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[nodejs binding] Fix building in latest clang (#23146)

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### Description

This change fixes the build break for Node.js binding on latest
AppleClang:

```
...tensor_helper.cc:65:5 error: integer value -1 is outside of the valid range of values [0,15] for the enumeration type 'napi_typedarray_type' [-Wenum-constexpr-conversion]

```

Use the underlying type of enum `napi_typedarray_type` for
`DATA_TYPE_TYPEDARRAY_MAP` to solve this issue.

Because the underlying type is implementation defined (it's `int` for
MSVC and `unsigned int` for Clang), we use `std::underlying_type_t` to
get the correct type.
This commit is contained in:
Yulong Wang 2024-12-19 10:23:27 -08:00 committed by GitHub
parent ae6dcc839e
commit 780735098d
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GPG key ID: B5690EEEBB952194
1 changed files with 34 additions and 21 deletions
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55
js/node/src/tensor_helper.cc
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@ -53,24 +53,24 @@ constexpr size_t DATA_TYPE_ELEMENT_SIZE_MAP[] = {
static_assert(sizeof(DATA_TYPE_ELEMENT_SIZE_MAP) == sizeof(size_t) * ONNX_TENSOR_ELEMENT_DATA_TYPE_COUNT,
"definition not matching");
constexpr napi_typedarray_type DATA_TYPE_TYPEDARRAY_MAP[] = {
(napi_typedarray_type)(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED not supported
napi_float32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT
napi_uint8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8
napi_int8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8
napi_uint16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16
napi_int16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16
napi_int32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32
napi_bigint64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64
(napi_typedarray_type)(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING not supported
napi_uint8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL
napi_uint16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16 FLOAT16 uses Uint16Array
napi_float64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE
napi_uint32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32
napi_biguint64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64
(napi_typedarray_type)(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX64 not supported
(napi_typedarray_type)(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX128 not supported
(napi_typedarray_type)(-1) // ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16 not supported
constexpr std::underlying_type_t<napi_typedarray_type> DATA_TYPE_TYPEDARRAY_MAP[] = {
std::underlying_type_t<napi_typedarray_type>(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED not supported
napi_float32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT
napi_uint8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8
napi_int8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8
napi_uint16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16
napi_int16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16
napi_int32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32
napi_bigint64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64
std::underlying_type_t<napi_typedarray_type>(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING not supported
napi_uint8_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL
napi_uint16_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16 FLOAT16 uses Uint16Array
napi_float64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE
napi_uint32_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32
napi_biguint64_array, // ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64
std::underlying_type_t<napi_typedarray_type>(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX64 not supported
std::underlying_type_t<napi_typedarray_type>(-1), // ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX128 not supported
std::underlying_type_t<napi_typedarray_type>(-1) // ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16 not supported
};
static_assert(sizeof(DATA_TYPE_TYPEDARRAY_MAP) == sizeof(napi_typedarray_type) * ONNX_TENSOR_ELEMENT_DATA_TYPE_COUNT,
"definition not matching");
@ -98,7 +98,20 @@ static_assert(sizeof(DATA_TYPE_ID_TO_NAME_MAP) == sizeof(const char*) * ONNX_TEN
"definition not matching");
const std::unordered_map<std::string, ONNXTensorElementDataType> DATA_TYPE_NAME_TO_ID_MAP = {
{"float32", ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT}, {"uint8", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8}, {"int8", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8}, {"uint16", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16}, {"int16", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16}, {"int32", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32}, {"int64", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64}, {"string", ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING}, {"bool", ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL}, {"float16", ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16}, {"float64", ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE}, {"uint32", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32}, {"uint64", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64}};
{"float32", ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT},
{"uint8", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8},
{"int8", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8},
{"uint16", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16},
{"int16", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16},
{"int32", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32},
{"int64", ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64},
{"string", ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING},
{"bool", ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL},
{"float16", ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16},
{"float64", ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE},
{"uint32", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32},
{"uint64", ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64},
};
// currently only support tensor
Ort::Value NapiValueToOrtValue(Napi::Env env, Napi::Value value, OrtMemoryInfo* cpu_memory_info, OrtMemoryInfo* webgpu_memory_info) {
@ -181,7 +194,7 @@ Ort::Value NapiValueToOrtValue(Napi::Env env, Napi::Value value, OrtMemoryInfo*
"Tensor.data must be a typed array for numeric tensor.");
auto tensorDataTypedArray = tensorDataValue.As<Napi::TypedArray>();
auto typedArrayType = tensorDataValue.As<Napi::TypedArray>().TypedArrayType();
std::underlying_type_t<napi_typedarray_type> typedArrayType = tensorDataValue.As<Napi::TypedArray>().TypedArrayType();
ORT_NAPI_THROW_TYPEERROR_IF(DATA_TYPE_TYPEDARRAY_MAP[elemType] != typedArrayType, env,
"Tensor.data must be a typed array (", DATA_TYPE_TYPEDARRAY_MAP[elemType], ") for ",
tensorTypeString, " tensors, but got typed array (", typedArrayType, ").");
@ -294,7 +307,7 @@ Napi::Value OrtValueToNapiValue(Napi::Env env, Ort::Value&& value) {
}
napi_value typedArrayData;
napi_status status =
napi_create_typedarray(env, DATA_TYPE_TYPEDARRAY_MAP[elemType], size, arrayBuffer, 0, &typedArrayData);
napi_create_typedarray(env, (napi_typedarray_type)DATA_TYPE_TYPEDARRAY_MAP[elemType], size, arrayBuffer, 0, &typedArrayData);
NAPI_THROW_IF_FAILED(env, status, Napi::Value);
// new Tensor(type, typedArrayData, dims)