def _init_impl(self, scale, out):
if self.rnd_type == 'uniform':
random.uniform(-scale, scale, out=out)
elif self.rnd_type == 'gaussian':
random.normal(0, scale, out=out)
else:
raise ValueError('Unknown random type')
def _init_weight(self, _, arr):
shape = arr.shape
hw_scale = 1.
if len(shape) > 2:
hw_scale = np.prod(shape[2:])
fan_in, fan_out = shape[1] * hw_scale, shape[0] * hw_scale
w_bound = np.sqrt(6. / (fan_in + fan_out))
random.uniform(-w_bound, w_bound, out=arr)
def _init_weight(self, name, arr):
if name in self._kwargs.keys():
init_params = self._kwargs[name]
for (k, v) in init_params.items():
if k.lower() == "normal":
random.normal(0, v, out=arr)
elif k.lower() == "uniform":
random.uniform(-v, v, out=arr)
elif k.lower() == "orthogonal":
raise NotImplementedError("Not support at the moment")
elif k.lower() == "xavier":
xa = Xavier(v[0], v[1], v[2])
xa(name, arr)
else:
raise NotImplementedError("Not support")
def _init_weight(self, name, arr):
if name in self._kwargs.keys():
init_params = self._kwargs[name]
for (k, v) in init_params.items():
if k.lower() == "normal":
random.normal(0, v, out=arr)
elif k.lower() == "uniform":
random.uniform(-v, v, out=arr)
elif k.lower() == "orthogonal":
raise NotImplementedError("Not support at the moment")
elif k.lower() == "xavier":
xa = Xavier(v[0], v[1], v[2])
xa(name, arr)
else:
raise NotImplementedError("Not support")
def _init_weight(self, _, arr):
random.uniform(0, self.scale, out=arr)
