Remove KMeansMG

I _think_ we can fully remove `KMeansMG`.

As is, KMeansMG is a thin wrapper around `KMeans` itself, with just the
`fit` method reimplemented. Looking at the implementation though, all it
does is call `cuvs::cluster::kmeans::fit` (with much less input
validation than it should) followed by `cuvs::cluster::kmeans::predict`
instead of a single call to `cuvs::cluster::kmeans::fit_predict` (like
`KMeans` does). Reading through the cuvs docs, I don't see a strong
reason why we can't just use `fit_predict` everywhere. Ripping out
`KMeansMG` does lead all tests to pass.

Author: jcrist

python/cuml/cuml/cluster/CMakeLists.txt

@@ -17,12 +17,6 @@ add_module_gpu_default("agglomerative.pyx" ${agglomerative_algo} ${cluster_algo}
 add_module_gpu_default("dbscan.pyx" ${dbscan_algo} ${cluster_algo})
 add_module_gpu_default("kmeans.pyx" ${kmeans_algo} ${cluster_algo})
 
-if(NOT SINGLEGPU)
-  list(APPEND cython_sources
-       kmeans_mg.pyx
-  )
-endif()
-
 add_subdirectory(hdbscan)
 
 rapids_cython_create_modules(

python/cuml/cuml/cluster/kmeans_mg.pyx

@@ -98,7 +98,7 @@ def __init__(self, *, client=None, verbose=False, **kwargs):
     @staticmethod
     @mnmg_import
     def _func_fit(sessionId, objs, datatype, has_weights, **kwargs):
-        from cuml.cluster.kmeans_mg import KMeansMG as cumlKMeans
+        from cuml.cluster.kmeans import KMeans
 
         handle = get_raft_comm_state(sessionId, get_worker())["handle"]
 
@@ -109,7 +109,7 @@ def _func_fit(sessionId, objs, datatype, has_weights, **kwargs):
             inp_data = concatenate([X for X, weights in objs])
             inp_weights = concatenate([weights for X, weights in objs])
 
-        return cumlKMeans(handle=handle, output_type=datatype, **kwargs).fit(
+        return KMeans(handle=handle, output_type=datatype, **kwargs).fit(
             inp_data, sample_weight=inp_weights
         )