Inception Resnet A

incresA.py

def incresA(x,scale,name=None):
    pad = 'same'
    branch0 = conv2d(x,32,1,1,pad,True,name=name+'b0')
    branch1 = conv2d(x,32,1,1,pad,True,name=name+'b1_1')
    branch1 = conv2d(branch1,32,3,1,pad,True,name=name+'b1_2')
    branch2 = conv2d(x,32,1,1,pad,True,name=name+'b2_1')
    branch2 = conv2d(branch2,48,3,1,pad,True,name=name+'b2_2')
    branch2 = conv2d(branch2,64,3,1,pad,True,name=name+'b2_3')
    branches = [branch0,branch1,branch2]
    mixed = Concatenate(axis=3, name=name + '_concat')(branches)
    filt_exp_1x1 = conv2d(mixed,384,1,1,pad,False,name=name+'filt_exp_1x1')
    final_lay = Lambda(lambda inputs, scale: inputs[0] + inputs[1] * scale,
                      output_shape=backend.int_shape(x)[1:],
                      arguments={'scale': scale},
                      name=name+'act_scaling')([x, filt_exp_1x1])
    return final_lay