def fprop_relu(self, layer, x, slope):
if layer is None:
layer = layer_mkl.ReluLayerMKL()
if not hasattr(x, 'shape5D'):
return self.maximum(x, 0) + slope * self.minimum(0, x)
if slope != 0:
self.convert(x)
x.clean_mkl()
return self.maximum(x, 0) + slope * self.minimum(0, x)
if x.shape5D is not None:
C, D, H, W, N = x.shape5D
else:
C, N = x._tensor.shape
D, H, W = 1, 1, 1
x.shape5D = C, D, H, W, N
layer.shape5D = C, D, H, W, N
primitives = c_longlong(layer.dnnPrimitives.ctypes.data)
if x.primitive[3] == 0:
layer.inputMKL = False
self.mklEngine.Relu_f(x.get_prim(), primitives, layer.initOk_f, N, C,
H, W)
layer.initOk_f = 1
return x
def bprop_relu(self, layer, x, error, deltas, slope):
if layer is None:
layer = layer_mkl.ReluLayerMKL()
if slope != 0 or error is None:
if error is not None:
self.convert(error)
error.clean_mkl()
return self.greater(x, 0) + slope * self.less(x, 0)
# to be moved to C code
if not layer.inputMKL:
self.convert(error)
error.clean_mkl()
primitives = c_longlong(layer.dnnPrimitives.ctypes.data)
self.mklEngine.Relu_b(x.get_prim(), error.get_prim(), primitives, layer.initOk_b)
layer.initOk_b = 1
deltas.set_mkl(error)
deltas.shape5D = layer.shape5D
if deltas.primitive[3] == 0:
deltas[:] = error
def relu_layer(self):
return layer_mkl.ReluLayerMKL()
