Create initial LWE-to-jaxiteword conversion pass

PiperOrigin-RevId: 727611223

BUILD

@@ -178,6 +178,22 @@ tpu_test(
     ],
 )
 
+tpu_test(
+    name = "add_test",
+    size = "large",
+    timeout = "eternal",
+    srcs = ["jaxite_word/add_test.py"],
+    shard_count = 3,
+    deps = [
+        ":jaxite",
+        "@com_google_absl_py//absl/testing:absltest",
+        "@com_google_absl_py//absl/testing:parameterized",
+        "@jaxite_deps_jax//:pkg",
+        "@jaxite_deps_jaxlib//:pkg",
+        "@jaxite_deps_numpy//:pkg",
+    ],
+)
+
 cpu_gpu_tpu_test(
     name = "decomposition_test",
     size = "small",

jaxite_word/add.py

@@ -0,0 +1,58 @@
+"""TPU kernels for Evaluation of the CKKS algorithm."""
+
+import jax
+import jax.numpy as jnp
+
+
+def jax_add(value_a: jax.Array, value_b: jax.Array, modulus_list: jax.Array):
+  """This function processes all degree of the two input polynomials in parallel using multi-trheading.
+
+  Assuming the input data type is jax array.
+
+  Args:
+    value_a: the first operand of the addition.
+    value_b: the second operand of the addition.
+    modulus_list: the list of moduli for each degree.
+
+  Returns:
+    The result of the addition.
+  """
+  num_elements, _, degree = value_a.shape
+  modulus_broadcast = jnp.tile(
+      modulus_list[None, :, None], (num_elements, 1, degree)
+  )
+  result = value_a + value_b
+  return jnp.where(
+      result > modulus_broadcast, result - modulus_broadcast, result
+  )  # jnp.mod(value_a + value_b, modulus_broadcast)
+
+
+def vmap_add(
+    value_a: jax.Array, value_b: jax.Array, modulus_list: jax.Array
+):
+  """This function processes all degree of the two input polynomials in SIMD using jax.vmap.
+
+  Assuming the input data type is jax array.
+
+  Args:
+    value_a: the first operand of the addition.
+    value_b: the second operand of the addition.
+    modulus_list: the list of moduli for each degree.
+
+  Returns:
+    The result of the addition.
+  """
+  num_elements, num_towers, degree = value_a.shape
+  #ToDo: expand api into four dimensions array with num_ciphertexts, num_towers, degree, num_elements
+  modulus_broadcast = jnp.tile(
+      modulus_list[None, :, None], (num_elements, 1, degree)
+  )
+
+  def chunk_wise_add(value_a, value_b):
+    return value_a + value_b
+
+  def chunk_wise_subtract(value_a, value_b):
+    return jnp.where(value_a > value_b, value_a - value_b, value_a)
+
+  result = jax.vmap(chunk_wise_add)(value_a, value_b)
+  return jax.vmap(chunk_wise_subtract)(result, modulus_broadcast)

jaxite_word/add_test.py

@@ -0,0 +1,108 @@
+"""A module for operations on test CKKS evaluation kernels including.
+
+- ModAdd
+- HEAdd
+- HESub
+- HEMul
+- HERotate
+"""
+
+from concurrent import futures
+from typing import Any, Callable
+
+import jax
+import jax.numpy as jnp
+from jaxite.jaxite_word import add
+
+from absl.testing import absltest
+from absl.testing import parameterized
+
+
+ProcessPoolExecutor = futures.ProcessPoolExecutor
+
+jax.config.update("jax_enable_x64", True)
+jax.config.update("jax_traceback_filtering", "off")
+
+
+class CKKSEvalKernelsTest(parameterized.TestCase):
+  """A base class for running bootstrap tests."""
+
+  def __init__(self, *args, **kwargs):
+    super(CKKSEvalKernelsTest, self).__init__(*args, **kwargs)
+    self.debug = False  # dsiable it from printing the test input values
+    self.modulus_element_0_tower_0 = 1152921504606748673
+    self.modulus_element_0_tower_1 = 268664833
+    self.modulus_element_0_tower_2 = 557057
+    self.random_key = jax.random.key(0)
+
+  def random(self, shape, modulus_list, dtype=jnp.int32):
+    assert len(modulus_list) == shape[1]
+
+    return jnp.concatenate(
+        [
+            jax.random.randint(
+                self.random_key,
+                shape=(shape[0], 1, shape[2]),
+                minval=0,
+                maxval=bound,
+                dtype=dtype,
+            )
+            for bound in modulus_list
+        ],
+        axis=1,
+    )
+
+  @parameterized.named_parameters(
+      dict(
+          testcase_name="jax_add",
+          test_target=add.jax_add,
+          modulus_list=[1152921504606748673, 268664833, 557057],
+          shape=(2, 3, 16384),  # number of elements, number of towers, degree
+      ),
+      dict(
+          testcase_name="vmap_add",
+          test_target=add.vmap_add,
+          modulus_list=[1152921504606748673, 268664833, 557057],
+          shape=(2, 3, 16384),  # number of elements, number of towers, degree
+      ),
+  )
+  def test_add(
+      self,
+      test_target: Callable[[Any, Any, Any], Any],
+      modulus_list=jax.Array,
+      shape=tuple[int, int, int],
+  ):
+    """This function tests the add function using Python native integer data type with arbitrary precision.
+
+    This test finishes in 1.05 second.
+
+    Args:
+      test_target: The function to test.
+      modulus_list: A jax.Array of integers.
+      shape: A tuple of integers representing the shape of the input arrays.
+    """
+    # Only test a single element to save comparison time,
+    # Correctness-wise, it's sufficient for add.
+    value_a = self.random(shape, modulus_list, dtype=jnp.uint64)
+    value_b = self.random(shape, modulus_list, dtype=jnp.uint64)
+    assert value_a.shape == shape
+    assert value_b.shape == shape
+    result_a_plus_b = []
+    for element_id in range(value_a.shape[0]):
+      result_a_plus_b_one_element = []
+      for tower_id in range(value_a.shape[1]):
+        add_res = int(value_b[element_id, tower_id, 0]) + int(
+            value_a[element_id, tower_id, 0]
+        )
+        if add_res > modulus_list[tower_id]:
+          add_res = add_res - modulus_list[tower_id]
+        result_a_plus_b_one_element.append(add_res)
+      result_a_plus_b.append(result_a_plus_b_one_element)
+    result_a_plus_b = jnp.array(result_a_plus_b, dtype=jnp.uint64)
+    modulus_list = jnp.array(modulus_list, dtype=jnp.uint64)
+    result = test_target(value_a, value_b, modulus_list)
+    self.assertEqual(result[:, :, 0].all(), result_a_plus_b.all())
+
+
+if __name__ == "__main__":
+  absltest.main()