def setup(self):
# Shape of the tensor
shape = (2, 3, 4, 5)
# Number of elements in the tensor
num_of_elements = np.prod(shape)
# Creating a numpy tensor with the desired shape and size
tensor = np.arange(num_of_elements).reshape(shape)
# Declaring in1 as input tensor
in1 = self.declare_input('in1', val=tensor)
# Computing the 6-norm on in1 without specifying an axis
self.register_output('axis_free_pnorm', ot.pnorm(in1, pnorm_type=3))
def setup(self):
# Shape of the tensor
shape = (2, 3, 4, 5)
# Number of elements in the tensor
num_of_elements = np.prod(shape)
# Creating a numpy tensor with the desired shape and size
tensor = np.arange(num_of_elements).reshape(shape)
# Declaring in1 as input tensor
in1 = self.declare_input('in1', val=tensor)
# Computing the 6-norm of in1 over the specified axes.
self.register_output('axiswise_pnorm',
ot.pnorm(in1, axis=(1, 3), pnorm_type=6))