Migrate nvtext jaccard API to pylibcudf

docs/cudf/source/user_guide/api_docs/pylibcudf/nvtext/index.rst

@@ -6,3 +6,4 @@ nvtext
 
     edit_distance
     generate_ngrams
+    jaccard

docs/cudf/source/user_guide/api_docs/pylibcudf/nvtext/jaccard.rst

@@ -0,0 +1,6 @@
+=======
+jaccard
+=======
+
+.. automodule:: pylibcudf.nvtext.jaccard
+   :members:

python/cudf/cudf/_lib/nvtext/jaccard.pyx

@@ -2,33 +2,16 @@
 
 from cudf.core.buffer import acquire_spill_lock
 
-from libcpp.memory cimport unique_ptr
-from libcpp.utility cimport move
-
-from pylibcudf.libcudf.column.column cimport column
-from pylibcudf.libcudf.column.column_view cimport column_view
-from pylibcudf.libcudf.nvtext.jaccard cimport (
-    jaccard_index as cpp_jaccard_index,
-)
-from pylibcudf.libcudf.types cimport size_type
-
 from cudf._lib.column cimport Column
 
+from pylibcudf import nvtext
+
 
 @acquire_spill_lock()
 def jaccard_index(Column input1, Column input2, int width):
-    cdef column_view c_input1 = input1.view()
-    cdef column_view c_input2 = input2.view()
-    cdef size_type c_width = width
-    cdef unique_ptr[column] c_result
-
-    with nogil:
-        c_result = move(
-            cpp_jaccard_index(
-                c_input1,
-                c_input2,
-                c_width
-            )
-        )
-
-    return Column.from_unique_ptr(move(c_result))
+    result = nvtext.jaccard.jaccard_index(
+        input1.to_pylibcudf(mode="read"),
+        input2.to_pylibcudf(mode="read"),
+        width,
+    )
+    return Column.from_pylibcudf(result)

python/pylibcudf/pylibcudf/nvtext/CMakeLists.txt

@@ -12,7 +12,7 @@
 # the License.
 # =============================================================================
 
-set(cython_sources edit_distance.pyx generate_ngrams.pyx)
+set(cython_sources edit_distance.pyx generate_ngrams.pyx jaccard.pyx)
 
 set(linked_libraries cudf::cudf)
 rapids_cython_create_modules(

python/pylibcudf/pylibcudf/nvtext/__init__.pxd

@@ -1,8 +1,9 @@
 # Copyright (c) 2024, NVIDIA CORPORATION.
 
-from . cimport edit_distance, generate_ngrams
+from . cimport edit_distance, generate_ngrams, jaccard
 
 __all__ = [
     "edit_distance",
     "generate_ngrams",
+    "jaccard",
 ]

python/pylibcudf/pylibcudf/nvtext/__init__.py

@@ -1,8 +1,9 @@
 # Copyright (c) 2024, NVIDIA CORPORATION.
 
-from . import edit_distance, generate_ngrams
+from . import edit_distance, generate_ngrams, jaccard
 
 __all__ = [
     "edit_distance",
     "generate_ngrams",
+    "jaccard",
 ]

python/pylibcudf/pylibcudf/nvtext/jaccard.pxd

@@ -0,0 +1,7 @@
+# Copyright (c) 2024, NVIDIA CORPORATION.
+
+from pylibcudf.column cimport Column
+from pylibcudf.libcudf.types cimport size_type
+
+
+cpdef Column jaccard_index(Column input1, Column input2, size_type width)

python/pylibcudf/pylibcudf/nvtext/jaccard.pyx

@@ -0,0 +1,47 @@
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
+
+from libcpp.memory cimport unique_ptr
+from libcpp.utility cimport move
+from pylibcudf.column cimport Column
+from pylibcudf.libcudf.column.column cimport column
+from pylibcudf.libcudf.column.column_view cimport column_view
+from pylibcudf.libcudf.nvtext.jaccard cimport (
+    jaccard_index as cpp_jaccard_index,
+)
+from pylibcudf.libcudf.types cimport size_type
+
+
+cpdef Column jaccard_index(Column input1, Column input2, size_type width):
+    """
+    Returns the Jaccard similarity between individual rows in two strings columns.
+
+    For details, see :cpp:func:`jaccard_index`
+
+    Parameters
+    ----------
+    input1 : Column
+        Input strings column
+    input2 : Column
+        Input strings column
+    width : size_type
+        The ngram number to generate
+
+    Returns
+    -------
+    Column
+        Index calculation values
+    """
+    cdef column_view c_input1 = input1.view()
+    cdef column_view c_input2 = input2.view()
+    cdef unique_ptr[column] c_result
+
+    with nogil:
+        c_result = move(
+            cpp_jaccard_index(
+                c_input1,
+                c_input2,
+                width
+            )
+        )
+
+    return Column.from_libcudf(move(c_result))

python/pylibcudf/pylibcudf/tests/test_nvtext_jaccard.py

@@ -0,0 +1,37 @@
+# Copyright (c) 2024, NVIDIA CORPORATION.
+
+import pyarrow as pa
+import pylibcudf as plc
+import pytest
+from utils import assert_column_eq
+
+
+@pytest.fixture(scope="module")
+def input_data():
+    input1 = ["the fuzzy dog", "little piggy", "funny bunny", "chatty parrot"]
+    input2 = ["the fuzzy cat", "bitty piggy", "funny bunny", "silent partner"]
+    return pa.array(input1), pa.array(input2)
+
+
+@pytest.mark.parametrize("width", [2, 3])
+def test_jaccard_index(input_data, width):
+    def get_tokens(s, width):
+        return [s[i : i + width] for i in range(len(s) - width + 1)]
+
+    def jaccard_index(s1, s2, width):
+        x = set(get_tokens(s1, width))
+        y = set(get_tokens(s2, width))
+        return len(x & y) / len(x | y)
+
+    input1, input2 = input_data
+    result = plc.nvtext.jaccard.jaccard_index(
+        plc.interop.from_arrow(input1), plc.interop.from_arrow(input2), width
+    )
+    expected = pa.array(
+        [
+            jaccard_index(s1.as_py(), s2.as_py(), width)
+            for s1, s2 in zip(input1, input2)
+        ],
+        type=pa.float32(),
+    )
+    assert_column_eq(result, expected)