removed softmax loss, removed a redundant variable, moved mg files in…

…to same directory
rapidsai · Aug 25, 2023 · e8d6ccf · e8d6ccf
1 parent 6dc3c0d
commit e8d6ccf
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Showing 3 changed files with 12 additions and 26 deletions.
diff --git a/cpp/src/glm/qn/glm_base_mg.cuh → cpp/src/glm/qn/mg/glm_base_mg.cuh b/cpp/src/glm/qn/glm_base_mg.cuh → cpp/src/glm/qn/mg/glm_base_mg.cuh
@@ -90,7 +90,6 @@ struct GLMWithDataMG : ML::GLM::detail::GLMWithData<T, GLMObjective> {
   int rank;
   int64_t n_samples;
   int n_ranks;
-  T l2;
 
   GLMWithDataMG(raft::handle_t const& handle,
                 int rank,
@@ -99,15 +98,13 @@ struct GLMWithDataMG : ML::GLM::detail::GLMWithData<T, GLMObjective> {
                 GLMObjective* obj,
                 const SimpleMat<T>& X,
                 const SimpleVec<T>& y,
-                SimpleDenseMat<T>& Z,
-                T l2)
+                SimpleDenseMat<T>& Z)
     : ML::GLM::detail::GLMWithData<T, GLMObjective>(obj, X, y, Z)
   {
     this->handle_p  = &handle;
     this->rank      = rank;
     this->n_ranks   = n_ranks;
     this->n_samples = n_samples;
-    this->l2        = l2;
   }
 
   inline T operator()(const SimpleVec<T>& wFlat,
@@ -125,7 +122,7 @@ struct GLMWithDataMG : ML::GLM::detail::GLMWithData<T, GLMObjective> {
     auto reg             = regularizer_obj->reg;
     G.fill(0, stream);
     float reg_host = 0;
-    if (this->l2 != 0) {
+    if (reg->l2_penalty != 0) {
       reg->reg_grad(dev_scalar, G, W, lossFunc->fit_intercept, stream);
       raft::update_host(&reg_host, dev_scalar, 1, stream);
       // note: avoid syncing here because there's a sync before reg_host is used.

diff --git a/cpp/src/glm/qn/qn_mg.cuh → cpp/src/glm/qn/mg/qn_mg.cuh b/cpp/src/glm/qn/qn_mg.cuh → cpp/src/glm/qn/mg/qn_mg.cuh
@@ -15,12 +15,12 @@
  */
 
 #include "glm_base_mg.cuh"
-#include "glm_logistic.cuh"
-#include "glm_regularizer.cuh"
-#include "glm_softmax.cuh"
-#include "glm_svm.cuh"
-#include "qn_solvers.cuh"
-#include "qn_util.cuh"
+#include <glm/qn/glm_logistic.cuh>
+#include <glm/qn/glm_regularizer.cuh>
+#include <glm/qn/glm_softmax.cuh>
+#include <glm/qn/glm_svm.cuh>
+#include <glm/qn/qn_solvers.cuh>
+#include <glm/qn/qn_util.cuh>
 
 #include <cuml/linear_model/qn.h>
 #include <rmm/device_uvector.hpp>
@@ -56,8 +56,7 @@ int qn_fit_mg(const raft::handle_t& handle,
   ML::GLM::detail::Tikhonov<T> reg(l2);
   ML::GLM::detail::RegularizedGLM<T, LossFunction, decltype(reg)> regularizer_obj(&loss, &reg);
 
-  auto obj_function =
-    GLMWithDataMG(handle, rank, n_ranks, n_samples, &regularizer_obj, X, y, Z, l2);
+  auto obj_function = GLMWithDataMG(handle, rank, n_ranks, n_samples, &regularizer_obj, X, y, Z);
   return ML::GLM::detail::qn_minimize(
     handle, w0, fx, num_iters, obj_function, l1, opt_param, pams.verbose);
 }
@@ -99,19 +98,13 @@ inline void qn_fit_x_mg(const raft::handle_t& handle,
 
   switch (pams.loss) {
     case QN_LOSS_LOGISTIC: {
-      ASSERT(C == 2, "qn.h: logistic loss invalid C");
+      ASSERT(C == 2, "qn_mg.cuh: logistic loss invalid C");
       ML::GLM::detail::LogisticLoss<T> loss(handle, D, pams.fit_intercept);
       ML::GLM::opg::qn_fit_mg<T, decltype(loss)>(
         handle, pams, loss, X, y, Z, w0_data, f, num_iters, n_samples, rank, n_ranks);
     } break;
-    case QN_LOSS_SOFTMAX: {
-      ASSERT(C > 2, "qn.h: softmax invalid C");
-      ML::GLM::detail::Softmax<T> loss(handle, D, C, pams.fit_intercept);
-      ML::GLM::opg::qn_fit_mg<T, decltype(loss)>(
-        handle, pams, loss, X, y, Z, w0_data, f, num_iters, n_samples, rank, n_ranks);
-    } break;
     default: {
-      ASSERT(false, "qn.h: unknown loss function type (id = %d).", pams.loss);
+      ASSERT(false, "qn_mg.cuh: unknown loss function type (id = %d).", pams.loss);
     }
   }
 }

diff --git a/cpp/src/glm/qn_mg.cu b/cpp/src/glm/qn_mg.cu
@@ -14,11 +14,7 @@
  * limitations under the License.
  */
 
-#include "qn/glm_logistic.cuh"
-#include "qn/glm_regularizer.cuh"
-#include "qn/qn_mg.cuh"
-#include "qn/qn_solvers.cuh"
-#include "qn/qn_util.cuh"
+#include "qn/mg/qn_mg.cuh"
 #include "qn/simple_mat/dense.hpp"
 #include <cuda_runtime.h>
 #include <cuml/common/logger.hpp>