Add XGBoost test file (#1309)

source/python.js

@@ -2096,17 +2096,17 @@ python.Execution = class {
  });
  this.registerType('joblib.numpy_pickle.NumpyArrayWrapper', class {
 
- __setstate__(state) {
- this.subclass = state.subclass;
- this.dtype = state.dtype;
- this.shape = state.shape;
- this.order = state.order;
- this.allow_mmap = state.allow_mmap;
- }
  __read__(unpickler) {
  if (this.dtype.__name__ === 'object') {
  return unpickler.load();
  }
+ if (this.numpy_array_alignment_bytes) {
+ const [size] = unpickler.read(1);
+ unpickler.read(size);
+ }
+ if (this.order === 'F') {
+ throw new python.Error('Fortran order not implemented.');
+ }
  const size = this.dtype.itemsize * this.shape.reduce((a, b) => a * b, 1);
  this.data = unpickler.read(size);
  return execution.invoke(this.subclass, [this.shape, this.dtype, this.data]);

test/models.json

@@ -6409,6 +6409,13 @@
  "format": "scikit-learn v0.24.0rc1",
  "link": "https://github.com/lutzroeder/netron/issues/182"
  },
+ {
+ "type": "sklearn",
+ "target": "numpy_array_alignment_bytes.pkl",
+ "source": "https://github.com/user-attachments/files/16054844/numpy_array_alignment_bytes.pkl.zip[numpy_array_alignment_bytes.pkl]",
+ "format": "scikit-learn",
+ "link": "https://github.com/lutzroeder/netron/issues/182"
+ },
  {
  "type": "sklearn",
  "target": "phoenix_ml_classifier.pkl",