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// Compute convolution along the second and third dimension.
Tensor<float, 4, DataLayout> input(3, 3, 7, 11);
Tensor<float, 2, DataLayout> kernel(2, 2);
Tensor<float, 4, DataLayout> output(3, 2, 6, 11);
input.setRandom();
kernel.setRandom();
Eigen::array<ptrdiff_t, 2> dims({1, 2});  // Specify second and third dimension for convolution.
output = input.convolve(kernel, dims);
for (int i = 0; i < 3; ++i) {
  for (int j = 0; j < 2; ++j) {
    for (int k = 0; k < 6; ++k) {
      for (int l = 0; l < 11; ++l) {
        const float result = output(i,j,k,l);
        const float expected = input(i,j+0,k+0,l) * kernel(0,0) +
                               input(i,j+1,k+0,l) * kernel(1,0) +
                               input(i,j+0,k+1,l) * kernel(0,1) +
                               input(i,j+1,k+1,l) * kernel(1,1);
        VERIFY_IS_APPROX(result, expected);
      }
    }
  }
}