def get_name(self):
return get_model_name({
'mdl':
'cnn2d',
'dropout':
self.dropout,
'output_dims':
self.output_dims,
'cnn_features':
'.'.join([str(cnnf) for cnnf in self.cnn_features]),
})
def get_name(self):
encoder = self.autoencoder['encoder']
decoder = self.autoencoder['decoder']
return get_model_name({
'mdl':
f'ParallelRNN',
'input_dims':
f'{self.input_dims}',
'enc_emb':
get_enc_emb_str(encoder, self.band_names),
'dec_emb':
get_enc_emb_str(decoder, self.band_names),
'cell':
f'{self.rnn_cell_name}',
})
def get_name(self):
encoder = self.autoencoder['encoder']
decoder = self.autoencoder['decoder']
return get_model_name({
'mdl':
f'SerialTimeModAttn',
'input_dims':
f'{self.input_dims}',
'm':
self.mdl_kwargs['te_features'],
'kernel_size':
self.mdl_kwargs['kernel_size'],
'heads':
self.mdl_kwargs['heads'],
'fourier_dims':
self.mdl_kwargs['fourier_dims'],
'time_noise_window':
self.mdl_kwargs['time_noise_window'],
'enc_emb':
get_enc_emb_str(encoder, self.band_names),
'dec_emb':
get_enc_emb_str(decoder, self.band_names),
})
def get_name(self):
return get_model_name({
'mdl': 'mlp',
'dropout': self.dropout,
'output_dims': self.output_dims,
})