Add torch methods to discretize

Add fit_transform methods

Discretizer.cpp

@@ -0,0 +1,41 @@
+#include "Discretizer.h"
+
+namespace mdlp {
+    labels_t& Discretizer::transform(const samples_t& data)
+    {
+        discretizedData.clear();
+        discretizedData.reserve(data.size());
+        for (const precision_t& item : data) {
+            auto upper = std::upper_bound(cutPoints.begin(), cutPoints.end(), item);
+            discretizedData.push_back(upper - cutPoints.begin());
+        }
+        return discretizedData;
+    }
+    labels_t& Discretizer::fit_transform(samples_t& X_, labels_t& y_)
+    {
+        fit(X_, y_);
+        return transform(X_);
+    }
+    void Discretizer::fit_t(torch::Tensor& X_, torch::Tensor& y_)
+    {
+        auto num_elements = X_.numel();
+        samples_t X(X_.data_ptr<precision_t>(), X_.data_ptr<precision_t>() + num_elements);
+        labels_t y(y_.data_ptr<int64_t>(), y_.data_ptr<int64_t>() + num_elements);
+        fit(X, y);
+    }
+    torch::Tensor Discretizer::transform_t(torch::Tensor& X_)
+    {
+        auto num_elements = X_.numel();
+        samples_t X(X_.data_ptr<float>(), X_.data_ptr<float>() + num_elements);
+        auto result = transform(X);
+        return torch::tensor(result, torch::kInt64);
+    }
+    torch::Tensor Discretizer::fit_transform_t(torch::Tensor& X_, torch::Tensor& y_)
+    {
+        auto num_elements = X_.numel();
+        samples_t X(X_.data_ptr<precision_t>(), X_.data_ptr<precision_t>() + num_elements);
+        labels_t y(y_.data_ptr<int64_t>(), y_.data_ptr<int64_t>() + num_elements);
+        auto result = fit_transform(X, y);
+        return torch::tensor(result, torch::kInt64);
+    }
+}