import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Any      =				DownBlockaD  # noqa F405
				a__     :						Dict      =				"""down"""







				def       UpperCamelCase__       (     self)	->     List[str]:
								__UpperCamelCase					:Tuple        =		[-0.02_32, -0.98_69, 0.80_54, -0.06_37, -0.16_88, -1.42_64, 0.44_70, -1.33_94, 0.09_04]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Any      =				ResnetDownsampleBlockaD  # noqa F405
				a__     :						Any      =				"""down"""







				def       UpperCamelCase__       (     self)	->     Optional[int]:
								__UpperCamelCase					:List[Any]        =		[0.07_10, 0.24_10, -0.73_20, -1.07_57, -1.13_43, 0.35_40, -0.01_33, -0.25_76, 0.09_48]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Any      =				AttnDownBlockaD  # noqa F405
				a__     :						List[Any]      =				"""down"""







				def       UpperCamelCase__       (     self)	->     int:
								__UpperCamelCase					:List[str]        =		[0.06_36, 0.89_64, -0.62_34, -1.01_31, 0.08_44, 0.49_35, 0.34_37, 0.09_11, -0.29_57]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						List[Any]      =				CrossAttnDownBlockaD  # noqa F405
				a__     :						int      =				"""down"""







				def       UpperCamelCase__       (     self)	->     Union[str, Any]:
								__UpperCamelCase					:Any        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:Optional[Any]        =		32
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     Tuple:
								__UpperCamelCase					:List[Any]        =		[0.22_38, -0.73_96, -0.22_55, -0.38_29, 0.19_25, 1.16_65, 0.06_03, -0.72_95, 0.19_83]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Dict      =				SimpleCrossAttnDownBlockaD  # noqa F405
				a__     :						Optional[int]      =				"""down"""







				@property
				def       UpperCamelCase__       (     self)	->     Optional[int]:
								return super().get_dummy_input(include_encoder_hidden_states=__lowercase)







				def       UpperCamelCase__       (     self)	->     List[str]:
								__UpperCamelCase					:str        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:str        =		32
								return init_dict, inputs_dict







				@unittest.skipIf(torch_device == '''mps'''			,			'''MPS result is not consistent''')
				def       UpperCamelCase__       (     self)	->     Optional[int]:
								__UpperCamelCase					:int        =		[0.79_21, -0.09_92, -0.19_62, -0.76_95, -0.42_42, 0.78_04, 0.47_37, 0.27_65, 0.33_38]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Union[str, Any]      =				SkipDownBlockaD  # noqa F405
				a__     :						List[Any]      =				"""down"""







				@property
				def       UpperCamelCase__       (     self)	->     Any:
								return super().get_dummy_input(include_skip_sample=__lowercase)







				def       UpperCamelCase__       (     self)	->     Union[str, Any]:
								__UpperCamelCase					:int        =		[-0.08_45, -0.20_87, -0.24_65, 0.09_71, 0.19_00, -0.04_84, 0.26_64, 0.41_79, 0.50_69]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Union[str, Any]      =				AttnSkipDownBlockaD  # noqa F405
				a__     :						Any      =				"""down"""







				@property
				def       UpperCamelCase__       (     self)	->     List[str]:
								return super().get_dummy_input(include_skip_sample=__lowercase)







				def       UpperCamelCase__       (     self)	->     Optional[int]:
								__UpperCamelCase					:Any        =		[0.55_39, 0.16_09, 0.49_24, 0.05_37, -0.19_95, 0.40_50, 0.09_79, -0.27_21, -0.06_42]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Tuple      =				DownEncoderBlockaD  # noqa F405
				a__     :						Dict      =				"""down"""







				@property
				def       UpperCamelCase__       (     self)	->     List[str]:
								return super().get_dummy_input(include_temb=__lowercase)







				def       UpperCamelCase__       (     self)	->     Union[str, Any]:
								__UpperCamelCase					:List[str]        =		{
								    '''in_channels''': 32,
								    '''out_channels''': 32,
								}
								__UpperCamelCase					:List[Any]        =		self.dummy_input
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     Any:
								__UpperCamelCase					:Dict        =		[1.11_02, 0.53_02, 0.48_72, -0.00_23, -0.80_42, 0.04_83, -0.34_89, -0.56_32, 0.76_26]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Union[str, Any]      =				AttnDownEncoderBlockaD  # noqa F405
				a__     :						Optional[int]      =				"""down"""







				@property
				def       UpperCamelCase__       (     self)	->     Any:
								return super().get_dummy_input(include_temb=__lowercase)







				def       UpperCamelCase__       (     self)	->     Any:
								__UpperCamelCase					:Optional[int]        =		{
								    '''in_channels''': 32,
								    '''out_channels''': 32,
								}
								__UpperCamelCase					:List[Any]        =		self.dummy_input
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     List[Any]:
								__UpperCamelCase					:int        =		[0.89_66, -0.14_86, 0.85_68, 0.81_41, -0.90_46, -0.13_42, -0.09_72, -0.74_17, 0.15_38]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						str      =				UNetMidBlockaD  # noqa F405
				a__     :						Union[str, Any]      =				"""mid"""







				def       UpperCamelCase__       (     self)	->     Optional[int]:
								__UpperCamelCase					:Optional[int]        =		{
								    '''in_channels''': 32,
								    '''temb_channels''': 128,
								}
								__UpperCamelCase					:Dict        =		self.dummy_input
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     int:
								__UpperCamelCase					:Tuple        =		[-0.10_62, 1.72_48, 0.34_94, 1.45_69, -0.09_10, -1.24_21, -0.99_84, 0.67_36, 1.00_28]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						int      =				UNetMidBlockaDCrossAttn  # noqa F405
				a__     :						Tuple      =				"""mid"""







				def       UpperCamelCase__       (     self)	->     List[str]:
								__UpperCamelCase					:Tuple        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:Optional[Any]        =		32
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     str:
								__UpperCamelCase					:Optional[Any]        =		[0.01_87, 2.42_20, 0.44_84, 1.12_03, -0.61_21, -1.51_22, -0.82_70, 0.78_51, 1.83_35]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						str      =				UNetMidBlockaDSimpleCrossAttn  # noqa F405
				a__     :						int      =				"""mid"""







				@property
				def       UpperCamelCase__       (     self)	->     List[str]:
								return super().get_dummy_input(include_encoder_hidden_states=__lowercase)







				def       UpperCamelCase__       (     self)	->     Any:
								__UpperCamelCase					:Optional[Any]        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:int        =		32
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     List[str]:
								__UpperCamelCase					:Tuple        =		[0.71_43, 1.99_74, 0.54_48, 1.39_77, 0.12_82, -1.12_37, -1.42_38, 0.55_30, 0.88_80]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						List[str]      =				UpBlockaD  # noqa F405
				a__     :						str      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Optional[Any]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				def       UpperCamelCase__       (     self)	->     Dict:
								__UpperCamelCase					:Optional[int]        =		[-0.20_41, -0.41_65, -0.30_22, 0.00_41, -0.66_28, -0.70_53, 0.19_28, -0.03_25, 0.05_23]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Optional[int]      =				ResnetUpsampleBlockaD  # noqa F405
				a__     :						Optional[int]      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     List[str]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				def       UpperCamelCase__       (     self)	->     Optional[Any]:
								__UpperCamelCase					:Tuple        =		[0.22_87, 0.35_49, -0.13_46, 0.47_97, -0.17_15, -0.96_49, 0.73_05, -0.58_64, -0.62_44]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Optional[Any]      =				CrossAttnUpBlockaD  # noqa F405
				a__     :						List[Any]      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Optional[Any]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				def       UpperCamelCase__       (     self)	->     Any:
								__UpperCamelCase					:Union[str, Any]        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:Optional[int]        =		32
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     List[Any]:
								__UpperCamelCase					:Optional[int]        =		[-0.14_03, -0.35_15, -0.04_20, -0.14_25, 0.31_67, 0.50_94, -0.21_81, 0.59_31, 0.55_82]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Union[str, Any]      =				SimpleCrossAttnUpBlockaD  # noqa F405
				a__     :						int      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Dict:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase			,			include_encoder_hidden_states=__lowercase)







