Inner Product between Two Tensors

This is an example of how to use the csdl inner function to compute the inner product between two tensors.

from csdl_om import Simulatorfrom csdl import Modelimport csdlimport numpy as np

class ExampleTensorTensor(Model):
    def define(self):
        m = 3        n = 4        p = 5
        # Shape of the tensors        ten_shape = (m, n, p)
        # Number of elements in the tensors        num_ten_elements = np.prod(ten_shape)
        # Values for the two tensors        ten1 = np.arange(num_ten_elements).reshape(ten_shape)        ten2 = np.arange(num_ten_elements,                         2 * num_ten_elements).reshape(ten_shape)
        # Adding tensors to csdl        ten1 = self.declare_variable('ten1', val=ten1)        ten2 = self.declare_variable('ten2', val=ten2)
        # Tensor-Tensor Inner Product specifying the first and last axes        self.register_output(            'TenTenInner',            csdl.inner(ten1, ten2, axes=([0, 2], [0, 2])),        )

sim = Simulator(ExampleTensorTensor())sim.run()
print('ten1', sim['ten1'].shape)print(sim['ten1'])print('ten2', sim['ten2'].shape)print(sim['ten2'])print('TenTenInner', sim['TenTenInner'].shape)print(sim['TenTenInner'])

[[[ 0.  1.  2.  3.  4.]  [ 5.  6.  7.  8.  9.]  [10. 11. 12. 13. 14.]  [15. 16. 17. 18. 19.]]
 [[20. 21. 22. 23. 24.]  [25. 26. 27. 28. 29.]  [30. 31. 32. 33. 34.]  [35. 36. 37. 38. 39.]]
 [[40. 41. 42. 43. 44.]  [45. 46. 47. 48. 49.]  [50. 51. 52. 53. 54.]  [55. 56. 57. 58. 59.]]]ten2 (3, 4, 5)[[[ 60.  61.  62.  63.  64.]  [ 65.  66.  67.  68.  69.]  [ 70.  71.  72.  73.  74.]  [ 75.  76.  77.  78.  79.]]
 [[ 80.  81.  82.  83.  84.]  [ 85.  86.  87.  88.  89.]  [ 90.  91.  92.  93.  94.]  [ 95.  96.  97.  98.  99.]]
 [[100. 101. 102. 103. 104.]  [105. 106. 107. 108. 109.]  [110. 111. 112. 113. 114.]  [115. 116. 117. 118. 119.]]]TenTenInner (4, 4)[[31090. 32740. 34390. 36040.] [37240. 39265. 41290. 43315.] [43390. 45790. 48190. 50590.] [49540. 52315. 55090. 57865.]]