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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: |
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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') |
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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) | |