I am trying to train an LSTM model using Keras functional API. My training data is of shape:
>>> data.shape() (100000,variable_sequence_lengths,295)
where 100000 corresponds to the number of instances (the whole number of sequences) and 295 denotes the number of features in each element of a given sequence.
I am getting errors regarding the shape of the input data. How to define the shape of the data in the input layer and the subsequent one (LSTM) considering variable sequence lengths?
from keras.layers import Input, Dense, concatenate, LSTM from keras.models import Model import numpy as np inputs = Input(shape=(x,y,z)) x=LSTM(128, return_sequences=True, input_shape=(a,b,c))(inputs) ....
What values should x, y, z and a, b, c take?