				def       UpperCamelCase__       (     self)	->     Tuple:
								__UpperCamelCase					:Dict        =		super().prepare_init_args_and_inputs_for_common()
								__UpperCamelCase					:int        =		32
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     Union[str, Any]:
								__UpperCamelCase					:Optional[int]        =		[0.26_45, 0.14_80, 0.09_09, 0.80_44, -0.97_58, -0.90_83, 0.09_94, -1.14_53, -0.74_02]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Optional[int]      =				AttnUpBlockaD  # noqa F405
				a__     :						List[str]      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Optional[int]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				@unittest.skipIf(torch_device == '''mps'''			,			'''MPS result is not consistent''')
				def       UpperCamelCase__       (     self)	->     List[Any]:
								__UpperCamelCase					:int        =		[0.09_79, 0.13_26, 0.00_21, 0.06_59, 0.22_49, 0.00_59, 0.11_32, 0.59_52, 0.10_33]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Dict      =				SkipUpBlockaD  # noqa F405
				a__     :						Optional[Any]      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Optional[Any]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				def       UpperCamelCase__       (     self)	->     Tuple:
								__UpperCamelCase					:Optional[Any]        =		[-0.08_93, -0.12_34, -0.15_06, -0.03_32, 0.01_23, -0.02_11, 0.05_66, 0.01_43, 0.03_62]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Tuple      =				AttnSkipUpBlockaD  # noqa F405
				a__     :						List[Any]      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     List[str]:
								return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase)







				def       UpperCamelCase__       (     self)	->     List[str]:
								__UpperCamelCase					:List[str]        =		[0.03_61, 0.06_17, 0.27_87, -0.03_50, 0.03_42, 0.34_21, -0.08_43, 0.09_13, 0.30_15]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						List[str]      =				UpDecoderBlockaD  # noqa F405
				a__     :						int      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     Dict:
								return super().get_dummy_input(include_temb=__lowercase)







				def       UpperCamelCase__       (     self)	->     Optional[int]:
								__UpperCamelCase					:Union[str, Any]        =		{'''in_channels''': 32, '''out_channels''': 32}

								__UpperCamelCase					:List[Any]        =		self.dummy_input
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     Optional[Any]:
								__UpperCamelCase					:int        =		[0.44_04, 0.19_98, -0.98_86, -0.33_20, -0.31_28, -0.70_34, -0.69_55, -0.23_38, -0.31_37]
								super().test_output(__lowercase)


class      lowerCamelCase_					(       UpperCAmelCase_						,     unittest.TestCase			):






				'''simple docstring'''






				a__     :						Tuple      =				AttnUpDecoderBlockaD  # noqa F405
				a__     :						str      =				"""up"""







				@property
				def       UpperCamelCase__       (     self)	->     int:
								return super().get_dummy_input(include_temb=__lowercase)







				def       UpperCamelCase__       (     self)	->     int:
								__UpperCamelCase					:List[str]        =		{'''in_channels''': 32, '''out_channels''': 32}

								__UpperCamelCase					:int        =		self.dummy_input
								return init_dict, inputs_dict







				def       UpperCamelCase__       (     self)	->     Tuple:
								__UpperCamelCase					:List[str]        =		[0.67_38, 0.44_91, 0.10_55, 1.07_10, 0.73_16, 0.33_39, 0.33_52, 0.10_23, 0.35_68]
								super().test_output(__lowercase)






import os
from pathlib import Path

import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader

from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart import shift_tokens_right
from transformers.testing_utils import TestCasePlus, slow
from utils import FAIRSEQ_AVAILABLE, DistributedSortishSampler, LegacySeqaSeqDataset, SeqaSeqDataset


