Fixing 'ValueError: Input 0 of layer "lstm_2" is incompatible with the layer: expected ndim=3, found ndim=2.' Error in Keras LSTM Model

The error message 'ValueError: Input 0 of layer "lstm_2" is incompatible with the layer: expected ndim=3, found ndim=2.' indicates that the input shape of the LSTM layer doesn't match the actual shape of the data being provided. The LSTM layer anticipates a 3-dimensional input tensor, but the input tensor being fed has only two dimensions. This discrepancy arises because the data is reshaped incorrectly before being passed to the LSTM layer.

In the provided code, the input data (sequences converted to numerical representations) is reshaped using X_train.reshape((-1, 1000, 1)) and X_test.reshape((-1, 1000, 1)). While this adds an extra dimension to the data, it doesn't align with the LSTM layer's expectations. The LSTM layer expects a 3D tensor in the form (batch_size, timesteps, input_dim). In this context, input_dim should be 1 because each timestep represents a single nucleotide. The code should reshape the input data to preserve the number of timesteps (1000) and introduce a new dimension for the input channels. This can be achieved by using X_train.reshape((-1, 1000, 1)) and X_test.reshape((-1, 1000, 1)), resulting in shapes of (batch_size, 1000, 1). The corrected code snippet is:

seqs, labels = read_fasta('CP015726.fasta')
seq_num = seq_to_num(seqs)
encoded_labels = encode_labels(labels)
X_train, X_test, y_train, y_test = train_test_split(seq_num, encoded_labels, test_size=0.2, random_state=42)
model = create_model()
history = model.fit(X_train.reshape((-1, 1000, 1)), y_train, epochs=10, batch_size=32, validation_split=0.2)
score = model.evaluate(X_test.reshape((-1, 1000, 1)), y_test, verbose=0)
print('Test loss:', score[0])
print('Test accuracy:', score[1])

This code modification ensures that the input data has the correct shape, allowing the LSTM layer to process it effectively. By correctly reshaping the input data, the model should train and evaluate without encountering the 'ValueError: Input 0 of layer "lstm_2" is incompatible with the layer: expected ndim=3, found ndim=2.' error.