def _get_J_err_var_()

in theseus/embodied/motionmodel/quasi_static_pushing_planar.py [0:0]

• 9 lines of code
• 5 McCabe index (conditional complexity)

        def _get_J_err_var_(J_D_var_, J_V_var_, J_Vp_var_):
            # After einsum, each result is a tensor with size:
            #   batch_size x se2_dim x 3 x 1
            # so that after all terms are summed,
            # J_err_var_[b, d] is a (3, 1) vector derivative of
            # the b-th batch element of the 3-D error wrt to the
            # d-th dimension of the optimization variable.
            # At return, we squeeze the trailing dimension, and permute, so that the
            # output has shape (batch_size, 3, se2_dim), which is the expected jacobian
            # shape.
            J_err_var_ = torch.zeros_like(J_V_o1)
            if J_D_var_ is not None:
                J_err_var_ += torch.einsum(sum_str, J_D_var_, V_exp)
            if J_V_var_ is not None:
                J_err_var_ += torch.einsum(sum_str, D_exp, J_V_var_)
            if J_Vp_var_ is not None:
                J_err_var_ += -J_Vp_var_
            return J_err_var_.squeeze(3).permute(0, 2, 1)