__lowercase										= '''bert-base-cased'''
__lowercase										= '''google/pegasus-xsum'''
__lowercase										= [''' Sam ate lunch today.''', '''Sams lunch ingredients.''']
__lowercase										= ['''A very interesting story about what I ate for lunch.''', '''Avocado, celery, turkey, coffee''']
__lowercase										= '''patrickvonplaten/t5-tiny-random'''
__lowercase										= '''sshleifer/bart-tiny-random'''
__lowercase										= '''sshleifer/tiny-mbart'''
__lowercase										= '''sshleifer/tiny-marian-en-de'''



def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    __UpperCamelCase					:str        =		'''\n'''.join(SCREAMING_SNAKE_CASE     )
    Path(SCREAMING_SNAKE_CASE     ).open('''w'''     ).writelines(SCREAMING_SNAKE_CASE     )



def lowerCamelCase  (       SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    for split in ["train", "val", "test"]:
        _dump_articles(os.path.join(SCREAMING_SNAKE_CASE  ,      f"""{split}.source"""     )  ,      SCREAMING_SNAKE_CASE     )
        _dump_articles(os.path.join(SCREAMING_SNAKE_CASE  ,      f"""{split}.target"""     )  ,      SCREAMING_SNAKE_CASE     )
    return tmp_dir


class      lowerCamelCase_					(       UpperCAmelCase_			):






    '''simple docstring'''






    @parameterized.expand(
        [
            MBART_TINY,
            MARIAN_TINY,
            T5_TINY,
            BART_TINY,
            PEGASUS_XSUM,
        ]			,			)
    @slow
    def       UpperCamelCase__       (     self			,			__lowercase)	->     List[Any]:
        __UpperCamelCase					:Dict        =		AutoTokenizer.from_pretrained(__lowercase)
        __UpperCamelCase					:Optional[Any]        =		make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir())
        __UpperCamelCase					:List[Any]        =		max(len(tokenizer.encode(__lowercase)) for a in ARTICLES)
        __UpperCamelCase					:Optional[int]        =		max(len(tokenizer.encode(__lowercase)) for a in SUMMARIES)
        __UpperCamelCase					:int        =		4
        __UpperCamelCase					:Any        =		8
        assert max_len_target > max_src_len  # Will be truncated
        assert max_len_source > max_src_len  # Will be truncated
        __UpperCamelCase  ,	__UpperCamelCase					:Tuple        =		'''ro_RO''', '''de_DE'''  # ignored for all but mbart, but never causes error.
        __UpperCamelCase					:str        =		SeqaSeqDataset(
            __lowercase			,			data_dir=__lowercase			,			type_path='''train'''			,			max_source_length=__lowercase			,			max_target_length=__lowercase			,			src_lang=__lowercase			,			tgt_lang=__lowercase			,			)
        __UpperCamelCase					:Any        =		DataLoader(__lowercase			,			batch_size=2			,			collate_fn=train_dataset.collate_fn)
        for batch in dataloader:
            assert isinstance(__lowercase			,			__lowercase)
            assert batch["attention_mask"].shape == batch["input_ids"].shape
            # show that articles were trimmed.
            assert batch["input_ids"].shape[1] == max_src_len
            # show that targets are the same len
            assert batch["labels"].shape[1] == max_tgt_len
            if tok_name != MBART_TINY:
                continue
            # check language codes in correct place
            __UpperCamelCase					:Optional[int]        =		shift_tokens_right(batch['''labels''']			,			tokenizer.pad_token_id)
            assert batch["decoder_input_ids"][0, 0].item() == tokenizer.lang_code_to_id[tgt_lang]
            assert batch["decoder_input_ids"][0, -1].item() == tokenizer.eos_token_id
            assert batch["input_ids"][0, -2].item() == tokenizer.eos_token_id
            assert batch["input_ids"][0, -1].item() == tokenizer.lang_code_to_id[src_lang]

            break  # No need to test every batch







    @parameterized.expand([BART_TINY, BERT_BASE_CASED])
    def       UpperCamelCase__       (     self			,			__lowercase)	->     int:
        __UpperCamelCase					:Union[str, Any]        =		AutoTokenizer.from_pretrained(__lowercase)
        __UpperCamelCase					:Union[str, Any]        =		make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir())
        __UpperCamelCase					:int        =		max(len(tokenizer.encode(__lowercase)) for a in ARTICLES)
        __UpperCamelCase					:Dict        =		max(len(tokenizer.encode(__lowercase)) for a in SUMMARIES)
        __UpperCamelCase					:Union[str, Any]        =		4
        __UpperCamelCase					:List[str]        =		LegacySeqaSeqDataset(
            __lowercase			,			data_dir=__lowercase			,			type_path='''train'''			,			max_source_length=20			,			max_target_length=__lowercase			,			)
        __UpperCamelCase					:Dict        =		DataLoader(__lowercase			,			batch_size=2			,			collate_fn=train_dataset.collate_fn)
        for batch in dataloader:
            assert batch["attention_mask"].shape == batch["input_ids"].shape
            # show that articles were trimmed.
            assert batch["input_ids"].shape[1] == max_len_source
            assert 20 >= batch["input_ids"].shape[1]  # trimmed significantly
            # show that targets were truncated
            assert batch["labels"].shape[1] == trunc_target  # Truncated
            assert max_len_target > trunc_target  # Truncated
            break  # No need to test every batch







