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Merged
sdpython merged 2 commits intomainfrombug
Apr 8, 2024
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7 changes: 5 additions & 2 deletions_doc/examples/plot_benchmark_rf.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -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
Expand All@@ -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"]
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6 changes: 6 additions & 0 deletionsonnx_array_api/_command_lines_parser.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -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,
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5 changes: 3 additions & 2 deletionsonnx_array_api/reference/evaluator_yield.py
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Expand Up@@ -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] loadingfirst model")
print("[compare_onnx_execution] loadingsecond 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)
Expand Down
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