Tensorflow cpp with Eigen element wise multiply

Question

I am trying to do an element wise multiply for my own op in tensorflow + Eigen. This is a simple version of what I am currently using:

// eg) temp_res_shape = [3, 8], temp_b_shape = [1, 8]
// allocate Tensorflow tensors
Tensor temp_res;
OP_REQUIRES_OK(ctx, ctx->allocate_temp(DataTypeToEnum<complex64>::v(),
                   temp_res_shape, &temp_res));
Tensor temp_a;
OP_REQUIRES_OK(ctx, ctx->allocate_temp(DataTypeToEnum<complex64>::v(),
                   temp_res_shape, &temp_a));
Tensor temp_b;
OP_REQUIRES_OK(ctx, ctx->allocate_temp(DataTypeToEnum<complex64>::v(),
                   temp_b_shape, &temp_b));
// These actually come from different places but the type/shape is right
// ie) I want to do this within Eigen::TensorMap if possible
auto mult_res = Tensor(temp_res).flat_inner_dims<complex64, 2>();
auto a_in = Tensor(temp_a).flat_inner_dims<complex64, 2>();
auto b_in = Tensor(temp_b).flat_inner_dims<complex64, 2>();
// convert to an array
auto a_data = a_in.data();
auto b_data = b_in.data();
auto res = mult_res.data();
for ( int i = 0; i < 3; i++ ) {
  for ( int j = 0; j < 8; j++ )
    res[ i*8 + j ] = a_data[ i*3 + 8 ] * b_data[j];
}

This is obviously the wrong way to do it but I couldn't get anything else working. I feel like it should be something of the form:

mult_res.device( device ) = a_in * b_in;

But that does the matrix multiply. I couldn't figure out how to convert b_in to a diagonal matrix to multiply that way either :/ I feel like this should be trivial but I can't work it out (my cpp is not great). Thanks in advance!