    def       UpperCamelCase__       (     self)	->     Dict:
        __UpperCamelCase					:List[Any]        =		AutoTokenizer.from_pretrained('''facebook/mbart-large-cc25''')

        __UpperCamelCase					:Union[str, Any]        =		Path(make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()))
        __UpperCamelCase					:str        =		tmp_dir.joinpath('''train.source''').open().readlines()
        __UpperCamelCase					:int        =		Path(make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir()))
        pack_data_dir(__lowercase			,			__lowercase			,			128			,			__lowercase)
        __UpperCamelCase					:Union[str, Any]        =		{x.name for x in tmp_dir.iterdir()}
        __UpperCamelCase					:int        =		{x.name for x in save_dir.iterdir()}
        __UpperCamelCase					:Optional[int]        =		save_dir.joinpath('''train.source''').open().readlines()
        # orig: [' Sam ate lunch today.\n', 'Sams lunch ingredients.']
        # desired_packed: [' Sam ate lunch today.\n Sams lunch ingredients.']
        assert len(__lowercase) < len(__lowercase)
        assert len(__lowercase) == 1
        assert len(packed_examples[0]) == sum(len(__lowercase) for x in orig_examples)
        assert orig_paths == new_paths







    @pytest.mark.skipif(not FAIRSEQ_AVAILABLE			,			reason='''This test requires fairseq''')
    def       UpperCamelCase__       (     self)	->     List[Any]:
        if not FAIRSEQ_AVAILABLE:
            return
        __UpperCamelCase  ,	__UpperCamelCase  ,	__UpperCamelCase					:Any        =		self._get_dataset(max_len=64)
        __UpperCamelCase					:Union[str, Any]        =		64
        __UpperCamelCase					:Tuple        =		ds.make_dynamic_sampler(__lowercase			,			required_batch_size_multiple=__lowercase)
        __UpperCamelCase					:List[str]        =		[len(__lowercase) for x in batch_sampler]
        assert len(set(__lowercase)) > 1  # it's not dynamic batch size if every batch is the same length
        assert sum(__lowercase) == len(__lowercase)  # no dropped or added examples
        __UpperCamelCase					:int        =		DataLoader(__lowercase			,			batch_sampler=__lowercase			,			collate_fn=ds.collate_fn			,			num_workers=2)
        __UpperCamelCase					:List[str]        =		[]
        __UpperCamelCase					:int        =		[]
        for batch in data_loader:
            __UpperCamelCase					:List[Any]        =		batch['''input_ids'''].shape
            __UpperCamelCase					:Dict        =		src_shape[0]
            assert bs % required_batch_size_multiple == 0 or bs < required_batch_size_multiple
            __UpperCamelCase					:Optional[int]        =		np.product(batch['''input_ids'''].shape)
            num_src_per_batch.append(__lowercase)
            if num_src_tokens > (max_tokens * 1.1):
                failures.append(__lowercase)
        assert num_src_per_batch[0] == max(__lowercase)
        if failures:
            raise AssertionError(f"""too many tokens in {len(__lowercase)} batches""")







    def       UpperCamelCase__       (     self)	->     Tuple:
        __UpperCamelCase  ,	__UpperCamelCase  ,	__UpperCamelCase					:Optional[Any]        =		self._get_dataset(max_len=512)
        __UpperCamelCase					:Any        =		2
        __UpperCamelCase					:List[Any]        =		ds.make_sortish_sampler(__lowercase			,			shuffle=__lowercase)

