Better comments (#84)

* better comments

* status

Author: xadupre

_doc/examples/plot_benchmark_rf.py

@@ -22,8 +22,6 @@
 import numpy
 import pandas
 from lightgbm import LGBMRegressor
-from onnxmltools.convert.lightgbm.operator_converters.LightGbm import convert_lightgbm
-from onnxmltools.convert.xgboost.operator_converters.XGBoost import convert_xgboost
 from onnxruntime import InferenceSession, SessionOptions
 from psutil import cpu_count
 from sphinx_runpython.runpython import run_cmd
@@ -33,9 +31,14 @@
 from sklearn.ensemble import RandomForestRegressor
 from tqdm import tqdm
 from xgboost import XGBRegressor
+from onnxmltools.convert.xgboost.operator_converters.XGBoost import convert_xgboost
 
 
 def skl2onnx_convert_lightgbm(scope, operator, container):
+    from onnxmltools.convert.lightgbm.operator_converters.LightGbm import (
+        convert_lightgbm,
+    )
+
     options = scope.get_options(operator.raw_operator)
     if "split" in options:
         operator.split = options["split"]

onnx_array_api/_command_lines_parser.py

@@ -123,8 +123,14 @@ def _cmd_compare(argv: List[Any]):
 
     parser = get_parser_compare()
     args = parser.parse_args(argv[1:])
+    if args.verbose in ("1", 1, "True", True):
+        print(f"[compare] first model {args.model1!r}")
+        print(f"[compare] second model {args.model2!r}")
     onx1 = onnx.load(args.model1)
     onx2 = onnx.load(args.model2)
+    if args.verbose in ("1", 1, "True", True):
+        print(f"[compare] first model has {len(onx1.graph.node)} nodes")
+        print(f"[compare] second model has {len(onx2.graph.node)} nodes")
     res1, res2, align, dc = compare_onnx_execution(
         onx1,
         onx2,

onnx_array_api/reference/evaluator_yield.py

@@ -642,15 +642,16 @@ def compare_onnx_execution(
             print("[compare_onnx_execution] loading first model")
         proto1 = load(model1) if isinstance(model1, str) else model1
         if verbose:
-            print("[compare_onnx_execution] loading first model")
+            print("[compare_onnx_execution] loading second model")
         proto2 = load(model2) if isinstance(model2, str) else model2
         res1 = list(_enumerate_result_no_execution(proto1))
         res2 = list(_enumerate_result_no_execution(proto2))
     else:
         return
 
     if verbose:
-        print(f"[compare_onnx_execution] got {len(res2)} results")
+        print(f"[compare_onnx_execution] got {len(res1)} results (first model)")
+        print(f"[compare_onnx_execution] got {len(res2)} results (second model)")
         print("[compare_onnx_execution] compute edit distance")
     dc = DistanceExecution()
     _, align = dc.distance_sequence(res1, res2)