python - 如何使用 convert_coreml 转换自定义管道（分类 get

问题描述

我正在尝试将自定义 sklearn 管道保存为 onnx 模型，但在此过程中出现错误。

示例代码：

from sklearn.preprocessing import OneHotEncoder
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.pipeline import Pipeline

from sklearn import svm
from winmltools import convert_coreml

import copy
from IPython.display import display
# https://github.com/pandas-dev/pandas/issues/8918

class MyEncoder(TransformerMixin):

    def __init__(self, columns=None):
        self.columns = columns

    def transform(self, X, y=None, **kwargs):
        return pd.get_dummies(X, dtype=np.float, columns=['ID'])

    def fit(self, X, y=None, **kwargs):
        return self

# data
X = pd.DataFrame([[100, 1.1, 3.1], [200, 4.1, 5.1], [100, 4.1, 2.1]], columns=['ID', 'X1', 'X2'])
Y = pd.Series([3, 2, 4])

# check transform
df = MyEncoder().transform(X)
display(df)

# create pipeline
pipe = Pipeline( steps=[('categorical', MyEncoder()), ('classifier', svm.SVR())] )
print(type(pipe), MyEncoder().transform(X).dtypes, '\n')

# prepare models
svm_toy  = svm.SVR()
svm_toy.fit(X,Y)
pipe_toy = copy.deepcopy(pipe).fit(X, Y)

# save onnx

# no problem here
initial_type = [('X', FloatTensorType( [None, X.shape[1]] ) ) ] 
onx = convert_sklearn(svm_toy, initial_types=initial_type  )

# something goes wrong...
initial_type = [('X', FloatTensorType( [None, X.shape[1]] ) ) ] 
onx = convert_sklearn(pipe_toy, initial_types=initial_type  )

简单的转换很顺利：

# no problem here
initial_type = [('X', FloatTensorType( [None, X.shape[1]] ) ) ] 
onx = convert_sklearn(svm_toy, initial_types=initial_type  )

但是管道转换失败：

# something goes wrong...
initial_type = [('X', FloatTensorType( [None, X.shape[1]] ) ) ] 
onx = convert_sklearn(pipe_toy, initial_types=initial_type  )

出现以下错误：

MissingShapeCalculator: Unable to find a shape calculator for type ''.
It usually means the pipeline being converted contains a
transformer or a predictor with no corresponding converter
implemented in sklearn-onnx. If the converted is implemented
in another library, you need to register
the converted so that it can be used by sklearn-onnx (function
update_registered_converter). If the model is not yet covered
by sklearn-onnx, you may raise an issue to
https://github.com/onnx/sklearn-onnx/issues
to get the converter implemented or even contribute to the
project. If the model is a custom model, a new converter must
be implemented. Examples can be found in the gallery.

我是否缺少自定义管道和get_dummies？

标签： pythonscikit-learnonnx-coreml

python - 如何使用 convert_coreml 转换自定义管道（分类 get_dummies）？

问题描述

解决方案

推荐阅读