        __UpperCamelCase					:List[Any]        =		DataLoader(__lowercase			,			batch_size=__lowercase			,			collate_fn=ds.collate_fn			,			num_workers=2)
        __UpperCamelCase					:Tuple        =		DataLoader(__lowercase			,			batch_size=__lowercase			,			collate_fn=ds.collate_fn			,			num_workers=2			,			sampler=__lowercase)

        __UpperCamelCase					:int        =		tokenizer.pad_token_id

        def count_pad_tokens(__lowercase			,			__lowercase="input_ids"):
            return [batch[k].eq(__lowercase).sum().item() for batch in data_loader]

        assert sum(count_pad_tokens(__lowercase			,			k='''labels''')) < sum(count_pad_tokens(__lowercase			,			k='''labels'''))
        assert sum(count_pad_tokens(__lowercase)) < sum(count_pad_tokens(__lowercase))
        assert len(__lowercase) == len(__lowercase)







    def       UpperCamelCase__       (     self			,			__lowercase=1_000			,			__lowercase=128)	->     List[Any]:
        if os.getenv('''USE_REAL_DATA'''			,			__lowercase):
            __UpperCamelCase					:Optional[Any]        =		'''examples/seq2seq/wmt_en_ro'''
            __UpperCamelCase					:Dict        =		max_len * 2 * 64
            if not Path(__lowercase).joinpath('''train.len''').exists():
                save_len_file(__lowercase			,			__lowercase)
        else:
            __UpperCamelCase					:Union[str, Any]        =		'''examples/seq2seq/test_data/wmt_en_ro'''
            __UpperCamelCase					:Optional[int]        =		max_len * 4
            save_len_file(__lowercase			,			__lowercase)

        __UpperCamelCase					:str        =		AutoTokenizer.from_pretrained(__lowercase)
        __UpperCamelCase					:List[Any]        =		SeqaSeqDataset(
            __lowercase			,			data_dir=__lowercase			,			type_path='''train'''			,			max_source_length=__lowercase			,			max_target_length=__lowercase			,			n_obs=__lowercase			,			)
        return ds, max_tokens, tokenizer







    def       UpperCamelCase__       (     self)	->     Tuple:
        __UpperCamelCase  ,	__UpperCamelCase  ,	__UpperCamelCase					:List[Any]        =		self._get_dataset()
        __UpperCamelCase					:List[str]        =		set(DistributedSortishSampler(__lowercase			,			256			,			num_replicas=2			,			rank=0			,			add_extra_examples=__lowercase))
        __UpperCamelCase					:Tuple        =		set(DistributedSortishSampler(__lowercase			,			256			,			num_replicas=2			,			rank=1			,			add_extra_examples=__lowercase))
        assert idsa.intersection(__lowercase) == set()







    @parameterized.expand(
        [
            MBART_TINY,
            MARIAN_TINY,
            T5_TINY,
            BART_TINY,
            PEGASUS_XSUM,
        ]			,			)
    def       UpperCamelCase__       (     self			,			__lowercase)	->     List[Any]:
        __UpperCamelCase					:List[Any]        =		AutoTokenizer.from_pretrained(__lowercase			,			use_fast=__lowercase)
        if tok_name == MBART_TINY:
            __UpperCamelCase					:Optional[Any]        =		SeqaSeqDataset(
                __lowercase			,			data_dir=make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir())			,			type_path='''train'''			,			max_source_length=4			,			max_target_length=8			,			src_lang='''EN'''			,			tgt_lang='''FR'''			,			)
            __UpperCamelCase					:Tuple        =		train_dataset.dataset_kwargs
            assert "src_lang" in kwargs and "tgt_lang" in kwargs
        else:
            __UpperCamelCase					:Tuple        =		SeqaSeqDataset(
                __lowercase			,			data_dir=make_test_data_dir(tmp_dir=self.get_auto_remove_tmp_dir())			,			type_path='''train'''			,			max_source_length=4			,			max_target_length=8			,			)
            __UpperCamelCase					:Optional[int]        =		train_dataset.dataset_kwargs
            assert "add_prefix_space" not in kwargs if tok_name != BART_TINY else "add_prefix_space" in kwargs
            assert len(__lowercase) == 1 if tok_name == BART_TINY else len(__lowercase) == 0





