Seanny123

from keras.layers import Masking, Dense
from keras.layers.recurrent import LSTM
from keras.models import Sequential

import numpy as np

np.set_printoptions(precision=4)
np.random.seed(1)

Seanny123

from keras.layers import Input, Masking, LSTM, Dense
from keras.models import Model
import numpy as np

# Case1: model with return_sequences=True (output_shape = (1,10,1) )
##############################################################
input1 = Input(batch_shape=(1, 10, 16))
mask1 = Masking(mask_value=2.)(input1)
lstm1 = LSTM(16, return_sequences=True)(mask1)
dense_layer = Dense(1, activation='sigmoid')

Seanny123

import numpy as np

r = np.arange(1.0, 11.0, 0.1)

n = len(r)**3
pts = np.empty((n, 3))
i = 0
for x in r:
    for y in r:
        for z in r: