# CNN.Dense_NN(X_dense, y, epochs=100, name='Dense-6-sft', no_GPU=4,
# batch_size=10)
# sft = np.abs(np.load('sft50.npy'))
# X_1D = reshape_1D_conv(sft)
# CNN.CNN1D(X_1D, y, epochs=100, name='sft50-1D', no_GPU=4)
X_2D = np.abs(np.load('wave_2d_10_7:21.npy'))
print(X_2D.shape)
model = CNN.CNN2D(X_2D,
y,
epochs=100,
name='wave_2d_5',
no_GPU=4,
shuffle=True,
optimizer='adam',
batch_size=1,
loss='binary_crossentropy',
metrics=['accuracy'],
test_split_size=0.1)
# sft = np.abs(np.load('sft100.npy'))
# X_1D = reshape_1D_conv(sft)
# CNN.CNN1D(X_1D, y, epochs=50, name='sft100', no_GPU=4)
# X_2D = reshape_2D_conv(sft)
# CNN.CNN2D(X_2D, y, epochs=25, name='sft100', no_GPU=4)
# sft = np.abs(np.load('sft150.npy'))
# X_1D = reshape_1D_conv(sft)
# CNN.CNN1D(X_1D, y, epochs=50, name='sft150', no_GPU=4)
