// Allocate a buffer of 4K int values
IntDataBuffer bufferA = DataBuffers.ofInts(4096L);
assertEquals(4096L, bufferA.size());

// Write an int array at the beginning of the buffer
bufferA.write(new int[] { 1, 2, 3 });
assertEquals(3, bufferA.getInt(2));

// Slice buffer after its first value
IntDataBuffer bufferB = bufferA.offset(1);
assertEquals(4095L, bufferB.size());
assertEquals(2, bufferB.getInt(0));

// Resize a buffer to 10 elements
IntDataBuffer bufferC = bufferB.narrow(10);
assertEquals(10L, bufferB.size());
assertEquals(2, bufferB.getInt(0));

// Allocating a 3D matrix of 2x3x2
IntNdArray matrix3d = NdArrays.ofInts(Shape.of(2, 3, 2));
assertEquals(3, matrix3d.rank());

// Initializing 3D matrix data with vectors from the first dimension (index 0)
matrix3d.elements(0).forEach(matrix -> {
    assertEquals(2, matrix.rank());
    assertEquals(Shape.of(3, 2), matrix.shape());
    matrix
      .set(NdArrays.vectorOf(1, 2), 0)
      .set(NdArrays.vectorOf(3, 4), 1)
      .set(NdArrays.vectorOf(5, 6), 2);
});

// Visit all scalars of 3D matrix, printing their coordinates and value
matrix3d.scalars().forEachIdx((coords, scalar) ->
    System.out.println("Scalar at " + Arrays.toString(coords) + " has value " + scalar.getInt())
);

// Retrieving the second vector of the first matrix
IntNdArray vector = matrix3d.get(0, 1);
assertEquals(1, vector.rank());

// Rewriting the values of the vector using a primitive array
vector.copyFrom(DataBuffers.of(new int[] { 7, 8 }));
assertEquals(7, matrix3d.getInt(0, 1, 0));
assertEquals(8, matrix3d.getInt(0, 1, 1));

// Slicing the 3D matrix so we only keep the second element of the second dimension
IntNdArray slice = matrix3d.slice(all(), at(1));
assertEquals(2, slice.rank());
assertEquals(Shape.of(2, 2), slice.shape());
assertEquals(7, slice.getInt(0, 0));  // (0, 1, 0) in the original matrix
assertEquals(3, slice.getInt(1, 0));  // (1, 1, 0) in the original matrix

// Allocate a tensor of 32-bits integer of the shape (2, 3, 2)
TInt32 tensor = TInt32.ofShape(2, 3, 2);

// Access tensor memory directly
assertEquals(3, tensor.rank());
assertEquals(12, tensor.size());

try (EagerSession session = EagerSession.create()) {
  Ops tf = Ops.create(session);

  // Initialize tensor memory with zeros and take a snapshot
  tensor.scalars().forEach(scalar -> scalar.setInt(0));
  Constant<T> x = tf.constant(tensor);

  // Initialize the same tensor memory with ones and take a snapshot
  tensor.scalars().forEach(scalar -> scalar.setInt(1));
  Constant<T> y = tf.constant(tensor);

  // Subtract y from x and validate the result
  Sub<T> sub = tf.math.sub(x, y);
  sub.asTensor().scalars().forEach(scalar ->
      assertEquals(-1, scalar.getInt())
  );
}