Medium lstm article

lstm02.py

input_size = 1    # The number of variables in your sequence data. 
n_hidden   = 100  # The number of hidden nodes in the LSTM layer.
n_layers   = 2    # The total number of LSTM layers to stack.
out_size   = 1    # The size of the output you desire from your RNN.

lstm   = nn.LSTM(input_size, n_hidden, n_layers, batch_first=True)
linear = nn.Linear(n_hidden, 1)

# Data Flow Protocol:
# 1. network input shape: (batch_size, seq_length, num_features)
# 2. LSTM output shape: (batch_size, seq_length, hidden_size)
# 3. Linear input shape:  (batch_size * seq_length, hidden_size)
# 4. Linear output: (batch_size * seq_length, out_size)

x = get_batches(data)
lstm_out, hs = lstm(x, hs)            
linear_in = lstm_out.reshape(-1, hidden_size) 
linear_out = linear(linear_in)