

from datetime import datetime

import matplotlib.pyplot as plt
import torch

def 		UpperCamelCase      (lowercase_:				Optional[int]      )  ->   List[str]:
	for param in module.parameters():
		A__							:					Union[str, Any]       =	False

def 		UpperCamelCase      ()  ->   List[str]:
	A__							:					Tuple       =	"""cuda""" if torch.cuda.is_available() else """cpu"""
	if torch.backends.mps.is_available() and torch.backends.mps.is_built():
		A__							:					Any       =	"""mps"""
	if device == "mps":
		print(
		    """WARNING: MPS currently doesn't seem to work, and messes up backpropagation without any visible torch"""
		    """ errors. I recommend using CUDA on a colab notebook or CPU instead if you're facing inexplicable issues"""
		    """ with generations."""      )
	return device

def 		UpperCamelCase      (lowercase_:				Any      )  ->   List[str]:
	A__							:					Tuple       =	plt.imshow(lowercase_      )
	fig.axes.get_xaxis().set_visible(lowercase_      )
	fig.axes.get_yaxis().set_visible(lowercase_      )
	plt.show()


def 		UpperCamelCase      ()  ->   Optional[Any]:
	A__							:					Optional[int]       =	datetime.now()
	A__							:					Union[str, Any]       =	current_time.strftime("""%H:%M:%S"""      )
	return timestamp






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A_ :				Optional[Any]						 =    {}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_ :				str						 =    ['BartphoTokenizer']

if TYPE_CHECKING:
	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bartpho import BartphoTokenizer

else:
	import sys

	A_ :				Optional[int]						 =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



