Elementwise Minimum

This is an example of computing the elementwise minimum from multiple input tensors of the same size.

from csdl_om import Simulatorfrom csdl import Modelimport csdlimport numpy as np

class ExampleElementwise(Model):
    def define(self):
        m = 2        n = 3        # Shape of the three tensors is (2,3)        shape = (m, n)
        # Creating the values for two tensors        val1 = np.array([[1, 5, -8], [10, -3, -5]])        val2 = np.array([[2, 6, 9], [-1, 2, 4]])
        # Declaring the two input tensors        tensor1 = self.declare_variable('tensor1', val=val1)        tensor2 = self.declare_variable('tensor2', val=val2)
        # Creating the output for matrix multiplication        ma = self.register_output('ElementwiseMin',                                  csdl.min(tensor1, tensor2))        assert ma.shape == (2, 3)

sim = Simulator(ExampleElementwise())sim.run()
print('tensor1', sim['tensor1'].shape)print(sim['tensor1'])print('tensor2', sim['tensor2'].shape)print(sim['tensor2'])print('ElementwiseMin', sim['ElementwiseMin'].shape)print(sim['ElementwiseMin'])

[[ 1.  5. -8.] [10. -3. -5.]]tensor2 (2, 3)[[ 2.  6.  9.] [-1.  2.  4.]]ElementwiseMin (2, 3)[[ 1.  5. -8.] [-1. -3. -5.]]