clarify DEBUG-level log about tree depth (#4126)

* clarify DEBUG-level log about tree depth

* more places

docs/GPU-Targets.rst

@@ -104,10 +104,10 @@ Example of using GPU (``gpu_platform_id = 0`` and ``gpu_device_id = 0`` in our s
     [LightGBM] [Info] Size of histogram bin entry: 12
     [LightGBM] [Info] 40 dense feature groups (0.12 MB) transferred to GPU in 0.004211 secs. 76 sparse feature groups.
     [LightGBM] [Info] No further splits with positive gain, best gain: -inf
-    [LightGBM] [Info] Trained a tree with leaves=16 and max_depth=8
+    [LightGBM] [Info] Trained a tree with leaves=16 and depth=8
     [1]:    test's rmse:1.10643e-17 
     [LightGBM] [Info] No further splits with positive gain, best gain: -inf
-    [LightGBM] [Info] Trained a tree with leaves=7 and max_depth=5
+    [LightGBM] [Info] Trained a tree with leaves=7 and depth=5
     [2]:    test's rmse:0
 
 Running on OpenCL CPU backend devices is in generally slow, and we observe crashes on some Windows and macOS systems. Make sure you check the ``Using GPU Device`` line in the log and it is not using a CPU. The above log shows that we are using ``Oland`` GPU from AMD and not CPU.
@@ -142,10 +142,10 @@ Example of using CPU (``gpu_platform_id = 0``, ``gpu_device_id = 1``). The GPU d
     [LightGBM] [Info] Size of histogram bin entry: 12
     [LightGBM] [Info] 40 dense feature groups (0.12 MB) transferred to GPU in 0.004540 secs. 76 sparse feature groups.
     [LightGBM] [Info] No further splits with positive gain, best gain: -inf
-    [LightGBM] [Info] Trained a tree with leaves=16 and max_depth=8
+    [LightGBM] [Info] Trained a tree with leaves=16 and depth=8
     [1]:    test's rmse:1.10643e-17 
     [LightGBM] [Info] No further splits with positive gain, best gain: -inf
-    [LightGBM] [Info] Trained a tree with leaves=7 and max_depth=5
+    [LightGBM] [Info] Trained a tree with leaves=7 and depth=5
     [2]:    test's rmse:0
     
 

src/treelearner/linear_tree_learner.cpp

@@ -125,7 +125,7 @@ Tree* LinearTreeLearner::Train(const score_t* gradients, const score_t *hessians
     CalculateLinear<false>(tree_ptr, false, gradients_, hessians_, is_first_tree);
   }
 
-  Log::Debug("Trained a tree with leaves = %d and max_depth = %d", tree->num_leaves(), cur_depth);
+  Log::Debug("Trained a tree with leaves = %d and depth = %d", tree->num_leaves(), cur_depth);
   return tree.release();
 }
 

src/treelearner/serial_tree_learner.cpp

@@ -204,7 +204,7 @@ Tree* SerialTreeLearner::Train(const score_t* gradients, const score_t *hessians
     cur_depth = std::max(cur_depth, tree->leaf_depth(left_leaf));
   }
 
-  Log::Debug("Trained a tree with leaves = %d and max_depth = %d", tree->num_leaves(), cur_depth);
+  Log::Debug("Trained a tree with leaves = %d and depth = %d", tree->num_leaves(), cur_depth);
   return tree.release();
 }