mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-18 21:21:17 +00:00
8b0c2e1f3d
Add `support64BitTensorsViaEmulation` to the internal registration info, that informs the graph partitioner that int64 is supported via emulation, even if the device doesn't support it natively. See further description in the corresponding WindowsAI DML PR: https://dev.azure.com/microsoft/WindowsAI/_git/WindowsAI/pullrequest/6101182 Note a later PR will most likely *delete* this newly added flag and simplify much of the existing logic, even deleting the strides hack completely ^__^... Related work items: #28761231
95 lines
3 KiB
C++
95 lines
3 KiB
C++
// Copyright (c) Microsoft Corporation. All rights reserved.
|
|
// Licensed under the MIT License.
|
|
|
|
#include "pch.h"
|
|
|
|
#ifdef USE_DML
|
|
|
|
#include "abi_custom_registry_impl.h"
|
|
|
|
namespace Windows::AI::MachineLearning::Adapter {
|
|
|
|
HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorSetSchema(
|
|
const MLOperatorSetId* opSetId,
|
|
int baseline_version,
|
|
const MLOperatorSchemaDescription* const* schema,
|
|
uint32_t schemaCount,
|
|
_In_opt_ IMLOperatorTypeInferrer* typeInferrer,
|
|
_In_opt_ IMLOperatorShapeInferrer* shapeInferrer) const noexcept try {
|
|
#ifdef LAYERING_DONE
|
|
for (uint32_t i = 0; i < schemaCount; ++i) {
|
|
telemetry_helper.RegisterOperatorSetSchema(
|
|
schema[i]->name,
|
|
schema[i]->inputCount,
|
|
schema[i]->outputCount,
|
|
schema[i]->typeConstraintCount,
|
|
schema[i]->attributeCount,
|
|
schema[i]->defaultAttributeCount);
|
|
}
|
|
#endif
|
|
|
|
// Delegate to base class
|
|
return AbiCustomRegistry::RegisterOperatorSetSchema(
|
|
opSetId,
|
|
baseline_version,
|
|
schema,
|
|
schemaCount,
|
|
typeInferrer,
|
|
shapeInferrer);
|
|
}
|
|
CATCH_RETURN();
|
|
|
|
HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorKernel(
|
|
const MLOperatorKernelDescription* opKernel,
|
|
IMLOperatorKernelFactory* operatorKernelFactory,
|
|
_In_opt_ IMLOperatorShapeInferrer* shapeInferrer) const noexcept {
|
|
return RegisterOperatorKernel(opKernel, operatorKernelFactory, shapeInferrer, nullptr, false, false, false);
|
|
}
|
|
|
|
HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorKernel(
|
|
const MLOperatorKernelDescription* opKernel,
|
|
IMLOperatorKernelFactory* operatorKernelFactory,
|
|
_In_opt_ IMLOperatorShapeInferrer* shapeInferrer,
|
|
_In_opt_ IMLOperatorSupportQueryPrivate* supportQuery,
|
|
bool isInternalOperator,
|
|
bool canAliasFirstInput,
|
|
bool supportsGraph,
|
|
const uint32_t* requiredInputCountForGraph,
|
|
bool supportedWith64BitTensorsVia32BitStrides,
|
|
bool supportedWith64BitTensorsVia32BitStridesFromAnyEp,
|
|
bool prefer64BitTensorsDirectly,
|
|
bool support64BitTensorsViaEmulation,
|
|
_In_reads_(constantCpuInputCount) const uint32_t* requiredConstantCpuInputs,
|
|
uint32_t constantCpuInputCount) const noexcept try {
|
|
#ifdef LAYERING_DONE
|
|
// Log a custom op telemetry if the operator is not a built-in DML operator
|
|
if (!isInternalOperator) {
|
|
telemetry_helper.LogRegisterOperatorKernel(
|
|
opKernel->name,
|
|
opKernel->domain,
|
|
static_cast<int>(opKernel->executionType));
|
|
}
|
|
#endif
|
|
|
|
// Delegate to base class
|
|
return AbiCustomRegistry::RegisterOperatorKernel(
|
|
opKernel,
|
|
operatorKernelFactory,
|
|
shapeInferrer,
|
|
supportQuery,
|
|
isInternalOperator,
|
|
canAliasFirstInput,
|
|
supportsGraph,
|
|
requiredInputCountForGraph,
|
|
supportedWith64BitTensorsVia32BitStrides,
|
|
supportedWith64BitTensorsVia32BitStridesFromAnyEp,
|
|
prefer64BitTensorsDirectly,
|
|
support64BitTensorsViaEmulation,
|
|
requiredConstantCpuInputs,
|
|
constantCpuInputCount);
|
|
}
|
|
CATCH_RETURN();
|
|
|
|
} // namespace Windows::AI::MachineLearning::Adapter
|
|
|
|
#endif USE_DML
|