Fix byte ordering issue in from_numpy (#9508)

vishwakftw · facebook-github-bot · commit 7d16e87f14c4 · 2018-08-13T21:39:16.000-07:00
Summary: Fixes #3671 . Pull Request resolved: #9508 Differential Revision: D9307186 Pulled By: soumith fbshipit-source-id: 39dcaa6fd2d330d7085802acd6f63c19270164fa
diff --git a/test/test_torch.py b/test/test_torch.py
@@ -7925,7 +7925,7 @@ def test_from_numpy(self):
 
     @unittest.skipIf(not TEST_NUMPY, "Numpy not found")
     def test_ctor_with_numpy_array(self):
-        dtypes = [
+        correct_dtypes = [
             np.double,
             np.float,
             np.float16,
@@ -7934,7 +7934,11 @@ def test_ctor_with_numpy_array(self):
             np.int16,
             np.uint8
         ]
-        for dtype in dtypes:
+
+        incorrect_byteorder = '>' if sys.byteorder == 'little' else '<'
+        incorrect_dtypes = map(lambda t: incorrect_byteorder + t, ['d', 'f'])
+
+        for dtype in correct_dtypes:
             array = np.array([1, 2, 3, 4], dtype=dtype)
 
             # Upcast
diff --git a/torch/csrc/utils/tensor_numpy.cpp b/torch/csrc/utils/tensor_numpy.cpp
@@ -117,6 +117,11 @@ at::Tensor tensor_from_numpy(PyObject* obj) {
 
   void* data_ptr = PyArray_DATA(array);
   auto& type = CPU(numpy_dtype_to_aten(PyArray_TYPE(array)));
+  if (!PyArray_EquivByteorders(PyArray_DESCR(array)->byteorder, NPY_NATIVE)) {
+    throw ValueError(
+        "given numpy array has byte order different from the native byte order. "
+        "Conversion between byte orders is currently not supported.");
+  }
   Py_INCREF(obj);
   return type.tensorFromBlob(data_ptr, sizes, strides, [obj](void* data) {
     AutoGIL gil;
