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[FFI] Construct NDArray.strides by default #18272

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Merged
tqchen merged 8 commits into from
Sep 6, 2025
Merged

[FFI] Construct NDArray.strides by default #18272

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706bbf5
init
cyx-6 Sep 6, 2025
c093818
add doc
cyx-6 Sep 6, 2025
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upd
cyx-6 Sep 6, 2025
3b7bbf0
rename
cyx-6 Sep 6, 2025
ffa9ce6
fix lint
cyx-6 Sep 6, 2025
d84aeac
using ffi::IsContiguous
cyx-6 Sep 6, 2025
8791500
fix
cyx-6 Sep 6, 2025
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fix
cyx-6 Sep 6, 2025
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25 changes: 19 additions & 6 deletions ffi/include/tvm/ffi/container/ndarray.h
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,6 @@ namespace ffi {
* \return The check result.
*/
inline bool IsContiguous(const DLTensor& arr) {
if (arr.strides == nullptr) return true;
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@tqchen tqchen Sep 6, 2025

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keep this for now as this function is defined per DLTensor

int64_t expected_stride = 1;
for (int32_t i = arr.ndim; i != 0; --i) {
int32_t k = i - 1;
Expand Down Expand Up @@ -110,6 +109,21 @@ inline size_t GetDataSize(const DLTensor& arr) {
return GetDataSize(size, arr.dtype);
}

/*!
* \brief Infer the stride from shape
*
* \param shape the input Shape
* \return the inferred stride
*/
inline Shape InferStrideFromShape(Shape shape) {
size_t ndim = shape.size();
Array<int64_t> strides(ndim, 1);
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@tqchen tqchen Sep 6, 2025

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do not use array, instead, use https://github.com/apache/tvm/blob/main/ffi/include/tvm/ffi/container/shape.h#L71
details::MakeEmptyShape, then fill in the strides.

do something like

int64_t stride = 1;

for  () {
   assign
}

We can also move this function to shape.h details::

for (int i = ndim - 2; i >= 0; --i) {
strides.Set(i, shape[i + 1] * strides[i + 1]);
}
return Shape(strides);
}

/*! \brief An object representing an NDArray. */
class NDArrayObj : public Object, public DLTensor {
public:
Expand Down Expand Up @@ -151,6 +165,7 @@ class NDArrayObj : public Object, public DLTensor {
protected:
// backs up the shape of the NDArray
Optional<Shape> shape_data_;
Optional<Shape> stride_data_;

static void DLManagedTensorDeleter(DLManagedTensor* tensor) {
NDArrayObj* obj = static_cast<NDArrayObj*>(tensor->manager_ctx);
Expand Down Expand Up @@ -184,9 +199,11 @@ class NDArrayObjFromNDAlloc : public NDArrayObj {
this->ndim = static_cast<int>(shape.size());
this->dtype = dtype;
this->shape = const_cast<int64_t*>(shape.data());
this->strides = nullptr;
Shape strides = InferStrideFromShape(shape);
this->strides = const_cast<int64_t*>(strides.data());;
this->byte_offset = 0;
this->shape_data_ = std::move(shape);
this->stride_data_ = std::move(strides);
alloc_.AllocData(static_cast<DLTensor*>(this), std::forward<ExtraArgs>(extra_args)...);
}

Expand All @@ -202,10 +219,6 @@ class NDArrayObjFromDLPack : public NDArrayObj {
public:
explicit NDArrayObjFromDLPack(TDLPackManagedTensor* tensor) : tensor_(tensor) {
*static_cast<DLTensor*>(this) = tensor_->dl_tensor;
// set strides to nullptr if the tensor is contiguous.
if (IsContiguous(tensor->dl_tensor)) {
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also need to check tensor->dl_tensor->strides == nullptr and act accordingly if needed

this->strides = nullptr;
}
}

~NDArrayObjFromDLPack() {
Expand Down
6 changes: 4 additions & 2 deletions ffi/tests/cpp/test_ndarray.cc
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Expand Up @@ -69,7 +69,9 @@ TEST(NDArray, DLPack) {
EXPECT_EQ(dlpack->dl_tensor.device.device_type, kDLCPU);
EXPECT_EQ(dlpack->dl_tensor.device.device_id, 0);
EXPECT_EQ(dlpack->dl_tensor.byte_offset, 0);
EXPECT_EQ(dlpack->dl_tensor.strides, nullptr);
EXPECT_EQ(dlpack->dl_tensor.strides[0], 6);
EXPECT_EQ(dlpack->dl_tensor.strides[1], 3);
EXPECT_EQ(dlpack->dl_tensor.strides[2], 1);
EXPECT_EQ(nd.use_count(), 2);
{
NDArray nd2 = NDArray::FromDLPack(dlpack);
Expand All @@ -96,7 +98,7 @@ TEST(NDArray, DLPackVersioned) {
EXPECT_EQ(dlpack->dl_tensor.device.device_type, kDLCPU);
EXPECT_EQ(dlpack->dl_tensor.device.device_id, 0);
EXPECT_EQ(dlpack->dl_tensor.byte_offset, 0);
EXPECT_EQ(dlpack->dl_tensor.strides, nullptr);
EXPECT_EQ(dlpack->dl_tensor.strides[0], 1);

EXPECT_EQ(nd.use_count(), 2);
{
Expand Down
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