trainable_yamnet.py
def yamnet_model(feature_params):
    """Creates the yamnet model, without seperating into frames. 
    Takes as input one .wav file, performs feature extraction and
    produces a spectrogram which is the input to yamnet  """
    
    waveform = layers.Input((None,))
    _,patches = features_lib.waveform_to_log_mel_spectrogram_patches(
    tf.squeeze(waveform, axis=0), feature_params)
    predictions,_ = yamnet(patches,feature_params) #yamnet returns predictions and embedings
    
    single_spec_model = Model(name='yamnet_frames', 
                       inputs=waveform, outputs=[predictions])
    return single_spec_model
Creates the yamnet model, without seperating into frames. 
    Takes as input one .wav file, performs feature extraction and
    produces a spectrogram which is the input to yamnet  
Creates the yamnet model, without seperating into frames.
Takes as input one .wav file, performs feature extraction and
produces a spectrogram which is the input to yamnet
Creates the yamnet model without seperating into frames . Takes as input one . wav file performs feature extraction and produces a spectrogram which is the input to yamnet
def yamnet_model(feature_params):
    waveform = layers.Input((None,))
    _,patches = features_lib.waveform_to_log_mel_spectrogram_patches(
    tf.squeeze(waveform, axis=0), feature_params)
    predictions,_ = yamnet(patches,feature_params) 
    single_spec_model = Model(name='yamnet_frames', 
                       inputs=waveform, outputs=[predictions])
    return single_spec_model
def yamnet_model ( feature_params ) : waveform = layers . Input ( ( None , ) ) _ , patches = features_lib . waveform_to_log_mel_spectrogram_patches ( tf . squeeze ( waveform , axis = 0 ) , feature_params ) predictions , _ = yamnet ( patches , feature_params ) single_spec_model = Model ( name = 'yamnet_frames' , inputs = waveform , outputs = [ predictions ] ) return single_spec_model
Creates the yamnet model, without seperating into frames.
Creates the yamnet model without seperating into frames .
"""Creates the yamnet model, without seperating into frames. 
    Takes as input one .wav file, performs feature extraction and
    produces a spectrogram which is the input to yamnet  """ #yamnet returns predictions and embedings
feature_params