def forward(self, input_batch):
# Create data batch for the RNN
out = input_batch.view(input_batch.size(0), input_batch.size(1),
input_batch.size(2) * input_batch.size(3))
out = self.relu(self.first_layer(out))
out = out + self.relu(self.second_layer(out))
out = out + self.relu(self.third_layer(out))
out = self.relu(self.fourth_layer(out))
# RNN consumes batch backwards to create z0
reversed_mini_batch = utils.reverse_sequences_torch(out)
h0 = torch.zeros(self.rnn_layers,
input_batch.size(0),
self.rnn.hidden_size,
device=input_batch.device)
rnn_output, _ = self.rnn(reversed_mini_batch, h0)
rnn_output = rnn_output[:, -1]
z_0_loc = self.rnn_to_z0_loc(rnn_output)
z_0_log_var = self.rnn_to_z0_log_var(rnn_output)
# LSTM creates params
lstm_all_output, _ = self.lstm(out)
lstm_output = lstm_all_output[:, -1]
latent_params_loc = self.lstm_to_latent_loc(lstm_output)
latent_params_log_var = self.lstm_to_latent_log_var(lstm_output)
return z_0_loc, z_0_log_var, latent_params_loc, latent_params_log_var
def forward(self, mini_batch):
mini_batch = self.input_to_rnn_net(mini_batch)
reversed_mini_batch = utils.reverse_sequences_torch(mini_batch)
rnn_output, _ = self.rnn(reversed_mini_batch)
rnn_output = rnn_output[:, -1]
z_0_loc = self.rnn_to_latent_loc(rnn_output)
z_0_log_var = self.rnn_to_latent_log_var(rnn_output)
return z_0_loc, z_0_log_var
def forward(self, mini_batch):
mini_batch = mini_batch.view(mini_batch.size(0), mini_batch.size(1), mini_batch.size(2) * mini_batch.size(3))
mini_batch = self.relu(self.first_layer(mini_batch))
mini_batch = mini_batch + self.relu(self.second_layer(mini_batch))
mini_batch = mini_batch + self.relu(self.third_layer(mini_batch))
mini_batch = self.relu(self.fourth_layer(mini_batch))
reversed_mini_batch = utils.reverse_sequences_torch(mini_batch)
rnn_output, _ = self.rnn(reversed_mini_batch)
rnn_output = rnn_output[:, -1]
z_0_loc = self.rnn_to_latent_loc(rnn_output)
z_0_log_var = self.rnn_to_latent_log_var(rnn_output)
return z_0_loc, z_0_log_var
def forward(self, mini_batch):
mini_batch = self.input_to_rnn_net(mini_batch)
reversed_mini_batch = utils.reverse_sequences_torch(mini_batch)
rnn_output, _ = self.rnn(reversed_mini_batch)
rnn_output = rnn_output[:, -1]
latent_z_0_loc = self.rnn_to_latent_loc(rnn_output)
latent_z_0_log_var = self.rnn_to_latent_log_var(rnn_output)
lstm_all_output, _ = self.lstm(mini_batch)
lstm_output = lstm_all_output[:, -1]
latent_params_loc = self.lstm_to_latent_loc(lstm_output)
latent_params_log_var = self.lstm_to_latent_log_var(lstm_output)
return latent_z_0_loc, latent_z_0_log_var, latent_params_loc, latent_params_log_var