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Fix from_numpy in stride #7042

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merged 2 commits into from
Dec 16, 2021
Merged

Fix from_numpy in stride #7042

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cfbc10a
Fix(FromNumpy): fix bug in stride
wyg1997 Dec 16, 2021
449e5a9
Merge branch 'master' into fix-from_numpy_stride
oneflow-ci-bot Dec 16, 2021
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15 changes: 13 additions & 2 deletions oneflow/api/python/functional/tensor_api.cpp
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Expand Up @@ -231,8 +231,19 @@ class LocalTensorSharedNumpyDataFunctor {
DataType data_type = JUST(numpy::GetOFDataTypeFromNpArray(array));
Symbol<Device> device = JUST(Device::New("cpu"));
const npy_intp* stride_ptr = PyArray_STRIDES(array);
const auto stride = std::make_shared<Stride>(DimVector(stride_ptr, stride_ptr + dim));
auto tensor_meta = std::make_shared<MirroredTensorMeta>(shape, data_type, device, stride, 0);
// stride
auto strides_vec = DimVector(stride_ptr, stride_ptr + dim);
auto element_size_in_bytes = PyArray_ITEMSIZE(array);
// NumPy strides use bytes. OneFlow strides use element counts.
for (auto& stride : strides_vec) {
if (stride % element_size_in_bytes != 0) {
return Error::RuntimeError() << "given numpy array strides not a multiple of the element "
"byte size. Copy the numpy array to reallocate the memory.";
}
stride /= element_size_in_bytes;
}
const auto strides = std::make_shared<Stride>(strides_vec);
auto tensor_meta = std::make_shared<MirroredTensorMeta>(shape, data_type, device, strides, 0);

// Build TensorBuffer
const auto& Free = [obj](char* dptr) {
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3 changes: 3 additions & 0 deletions python/oneflow/test/modules/test_from_numpy.py
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Expand Up @@ -28,6 +28,9 @@ def test_same_data(test_case):
np_arr = np.random.randn(3, 4, 5)
tensor = flow.from_numpy(np_arr)
test_case.assertTrue(np.array_equal(np_arr, tensor.numpy()))
test_case.assertEqual(tensor.size(), (3, 4, 5))
test_case.assertEqual(tensor.stride(), (20, 5, 1))
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这个assert在下面tensor ** 2的那个test case也加一下吧

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应该不需要吧，因为 shape 的推导逻辑是 Op 的事，只要 Tensor 创建没问题了，后面TensorMeta 的检察应该在 Op 的测试中覆盖了，就和这个单测没关系了

test_case.assertEqual(tensor.storage_offset(), 0)

np_arr[1:2, 2:3, 3:4] = random.random()
test_case.assertTrue(np.array_equal(np_arr, tensor.numpy()))
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