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, })