def default_recurisive_init(custom_cell):
"""default_recurisive_init"""
for _, cell in custom_cell.cells_and_names():
if isinstance(cell, nn.Conv2d):
cell.weight.set_data(init.initializer(KaimingUniform(a=math.sqrt(5)),
cell.weight.shape,
cell.weight.dtype))
if cell.bias is not None:
fan_in, _ = _calculate_in_and_out(cell.weight)
bound = 1 / math.sqrt(fan_in)
cell.bias.set_data(init.initializer(init.Uniform(bound),
cell.bias.shape,
cell.bias.dtype))
elif isinstance(cell, nn.Dense):
cell.weight.set_data(init.initializer(KaimingUniform(a=math.sqrt(5)),
cell.weight.shape,
cell.weight.dtype))
if cell.bias is not None:
fan_in, _ = _calculate_in_and_out(cell.weight)
bound = 1 / math.sqrt(fan_in)
cell.bias.set_data(init.initializer(init.Uniform(bound),
cell.bias.shape,
cell.bias.dtype))
elif isinstance(cell, (nn.BatchNorm2d, nn.BatchNorm1d)):
pass
def __init__(self):
super(ParameterNet, self).__init__()
self.para_xavier_uniform = Parameter(init.initializer('xavier_uniform', parameter_shape), name="xavier_uniform")
self.para_he_uniform = Parameter(init.initializer('he_uniform', parameter_shape), name="he_uniform")
self.para_xavier_uniform2 = Parameter(init.initializer(init.XavierUniform(), parameter_shape), name="xavier_uniform2")
self.para_he_uniform2 = Parameter(init.initializer(init.HeUniform(), parameter_shape), name="he_uniform2")
self.para_truncated_normal = Parameter(init.initializer(init.TruncatedNormal(), parameter_shape), name="truncated_normal")
self.para_normal = Parameter(init.initializer(init.Normal(), parameter_shape), name="normal")
self.para_uniform = Parameter(init.initializer(init.Uniform(), parameter_shape), name="uniform")
def test_init_uniform():
scale = 10
tensor = init.initializer(init.Uniform(scale=scale), [5, 4], ms.float32)
_check_value(tensor, -scale, scale)
