Compute components_ in DBSCAN

docs/source/zero-code-change-limitations.rst

@@ -111,10 +111,6 @@ DBSCAN
 - If ``metric`` isn't one of the supported metrics (``"l2"``, ``"euclidean"``, ``"cosine"``, ``"precomputed"``).
 - If ``X`` is sparse.
 
-Additionally, the following fitted attributes are currently not computed:
-
-- ``components_``
-
 
 sklearn.decomposition
 ---------------------

python/cuml/cuml/accel/tests/scikit-learn/xfail-list.yaml

@@ -1245,7 +1245,6 @@
 - reason: cuml missing certain fit attributes
   marker: cuml_accel_missing_fit_attributes
   tests:
-  - "sklearn.tests.test_docstring_parameters::test_fit_docstring_attributes[DBSCAN-DBSCAN]"
   - "sklearn.tests.test_docstring_parameters::test_fit_docstring_attributes[ElasticNet-ElasticNet]"
   - "sklearn.tests.test_docstring_parameters::test_fit_docstring_attributes[Lasso-Lasso]"
   - "sklearn.tests.test_docstring_parameters::test_fit_docstring_attributes[SVC-SVC]"
@@ -1538,7 +1537,3 @@
   strict: false
   tests:
   - "sklearn.decomposition.tests.test_sparse_pca::test_equivalence_components_pca_spca[42]"
-- reason: 'cuml.accel bug: Missing components_ attribute'
-  tests:
-  - "sklearn.cluster.tests.test_dbscan::test_dbscan_no_core_samples[csr_array]"
-  - "sklearn.cluster.tests.test_dbscan::test_dbscan_no_core_samples[csr_matrix]"

python/cuml/cuml/cluster/dbscan.pyx

@@ -199,8 +199,9 @@ class DBSCAN(Base,
         :ref:`output-data-type-configuration` for more info.
     calc_core_sample_indices : (optional) boolean (default = True)
         Indicates whether the indices of the core samples should be calculated.
-        The the attribute `core_sample_indices_` will not be used, setting this
-        to False will avoid unnecessary kernel launches
+        If True (the default), ``core_sample_indices_`` and ``components_`` will
+        be computed and stored as fitted attributes. Set to False to avoid
+        computing these attributes, removing a small amount of overhead.
 
     Attributes
     ----------
@@ -210,7 +211,10 @@ class DBSCAN(Base,
         output_type.
     core_sample_indices_ : array-like or cuDF series
         The indices of the core samples. Only calculated if
-        calc_core_sample_indices==True
+        ``calc_core_sample_indices=True``.
+    components_ : array-like or cuDF series
+        Copy of each core sample found by training. Only calculated if
+        ``calc_core_sample_indices=True``.
 
     Notes
     -----
@@ -232,6 +236,7 @@ class DBSCAN(Base,
     """
 
     core_sample_indices_ = CumlArrayDescriptor(order="C")
+    components_ = CumlArrayDescriptor(order="C")
     labels_ = CumlArrayDescriptor(order="C")
 
     _cpu_class_path = "sklearn.cluster.DBSCAN"
@@ -274,13 +279,15 @@ class DBSCAN(Base,
     def _attrs_from_cpu(self, model):
         return {
             "core_sample_indices_": to_gpu(model.core_sample_indices_, order="C"),
+            "components_": to_gpu(model.components_, order="C"),
             "labels_": to_gpu(model.labels_, order="C"),
             **super()._attrs_from_cpu(model),
         }
 
     def _attrs_to_cpu(self, model):
         return {
             "core_sample_indices_": to_cpu(self.core_sample_indices_, order="C"),
+            "components_": to_cpu(self.components_, order="C"),
             "labels_": to_cpu(self.labels_, order="C"),
             **super()._attrs_to_cpu(model),
         }
@@ -305,12 +312,6 @@ class DBSCAN(Base,
         self.metric = metric
         self.algorithm = algorithm
 
-        # internal array attributes
-        self.labels_ = None
-
-        # One used when `self.calc_core_sample_indices == True`
-        self.core_sample_indices_ = None
-
         # C++ API expects this to be numeric.
         if self.max_mbytes_per_batch is None:
             self.max_mbytes_per_batch = 0
@@ -378,8 +379,7 @@ class DBSCAN(Base,
 
         # Create the output core_sample_indices only if needed
         if self.calc_core_sample_indices:
-            self.core_sample_indices_ = \
-                CumlArray.empty(n_rows, dtype=out_dtype)
+            self.core_sample_indices_ = CumlArray.empty(n_rows, dtype=out_dtype)
             core_sample_indices_ptr = self.core_sample_indices_.ptr
 
         if self.dtype == np.float32:
@@ -449,7 +449,6 @@ class DBSCAN(Base,
         # make sure that the `fit` is complete before the following
         # delete call happens
         self.handle.sync()
-        del X_m
 
         # Finally, resize the core_sample_indices array if necessary
         if self.calc_core_sample_indices:
@@ -459,13 +458,16 @@ class DBSCAN(Base,
                 # increasing, so the min index should be the first returned -1
                 min_index = cp.argmin(self.core_sample_indices_).item()
                 # Check for the case where there are no -1's
-                if ((min_index == 0 and
-                        self.core_sample_indices_[min_index].item() != -1)):
+                if ((min_index == 0 and self.core_sample_indices_[min_index].item() != -1)):
                     # Nothing to delete. The array has no -1's
                     pass
                 else:
-                    self.core_sample_indices_ = \
-                        self.core_sample_indices_[:min_index]
+                    self.core_sample_indices_ = self.core_sample_indices_[:min_index]
+
+                self.components_ = X_m.to_output("cupy")[self.core_sample_indices_]
+        else:
+            self.core_sample_indices_ = None
+            self.components_ = None
 
         return self
 

python/cuml/cuml/tests/test_dbscan.py

@@ -329,6 +329,7 @@ def test_core_point_prop1():
     assert array_equal(
         cuml_dbscan.core_sample_indices_, sk_dbscan.core_sample_indices_
     )
+    assert array_equal(cuml_dbscan.components_, sk_dbscan.components_)
 
     # Check the labels are correct
     assert_dbscan_equal(
@@ -376,6 +377,7 @@ def test_core_point_prop2():
     assert array_equal(
         cuml_dbscan.core_sample_indices_, sk_dbscan.core_sample_indices_
     )
+    assert array_equal(cuml_dbscan.components_, sk_dbscan.components_)
 
     # Check the labels are correct
     assert_dbscan_equal(
@@ -429,6 +431,7 @@ def test_core_point_prop3():
     assert array_equal(
         cuml_dbscan.core_sample_indices_, sk_dbscan.core_sample_indices_
     )
+    assert array_equal(cuml_dbscan.components_, sk_dbscan.components_)
 
     # Check the labels are correct
     assert_dbscan_equal(
@@ -507,6 +510,7 @@ def test_dbscan_no_calc_core_point_indices():
 
     # Make sure we are None
     assert cuml_dbscan.core_sample_indices_ is None
+    assert cuml_dbscan.components_ is None
 
 
 def test_dbscan_on_empty_array():