mirror of
https://github.com/saymrwulf/onnxruntime.git
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c615002f5d
* commetns for dml graph transformer fixed ort value passing using the allocatir info * fixed and coded maps and sequences across the abi * cleaned up w4's cleaned up the model info ABI delayload directml.dll from winml * cleaned up namepsace aliases. renamed _winmla to winmla this was good PR feedback from tiago a while back. * moved files from inc to lib\api.core cleaned up some of the cmake * staged changes
87 lines
2.6 KiB
C++
87 lines
2.6 KiB
C++
// Copyright (c) Microsoft Corporation.
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// Licensed under the MIT License.
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#include "pch.h"
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#ifdef USE_DML
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#include "AbiCustomRegistryImpl.h"
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namespace Windows::AI::MachineLearning::Adapter {
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HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorSetSchema(
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const MLOperatorSetId* opSetId,
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int baseline_version,
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const MLOperatorSchemaDescription* const* schema,
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uint32_t schemaCount,
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_In_opt_ IMLOperatorTypeInferrer* typeInferrer,
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_In_opt_ IMLOperatorShapeInferrer* shapeInferrer) const noexcept try {
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#ifdef LAYERING_DONE
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for (uint32_t i = 0; i < schemaCount; ++i) {
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telemetry_helper.RegisterOperatorSetSchema(
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schema[i]->name,
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schema[i]->inputCount,
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schema[i]->outputCount,
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schema[i]->typeConstraintCount,
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schema[i]->attributeCount,
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schema[i]->defaultAttributeCount);
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}
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#endif
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// Delegate to base class
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return AbiCustomRegistry::RegisterOperatorSetSchema(
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opSetId,
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baseline_version,
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schema,
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schemaCount,
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typeInferrer,
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shapeInferrer);
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}
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CATCH_RETURN();
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HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorKernel(
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const MLOperatorKernelDescription* opKernel,
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IMLOperatorKernelFactory* operatorKernelFactory,
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_In_opt_ IMLOperatorShapeInferrer* shapeInferrer) const noexcept {
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return RegisterOperatorKernel(opKernel, operatorKernelFactory, shapeInferrer, false, false, false);
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}
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HRESULT STDMETHODCALLTYPE AbiCustomRegistryImpl::RegisterOperatorKernel(
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const MLOperatorKernelDescription* opKernel,
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IMLOperatorKernelFactory* operatorKernelFactory,
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_In_opt_ IMLOperatorShapeInferrer* shapeInferrer,
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bool isInternalOperator,
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bool canAliasFirstInput,
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bool supportsGraph,
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const uint32_t* requiredInputCountForGraph,
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bool requiresFloatFormatsForGraph,
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_In_reads_(constantCpuInputCount) const uint32_t* requiredConstantCpuInputs,
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uint32_t constantCpuInputCount) const noexcept try {
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#ifdef LAYERING_DONE
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// Log a custom op telemetry if the operator is not a built-in DML operator
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if (!isInternalOperator) {
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telemetry_helper.LogRegisterOperatorKernel(
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opKernel->name,
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opKernel->domain,
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static_cast<int>(opKernel->executionType));
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}
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#endif
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// Delegate to base class
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return AbiCustomRegistry::RegisterOperatorKernel(
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opKernel,
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operatorKernelFactory,
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shapeInferrer,
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isInternalOperator,
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canAliasFirstInput,
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supportsGraph,
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requiredInputCountForGraph,
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requiresFloatFormatsForGraph,
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requiredConstantCpuInputs,
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constantCpuInputCount);
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}
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CATCH_RETURN();
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} // namespace Windows::AI::MachineLearning::Adapter
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#endif USE_DML
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