
'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_UpperCAmelCase :   List[Any]			    =	{
    """configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5OnnxConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase :   Optional[Any]			    =	[
	    """LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """LongT5EncoderModel""",
	    """LongT5ForConditionalGeneration""",
	    """LongT5Model""",
	    """LongT5PreTrainedModel""",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase :   Tuple			    =	[
	    """FlaxLongT5ForConditionalGeneration""",
	    """FlaxLongT5Model""",
	    """FlaxLongT5PreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_longta import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongTaConfig, LongTaOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_longta import (
		    LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LongTaEncoderModel,
		    LongTaForConditionalGeneration,
		    LongTaModel,
		    LongTaPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_longta import (
		    FlaxLongTaForConditionalGeneration,
		    FlaxLongTaModel,
		    FlaxLongTaPreTrainedModel,
		)


else:
	import sys

	_UpperCAmelCase :   Optional[Any]			    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






'''simple docstring'''




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
						import torch

						from transformers.generation import DisjunctiveConstraint






@require_torch
class 							a__(   unittest.TestCase      ):


			'''simple docstring'''






			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 4], [1, 2, 3, 4]]
					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)
					self.assertTrue(isinstance(dc.token_ids			,       __lowerCAmelCase))

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]))

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint([torch.LongTensor([1, 2, 4]), torch.LongTensor([1, 2, 3, 4, 5])])



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2], [1, 2, 3, 4]]

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint(__lowerCAmelCase)  # fails here



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 3], [1, 2, 4]]

					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					lowerCAmelCase     =    stepped is True and completed is False and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					lowerCAmelCase     =    stepped is True and completed is False and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(3)
					lowerCAmelCase     =    stepped is True and completed is True and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.current_seq == [1, 2, 3])







			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(4)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2, 4])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(5)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.current_seq == [1, 2, 4, 5])

					dc.reset()

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.remaining() == 3)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.remaining() == 2)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(5)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.remaining() == 0)
					self.assertTrue(dc.current_seq == [1, 2, 5])




