


"""simple docstring"""


def  __snake_case       (   UpperCamelCase__	)      ->		"list[int]":







		"""simple docstring"""





		if upper_limit < 0:
				raise ValueError('Limit for the Catalan sequence must be ≥ 0'	)

		A					       = [0] * (upper_limit + 1)

		# Base case: C(0) = C(1) = 1
		A					       = 1
		if upper_limit > 0:
				A					       = 1

		# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
		for i in range(2 ,			upper_limit + 1	):
				for j in range(UpperCamelCase__	):
						catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

		return catalan_list


if __name__ == "__main__":
						print("\n********* Catalan Numbers Using Dynamic Programming ************\n")
						print("\n*** Enter -1 at any time to quit ***")
						print("\nEnter the upper limit (≥ 0) for the Catalan number sequence: ", end="")
						try:
												while True:
																		UpperCamelCase						:				Dict             =      int(input().strip())
																		if N < 0:
																								print("\n********* Goodbye!! ************")
																								break
																		else:
																								print(F"""The Catalan numbers from 0 through {N} are:""")
																								print(catalan_numbers(N))
																								print("Try another upper limit for the sequence: ", end="")
						except (NameError, ValueError):
												print("\n********* Invalid input, goodbye! ************\n")

						import doctest

						doctest.testmod()









"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase						:				Any             =      {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				int             =      ["LxmertTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Union[str, Any]             =      [
	    "LxmertEncoder",
	    "LxmertForPreTraining",
	    "LxmertForQuestionAnswering",
	    "LxmertModel",
	    "LxmertPreTrainedModel",
	    "LxmertVisualFeatureEncoder",
	    "LxmertXLayer",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCamelCase						:				Union[str, Any]             =      [
	    "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFLxmertForPreTraining",
	    "TFLxmertMainLayer",
	    "TFLxmertModel",
	    "TFLxmertPreTrainedModel",
	    "TFLxmertVisualFeatureEncoder",
	]


if TYPE_CHECKING:
	from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
	from .tokenization_lxmert import LxmertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_lxmert_fast import LxmertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lxmert import (
		    LxmertEncoder,
		    LxmertForPreTraining,
		    LxmertForQuestionAnswering,
		    LxmertModel,
		    LxmertPreTrainedModel,
		    LxmertVisualFeatureEncoder,
		    LxmertXLayer,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_lxmert import (
		    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLxmertForPreTraining,
		    TFLxmertMainLayer,
		    TFLxmertModel,
		    TFLxmertPreTrainedModel,
		    TFLxmertVisualFeatureEncoder,
		)

else:
	import sys

	UpperCamelCase						:				Dict             =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





