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More error checking in from_dlpack #10850

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May 16, 2022
Merged

More error checking in from_dlpack #10850

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401264f
Add more error checking in from_dlpack
wence- May 13, 2022
362fc40
Add autodoc entry for cudf.from_dlpack
wence- May 13, 2022
783c293
Fix condition for 2D tensors
wence- May 13, 2022
073660b
Merge error checking in from_dlpack
wence- May 16, 2022
35dab88
Single column tensors are fine in 2D
wence- May 16, 2022
2582104
Tests strided from_dlpack error checking
wence- May 16, 2022
4b9743f
Typography in some CUDF_EXPECTS messages
wence- May 16, 2022
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25 changes: 19 additions & 6 deletions cpp/src/interop/dlpack.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -148,20 +148,33 @@ std::unique_ptr<table> from_dlpack(DLManagedTensor const* managed_tensor,
CUDF_EXPECTS(tensor.device.device_id == device_id, "DLTensor device ID must be current device");
}

// Currently only 1D and 2D tensors are supported
CUDF_EXPECTS(tensor.ndim > 0 && tensor.ndim <= 2, "DLTensor must be 1D or 2D");

// We only support 1D and 2D tensors with some restrictions on layout
if (tensor.ndim == 1) {
// 1D tensors must have dense layout (strides == nullptr <=> dense row-major)
CUDF_EXPECTS(nullptr == tensor.strides || tensor.strides[0] == 1,
"from_dlpack of 1D DLTensor only for unit-stride data");
} else if (tensor.ndim == 2) {
// 2D tensors must have column-major layout and the fastest dimension must have dense layout
CUDF_EXPECTS((
// 1D tensor reshaped into (N, 1) is fine
tensor.shape[1] == 1 && (nullptr == tensor.strides || tensor.strides[0] == 1))
// General case
|| (nullptr != tensor.strides && tensor.strides[0] == 1 &&
tensor.strides[1] >= tensor.shape[0]),
"from_dlpack of 2D DLTensor only for column-major unit-stride data");
} else {
CUDF_FAIL("DLTensor must be 1D or 2D");
}
CUDF_EXPECTS(tensor.shape[0] >= 0,
"DLTensor first dim should be of shape greater than or equal-to 0.");
"DLTensor first dim should be of shape greater than or equal to 0.");
CUDF_EXPECTS(tensor.shape[0] < std::numeric_limits<size_type>::max(),
"DLTensor first dim exceeds size supported by cudf");
if (tensor.ndim > 1) {
CUDF_EXPECTS(tensor.shape[1] >= 0,
"DLTensor second dim should be of shape greater than or equal-to 0.");
"DLTensor second dim should be of shape greater than or equal to 0.");
CUDF_EXPECTS(tensor.shape[1] < std::numeric_limits<size_type>::max(),
"DLTensor second dim exceeds size supported by cudf");
}

size_t const num_columns = (tensor.ndim == 2) ? static_cast<size_t>(tensor.shape[1]) : 1;

// Validate and convert data type to cudf
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114 changes: 114 additions & 0 deletions cpp/tests/interop/dlpack_test.cpp
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Expand Up @@ -208,6 +208,120 @@ TEST_F(DLPackUntypedTests, UnsupportedLanesFromDlpack)
EXPECT_THROW(cudf::from_dlpack(tensor.get()), cudf::logic_error);
}

TEST_F(DLPackUntypedTests, UnsupportedBroadcast1DTensorFromDlpack)
{
using T = float;
constexpr int ndim = 1;
// Broadcasted (stride-0) 1D tensor
auto const data = cudf::test::make_type_param_vector<T>({1});
int64_t shape[ndim] = {5};
int64_t strides[ndim] = {0};

DLManagedTensor tensor{};
tensor.dl_tensor.device.device_type = kDLCPU;
tensor.dl_tensor.dtype = get_dtype<T>();
tensor.dl_tensor.ndim = ndim;
tensor.dl_tensor.byte_offset = 0;
tensor.dl_tensor.shape = shape;
tensor.dl_tensor.strides = strides;

thrust::host_vector<T> host_vector(data.begin(), data.end());
tensor.dl_tensor.data = host_vector.data();

