




from datetime import datetime

import matplotlib.pyplot as plt
import torch







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     for param in module.parameters():
          UpperCAmelCase_     :				str  =     False







def lowerCamelCase__  (     ):

     '''simple docstring'''


     UpperCAmelCase_     :				List[str]  =     '''cuda''' if torch.cuda.is_available() else '''cpu'''
     if torch.backends.mps.is_available() and torch.backends.mps.is_built():
          UpperCAmelCase_     :				Dict  =     '''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 lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				Tuple  =     plt.imshow(_lowercase )
     fig.axes.get_xaxis().set_visible(_lowercase )
     fig.axes.get_yaxis().set_visible(_lowercase )
     plt.show()







def lowerCamelCase__  (     ):

     '''simple docstring'''


     UpperCAmelCase_     :				Optional[Any]  =     datetime.now()
     UpperCAmelCase_     :				Optional[Any]  =     current_time.strftime('''%H:%M:%S''' )
     return timestamp







'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase      					={
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase      					=[
          "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ClapModel",
          "ClapPreTrainedModel",
          "ClapTextModel",
          "ClapTextModelWithProjection",
          "ClapAudioModel",
          "ClapAudioModelWithProjection",
      ]
      UpperCamelCase      					=["ClapFeatureExtractor"]

if TYPE_CHECKING:
      from .configuration_clap import (
          CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
          ClapAudioConfig,
          ClapConfig,
          ClapTextConfig,
      )
      from .processing_clap import ClapProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_clap import ClapFeatureExtractor
            from .modeling_clap import (
                CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
                ClapAudioModel,
                ClapAudioModelWithProjection,
                ClapModel,
                ClapPreTrainedModel,
                ClapTextModel,
                ClapTextModelWithProjection,
            )


else:
      import sys

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






