"This is the third record",
													        B"This is the fourth record",
													        B"This is the fifth record",
													        B"This is a longer longer longer record",
													    ]				,    dtype=lowercase_				,    )
													return block_records



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					List[str]    =   RealmRetriever(
													    block_records=self.get_dummy_block_records()				,    tokenizer=self.get_tokenizer()				,    )
													return retriever



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Union[str, Any]    =   self.get_config()
													_snake_case						:					List[Any]    =   self.get_dummy_retriever()
													_snake_case						:					Any    =   retriever.tokenizer

													_snake_case						:					Optional[int]    =   np.array([0, 3]				,    dtype="long"    )
													_snake_case						:					Optional[Any]    =   tokenizer(["Test question"]    ).input_ids
													_snake_case						:					Any    =   tokenizer(
													    ["the fourth"]				,    add_special_tokens=lowercase_				,    return_token_type_ids=lowercase_				,    return_attention_mask=lowercase_				,    ).input_ids
													_snake_case						:					List[Any]    =   config.reader_seq_len

													_snake_case    ,_snake_case    ,_snake_case    ,_snake_case						:					Any    =   retriever(
													    lowercase_				,    lowercase_				,    answer_ids=lowercase_				,    max_length=lowercase_				,    return_tensors="np"    )

													self.assertEqual(len(lowercase_    )				,    2    )
													self.assertEqual(len(lowercase_    )				,    2    )
													self.assertEqual(len(lowercase_    )				,    2    )
													self.assertEqual(concat_inputs.input_ids.shape				,    (2, 10)    )
													self.assertEqual(concat_inputs.attention_mask.shape				,    (2, 10)    )
													self.assertEqual(concat_inputs.token_type_ids.shape				,    (2, 10)    )
													self.assertEqual(concat_inputs.special_tokens_mask.shape				,    (2, 10)    )
													self.assertEqual(
													    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[0]    )				,    ["[CLS]", "test", "question", "[SEP]", "this", "is", "the", "first", "record", "[SEP]"]				,    )
													self.assertEqual(
													    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[1]    )				,    ["[CLS]", "test", "question", "[SEP]", "this", "is", "the", "fourth", "record", "[SEP]"]				,    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Union[str, Any]    =   self.get_config()
													_snake_case						:					Union[str, Any]    =   self.get_dummy_retriever()
													_snake_case						:					Tuple    =   retriever.tokenizer

													_snake_case						:					Union[str, Any]    =   np.array([0, 3, 5]				,    dtype="long"    )
													_snake_case						:					Optional[Any]    =   tokenizer(["Test question"]    ).input_ids
													_snake_case						:					Optional[Any]    =   tokenizer(
													    ["the fourth", "longer longer"]				,    add_special_tokens=lowercase_				,    return_token_type_ids=lowercase_				,    return_attention_mask=lowercase_				,    ).input_ids
													_snake_case						:					List[str]    =   config.reader_seq_len

													_snake_case    ,_snake_case    ,_snake_case    ,_snake_case						:					Optional[Any]    =   retriever(
													    lowercase_				,    lowercase_				,    answer_ids=lowercase_				,    max_length=lowercase_				,    return_tensors="np"    )

													self.assertEqual([False, True, True]				,    lowercase_    )
													self.assertEqual([[-1, -1, -1], [6, -1, -1], [6, 7, 8]]				,    lowercase_    )
													self.assertEqual([[-1, -1, -1], [7, -1, -1], [7, 8, 9]]				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					int    =   self.get_dummy_retriever()
													retriever.save_pretrained(os.path.join(self.tmpdirname				,    "realm_block_records"    )    )

													# Test local path
													_snake_case						:					Optional[Any]    =   retriever.from_pretrained(os.path.join(self.tmpdirname				,    "realm_block_records"    )    )
													self.assertEqual(retriever.block_records[0]				,    B"This is the first record"    )

													# Test mocked remote path
													with patch("transformers.models.realm.retrieval_realm.hf_hub_download"    ) as mock_hf_hub_download:
																			_snake_case						:					Any    =   os.path.join(
																			    os.path.join(self.tmpdirname				,    "realm_block_records"    )				,    _REALM_BLOCK_RECORDS_FILENAME    )
																			_snake_case						:					List[Any]    =   RealmRetriever.from_pretrained("google/realm-cc-news-pretrained-openqa"    )

													self.assertEqual(retriever.block_records[0]				,    B"This is the first record"    )
import os

import pytest
from attr import dataclass


__SCREAMING_SNAKE_CASE						:   int         =			'us-east-1'  # defaults region



@dataclass
class        lowercase_   :
							_lowerCamelCase						=		42
							_lowerCamelCase						=		'arn:aws:iam::558105141721:role/sagemaker_execution_role'
							_lowerCamelCase						=		{
							    'task_name': 'mnli',
							    'per_device_train_batch_size': 16,
							    'per_device_eval_batch_size': 16,
							    'do_train': True,
							    'do_eval': True,
							    'do_predict': True,
							    'output_dir': '/opt/ml/model',
							    'overwrite_output_dir': True,
							    'max_steps': 500,
							    'save_steps': 5_500,
							}
							_lowerCamelCase						=		{**hyperparameters, 'max_steps': 1_000}



							@property
							def 	UpperCamelCase	(						self    ):
													if self.framework == "pytorch":
																			return [
																			    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																			    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
																			    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
																			]
													else:
																			return [
																			    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																			    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
																			    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
																			]



							@property
							def 	UpperCamelCase	(						self    ):
													return f"""{self.framework}-transfromers-test"""



							@property
							def 	UpperCamelCase	(						self    ):
													return f"""./tests/sagemaker/scripts/{self.framework}"""



							@property
							def 	UpperCamelCase	(						self    ):
													if self.framework == "pytorch":
																			return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
													else:
																			return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"




@pytest.fixture(scope="class"						)
def  snake_case						(__lowercase						)	->	str:

						'''simple docstring'''



						_snake_case						:					List[str]    =   SageMakerTestEnvironment(framework=request.cls.framework						)