EXPECT_THROW(cudf::from_dlpack(&tensor), cudf::logic_error);
}

TEST_F(DLPackUntypedTests, UnsupportedStrided1DTensorFromDlpack)
{
using T = float;
constexpr int ndim = 1;
// Strided 1D tensor
auto const data = cudf::test::make_type_param_vector<T>({1, 2, 3, 4});
int64_t shape[ndim] = {2};
int64_t strides[ndim] = {2};

DLManagedTensor tensor{};
tensor.dl_tensor.device.device_type = kDLCPU;
tensor.dl_tensor.dtype = get_dtype<T>();
tensor.dl_tensor.ndim = ndim;
tensor.dl_tensor.byte_offset = 0;
tensor.dl_tensor.shape = shape;
tensor.dl_tensor.strides = strides;

thrust::host_vector<T> host_vector(data.begin(), data.end());
tensor.dl_tensor.data = host_vector.data();

EXPECT_THROW(cudf::from_dlpack(&tensor), cudf::logic_error);
}

TEST_F(DLPackUntypedTests, UnsupportedImplicitRowMajor2DTensorFromDlpack)
{
using T = float;
constexpr int ndim = 2;
// Row major 2D tensor
auto const data = cudf::test::make_type_param_vector<T>({1, 2, 3, 4});
int64_t shape[ndim] = {2, 2};

DLManagedTensor tensor{};
tensor.dl_tensor.device.device_type = kDLCPU;
tensor.dl_tensor.dtype = get_dtype<T>();
tensor.dl_tensor.ndim = ndim;
tensor.dl_tensor.byte_offset = 0;
tensor.dl_tensor.shape = shape;
tensor.dl_tensor.strides = nullptr;

thrust::host_vector<T> host_vector(data.begin(), data.end());
tensor.dl_tensor.data = host_vector.data();

EXPECT_THROW(cudf::from_dlpack(&tensor), cudf::logic_error);
}

TEST_F(DLPackUntypedTests, UnsupportedExplicitRowMajor2DTensorFromDlpack)
{
using T = float;
constexpr int ndim = 2;
// Row major 2D tensor with explicit strides
auto const data = cudf::test::make_type_param_vector<T>({1, 2, 3, 4});
int64_t shape[ndim] = {2, 2};
int64_t strides[ndim] = {2, 1};

DLManagedTensor tensor{};
tensor.dl_tensor.device.device_type = kDLCPU;
tensor.dl_tensor.dtype = get_dtype<T>();
tensor.dl_tensor.ndim = ndim;
tensor.dl_tensor.byte_offset = 0;
tensor.dl_tensor.shape = shape;
tensor.dl_tensor.strides = strides;

thrust::host_vector<T> host_vector(data.begin(), data.end());
tensor.dl_tensor.data = host_vector.data();

EXPECT_THROW(cudf::from_dlpack(&tensor), cudf::logic_error);
}

TEST_F(DLPackUntypedTests, UnsupportedStridedColMajor2DTensorFromDlpack)
{
using T = float;
constexpr int ndim = 2;
// Column major, but strided in fastest dimension
auto const data = cudf::test::make_type_param_vector<T>({1, 2, 3, 4, 5, 6, 7, 8});
int64_t shape[ndim] = {2, 2};
int64_t strides[ndim] = {2, 4};

DLManagedTensor tensor{};
tensor.dl_tensor.device.device_type = kDLCPU;
tensor.dl_tensor.dtype = get_dtype<T>();
tensor.dl_tensor.ndim = ndim;
tensor.dl_tensor.byte_offset = 0;
tensor.dl_tensor.shape = shape;
tensor.dl_tensor.strides = strides;

thrust::host_vector<T> host_vector(data.begin(), data.end());
tensor.dl_tensor.data = host_vector.data();

EXPECT_THROW(cudf::from_dlpack(&tensor), cudf::logic_error);
}

template <typename T>
class DLPackTimestampTests : public BaseFixture {
};
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1 change: 1 addition & 0 deletions docs/cudf/source/api_docs/general_functions.rst
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Expand Up @@ -23,6 +23,7 @@ Top-level conversions
:toctree: api/

cudf.to_numeric
cudf.from_dlpack

Top-level dealing with datetimelike
-----------------------------------
Expand Down