




from datetime import datetime

import matplotlib.pyplot as plt
import torch



def       UpperCAmelCase_       (      __UpperCamelCase      ):







    for param in module.parameters():
        SCREAMING_SNAKE_CASE__        =False



def       UpperCAmelCase_       (      ):
    SCREAMING_SNAKE_CASE__        ="""cuda""" if torch.cuda.is_available() else """cpu"""
    if torch.backends.mps.is_available() and torch.backends.mps.is_built():
        SCREAMING_SNAKE_CASE__        ="""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_       (      __UpperCamelCase      ):
    SCREAMING_SNAKE_CASE__        =plt.imshow(__snake_case      )
    fig.axes.get_xaxis().set_visible(__snake_case      )
    fig.axes.get_yaxis().set_visible(__snake_case      )
    plt.show()




def       UpperCAmelCase_       (      ):
    SCREAMING_SNAKE_CASE__        =datetime.now()
    SCREAMING_SNAKE_CASE__        =current_time.strftime("""%H:%M:%S"""      )
    return timestamp










"""simple docstring"""
from typing import TYPE_CHECKING

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


UpperCAmelCase				=						{
    """configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig""", """VisionEncoderDecoderOnnxConfig"""]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase				=						["""VisionEncoderDecoderModel"""]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase				=						["""TFVisionEncoderDecoderModel"""]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase				=						["""FlaxVisionEncoderDecoderModel"""]

if TYPE_CHECKING:
 from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
 import sys

 UpperCAmelCase				=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

