Adds support for string and binary data processing in Colocated Python.

PiperOrigin-RevId: 727048049

tests/colocated_python_test.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import base64
+import struct
 import tempfile
 import threading
 import time
@@ -23,6 +25,7 @@ from absl.testing import parameterized
 import jax
 from jax._src import config
 from jax._src import test_util as jtu
+from jax._src.lib import xla_extension_version
 from jax.experimental import colocated_python
 from jax.experimental.colocated_python import serialization
 from jax.extend.ifrt_programs import ifrt_programs
@@ -37,6 +40,7 @@ try:
 except (ModuleNotFoundError, ImportError):
   raise unittest.SkipTest("tests depend on cloudpickle library")
 
+
 def _colocated_cpu_devices(
     devices: Sequence[jax.Device],
 ) -> Sequence[jax.Device]:
@@ -378,6 +382,99 @@ class ColocatedPythonTest(jtu.JaxTestCase):
       if "_testing_global_state" in colocated_python.__dict__:
         del colocated_python._testing_global_state
 
+  def testStringProcessing(self):
+    if xla_extension_version < 315:
+      self.skipTest(
+          "String support for colocated Python requires xla_extension_version"
+          " >= 315"
+      )
+    cpu_devices = _colocated_cpu_devices(jax.local_devices())
+    if len(cpu_devices) < 2:
+      self.skipTest(f"Need at least two CPU devices, got: {len(cpu_devices)}")
+
+    @colocated_python.colocated_python
+    def f(x):
+      out_arrays = []
+      upper_caser = np.vectorize(
+          lambda x: x.upper(), otypes=[np.dtypes.StringDType()]
+      )
+      for shard in x.addressable_shards:
+        np_array = jax.device_get(shard.data)
+        out_np_array = upper_caser(np_array)
+        out_arrays.append(jax.device_put(out_np_array, device=shard.device))
+      return jax.make_array_from_single_device_arrays(
+          sharding=x.sharding, shape=x.shape, arrays=out_arrays
+      )
+
+    # Make a string array.
+    numpy_string_array = np.array(
+        [["abcd", "efgh"], ["ijkl", "mnop"]], dtype=np.dtypes.StringDType()  # type: ignore
+    )
+    mesh = jax.sharding.Mesh(
+        np.array(cpu_devices[:2]).reshape((2, 1)), ("x", "y")
+    )
+    sharding = jax.sharding.NamedSharding(mesh, jax.sharding.PartitionSpec("x"))
+    x = jax.device_put(numpy_string_array, device=sharding)
+
+    # Run the colocated Python function with the string array as input.
+    out = f(x)
+    out = jax.device_get(out)
+
+    # Should have gotten the strings with all upper case letters.
+    np.testing.assert_equal(
+        out,
+        np.array(
+            [["ABCD", "EFGH"], ["IJKL", "MNOP"]], dtype=np.dtypes.StringDType()
+        ),
+    )
+
+  def testBinaryDataProcessing(self):
+    if xla_extension_version < 315:
+      self.skipTest(
+          "String support for colocated Python requires xla_extension_version"
+          " >= 315"
+      )
+    cpu_devices = _colocated_cpu_devices(jax.local_devices())
+    if len(cpu_devices) < 1:
+      self.skipTest("Need at least one CPU devices")
+
+    @colocated_python.colocated_python
+    def f(x):
+      out_arrays = []
+      for shard in x.addressable_shards:
+        np_array = jax.device_get(shard.data)
+        input_ints = struct.unpack(
+            "<ii", base64.b64decode(np_array[0].encode("ascii"))
+        )
+        output_string = base64.b64encode(
+            struct.pack("<ii", input_ints[0] + 1, input_ints[1] + 1)
+        ).decode("ascii")
+        out_np_array = np.array([output_string], dtype=np.dtypes.StringDType())
+        out_arrays.append(jax.device_put(out_np_array, device=shard.device))
+
+      out = jax.make_array_from_single_device_arrays(
+          sharding=x.sharding, shape=x.shape, arrays=out_arrays
+      )
+      return out
+
+    # Make the input array with the binary data that packs two integers as ascii
+    # string.
+    input_string = base64.b64encode(struct.pack("<ii", 1001, 1002)).decode(
+        "ascii"
+    )
+    numpy_string_array = np.array([input_string], dtype=np.dtypes.StringDType())
+    sharding = jax.sharding.SingleDeviceSharding(cpu_devices[0])
+    x = jax.device_put(numpy_string_array, device=sharding)
+
+    out = f(x)
+    out = jax.device_get(out)
+
+    # Should have gotten the binary data with the incremented integers as a
+    # ascii string.
+    out_ints = struct.unpack("<ii", base64.b64decode(out[0].encode("ascii")))
+    self.assertEqual(out_ints[0], 1002)
+    self.assertEqual(out_ints[1], 1003)
+
 
 if __name__ == "__main__":
   absltest.main(testLoader=jtu.JaxTestLoader())