





"""simple docstring"""




def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       str       ,			_lowercase		:       Dict   )					->List[Any]:






	'''simple docstring'''






	print("\nThe shortest path matrix using Floyd Warshall algorithm\n"   )
	for i in range(_lowercase   ):
		for j in range(_lowercase   ):
			if dist[i][j] != float("inf"   ):
				print(int(dist[i][j]   )       ,			end="\t"   )
			else:
				print("INF"       ,			end="\t"   )
		print()






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]       ,			_lowercase		:       Tuple   )					->Union[str, Any]:






	'''simple docstring'''






	a :						Any      =							[[float("inf"   ) for _ in range(_lowercase   )] for _ in range(_lowercase   )]

	for i in range(_lowercase   ):
		for j in range(_lowercase   ):
			a :						Dict      =							graph[i][j]

			# check vertex k against all other vertices (i, j)
	for k in range(_lowercase   ):
		# looping through rows of graph array
		for i in range(_lowercase   ):
			# looping through columns of graph array
			for j in range(_lowercase   ):
				if (
				    dist[i][k] != float("inf"   )
				    and dist[k][j] != float("inf"   )
				    and dist[i][k] + dist[k][j] < dist[i][j]
				):
					a :						Union[str, Any]      =							dist[i][k] + dist[k][j]

	_print_dist(_lowercase       ,			_lowercase   )
	return dist, v


if __name__ == "__main__":
		a		:					Optional[Any]	      =     int(input('''Enter number of vertices: '''))
		a		:					str	      =     int(input('''Enter number of edges: '''))

		a		:					Tuple	      =     [[float('''inf''') for i in range(v)] for j in range(v)]

		for i in range(v):
				a		:					Optional[Any]	      =     0.0

				# src and dst are indices that must be within the array size graph[e][v]
				# failure to follow this will result in an error
		for i in range(e):
				print('''\nEdge ''', i + 1)
				a		:					Tuple	      =     int(input('''Enter source:'''))
				a		:					Tuple	      =     int(input('''Enter destination:'''))
				a		:					List[Any]	      =     float(input('''Enter weight:'''))
				a		:					List[str]	      =     weight

		floyd_warshall(graph, v)

		# Example Input
		# Enter number of vertices: 3
		# Enter number of edges: 2

		# # generated graph from vertex and edge inputs
		# [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
		# [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

		# specify source, destination and weight for edge #1
		# Edge  1
		# Enter source:1
		# Enter destination:2
		# Enter weight:2

		# specify source, destination and weight for edge #2
		# Edge  2
		# Enter source:2
		# Enter destination:1
		# Enter weight:1

		# # Expected Output from the vertice, edge and src, dst, weight inputs!!
		# 0		INF	INF
		# INF	0	2
		# INF	1	0









"""simple docstring"""




from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_pt_objects import *  # noqa F403
else:
		from .scheduling_consistency_models import CMStochasticIterativeScheduler
		from .scheduling_ddim import DDIMScheduler
		from .scheduling_ddim_inverse import DDIMInverseScheduler
		from .scheduling_ddim_parallel import DDIMParallelScheduler
		from .scheduling_ddpm import DDPMScheduler
		from .scheduling_ddpm_parallel import DDPMParallelScheduler
		from .scheduling_deis_multistep import DEISMultistepScheduler
		from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
		from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
		from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
		from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
		from .scheduling_euler_discrete import EulerDiscreteScheduler
		from .scheduling_heun_discrete import HeunDiscreteScheduler
		from .scheduling_ipndm import IPNDMScheduler
		from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
		from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
		from .scheduling_karras_ve import KarrasVeScheduler
		from .scheduling_pndm import PNDMScheduler
		from .scheduling_repaint import RePaintScheduler
		from .scheduling_sde_ve import ScoreSdeVeScheduler
		from .scheduling_sde_vp import ScoreSdeVpScheduler
		from .scheduling_unclip import UnCLIPScheduler
		from .scheduling_unipc_multistep import UniPCMultistepScheduler
		from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
		from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_flax_objects import *  # noqa F403
else:
		from .scheduling_ddim_flax import FlaxDDIMScheduler
		from .scheduling_ddpm_flax import FlaxDDPMScheduler
		from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
		from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
		from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
		from .scheduling_pndm_flax import FlaxPNDMScheduler
		from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
		from .scheduling_utils_flax import (
		    FlaxKarrasDiffusionSchedulers,
		    FlaxSchedulerMixin,
		    FlaxSchedulerOutput,
		    broadcast_to_shape_from_left,
		)


try:
		if not (is_torch_available() and is_scipy_available()):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
		from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
		if not (is_torch_available() and is_torchsde_available()):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
		from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler


