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ONNXMLTools enables conversion of models to ONNX
model_path = 'c://model/m18.m1' lgb_model = lgb.Booster(model_file=model_path) input_type = FloatTensorType([1, 154]) onnx_model = onnxmltools.convert_lightgbm(lgb_model, initial_types=[('input', input_type)], target_opset=9) Traceback (most recent call last): Cell In[4], line 1 onnx_model = onnxmltools.convert_lightgbm(lgb_model, initial_types=[('input', input_type)],...
Hi, When running inference with a Lightgbm model having categorical features, experienced much higher latencies when compared to treating them as all numerical features, especially as vocab size increased. Did...
When converting a XGBRegressor with `objective="reg:logistic"`, the onnx model and the XGBoost model give different results. The difference seems to be a sigmoid transformation that is not included in the...
I was trying to convert XgBoost Regressor to an Onnx Model, even the example in the link https://onnx.ai/sklearn-onnx/auto_tutorial/plot_gexternal_xgboost.html not working with this error "Options ['zipmap'] are not registerd for model...
While trying to convert from Keras, I get the following error: ``` Traceback (most recent call last): File "C:\Users\emers\OneDrive\Documents\Code\ml4\.conda\lib\site-packages\tf2onnx\tf_loader.py", line 218, in from_trackable frozen_graph = from_function(concrete_func, inputs, outputs, large_model) File...
I trained an XGBClassifier model, and now I want to convert it to an ONNX format. It should be straightforward forward using this code: ``` import onnxmltools from skl2onnx.common.data_types import...
Hello everyone, I would like to convert my XGBClassifier with the 'gblinear' booster to onnx. Currently, this only works if the booster is 'gbtree'. Because the gblinear doesn't use trees...
Hi fellow developers, i was working on a simple 3d regressor model and i used the following parameters **#my code extract:** ``` from mlprodict.onnxrt import OnnxInference import numpy import onnxruntime...
A Pytorch Model converted to onnx using the script below successfully executes through ONNXRuntime. But post FP16 conversion, the model fails with `[ONNXRuntimeError] : 1 : FAIL : Type Error:...
XGBClassifier with squaredlogerror objective not getting converted to ONNX. I am trying something like this model = XGBClassifier(objective='reg:squaredlogerror') model.fit(X_train, y_train) initial_types = [('float_input', FloatTensorType([None, X_train.shape[1]]))] onnx_model = onnxmltools.convert_xgboost(model, initial_types =...
