def call(self, x): real = utils.GetReal()(x) imag = utils.GetImag()(x) abs1 = K.relu(utils.GetAbs()(x)) abs2 = K.relu(utils.GetAbs()(x) - self._b) real = real * abs2 / (abs1+0.0000001) imag = imag * abs2 / (abs1+0.0000001) merged = Concatenate()([real, imag]) return merged
def network_200_modrelu_short_shared(data_input, classes_num=10, weight_decay = 1e-4):
'''
Network that gets 99% acc on 20 MHz WiFi-2 data without channel
'''
convArgs = dict(use_bias=True,
kernel_regularizer=l2(weight_decay),
spectral_parametrization=False,
kernel_initializer='complex_independent')
model_name = "MODEL:"
########################
filters = 100
k_size = 200
strides = 100
o = ComplexConv1D(filters=filters,
kernel_size=[k_size],
strides=strides,
padding='valid',
activation=None,
name="ComplexConv1", **convArgs)(data_input)
model_name = model_name + "-" + str(filters) + "C" + str(k_size) + "x" + str(strides)
########################
########################
o = Modrelu(name="ModRelu1")(o)
model_name = model_name + "-ModReLU"
########################
########################
filters = 100
k_size = 10
strides = 1
o = ComplexConv1D(filters=filters,
kernel_size=[k_size],
strides=strides,
padding='valid',
activation=None,
name="ComplexConv2", **convArgs)(o)
model_name = model_name + "-" + str(filters) + "C" + str(k_size) + "x" + str(strides)
#########################
########################
o = Modrelu(name="ModRelu2")(o)
model_name = model_name + "-ModReLU"
########################
########################
o = utils.GetAbs(name="Abs")(o)
model_name = model_name + "-Abs"
########################
########################
neuron_num = 100
shared_dense = Dense(neuron_num,
activation='relu',
kernel_initializer="he_normal",
kernel_regularizer=l2(weight_decay),
name="Shared_Dense1")
model_name = model_name + "-" + str(neuron_num) + "shared_D"
########################
o = shared_dense(o)
########################
neuron_num = 100
shared_dense2 = Dense(neuron_num,
activation='relu',
kernel_initializer="he_normal",
kernel_regularizer=l2(weight_decay),
name="Shared_Dense2")
model_name = model_name + "-" + str(neuron_num) + "shared_D"
########################
o = shared_dense2(o)
########################
o = GlobalAveragePooling1D(name="Avg")(o)
model_name = model_name + "-Avg"
########################
x = Dense(classes_num,
activation='softmax',
kernel_initializer="he_normal",
name="Dense3")(o)
return x , model_name