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// Copyright 2022 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#ifndef THIRD_PARTY_BLINK_RENDERER_MODULES_ML_WEBNN_ML_GRAPH_H_
#define THIRD_PARTY_BLINK_RENDERER_MODULES_ML_WEBNN_ML_GRAPH_H_
#include "base/types/pass_key.h"
#include "services/webnn/public/cpp/operand_descriptor.h"
#include "services/webnn/public/cpp/webnn_trace.h"
#include "services/webnn/public/mojom/webnn_graph.mojom-blink.h"
#include "third_party/blink/renderer/bindings/core/v8/script_promise_resolver.h"
#include "third_party/blink/renderer/bindings/modules/v8/v8_ml_device_type.h"
#include "third_party/blink/renderer/bindings/modules/v8/v8_ml_operand_descriptor.h"
#include "third_party/blink/renderer/modules/modules_export.h"
#include "third_party/blink/renderer/platform/bindings/script_wrappable.h"
#include "third_party/blink/renderer/platform/heap/collection_support/heap_vector.h"
#include "third_party/blink/renderer/platform/heap/member.h"
#include "third_party/blink/renderer/platform/heap/visitor.h"
#include "third_party/blink/renderer/platform/mojo/heap_mojo_associated_remote.h"
namespace blink {
class MLTensor;
class MLContext;
class MLGraphBuilder;
class ExecutionContext;
typedef HeapVector<std::pair<String, Member<MLTensor>>> MLNamedTensors;
// Represents a handle to a compiled, platform-specific computational graph.
class MODULES_EXPORT MLGraph : public ScriptWrappable {
DEFINE_WRAPPERTYPEINFO();
public:
using NamedOperandDescriptors =
HashMap<String, std::optional<webnn::OperandDescriptor>>;
// Instances should only be constructed via `MLGraphBuilder.build()`.
// This method is public as required by the `MakeGarbageCollected` helper.
//
// `pending_graph_remote` is a handle to the computational graph.
// `input_constraints` and `output_constraints` describe the constraints on
// the inputs and outputs which may be used to execute the respective graph.
MLGraph(ExecutionContext* execution_context,
MLContext* context,
mojo::PendingAssociatedRemote<webnn::mojom::blink::WebNNGraph>
pending_graph_remote,
NamedOperandDescriptors input_constraints,
NamedOperandDescriptors output_constraints,
Vector<V8MLDeviceType> devices,
base::PassKey<MLGraphBuilder> pass_key);
MLGraph(const MLGraph&) = delete;
MLGraph& operator=(const MLGraph&) = delete;
~MLGraph() override;
void Trace(Visitor* visitor) const override;
// ml_graph.idl
void destroy();
Vector<V8MLDeviceType> devices() const;
const NamedOperandDescriptors& GetInputConstraints() const;
const NamedOperandDescriptors& GetOutputConstraints() const;
// Execute the compiled platform graph asynchronously.
//
// This method validates the input and output MLNamedTensors against the
// graph's input and output resources info and then executes the compiled
// platform graph.
void Dispatch(webnn::ScopedTrace scoped_trace,
const MLNamedTensors& inputs,
const MLNamedTensors& outputs,
ExceptionState& exception_state);
const MLContext* Context() const;
private:
void OnConnectionError();
// Describes the constraints on the inputs or outputs to this graph.
// Note that `WTF::HashMap` values must be nullable, but
// `webnn::OperandDescriptor` lacks a default constructor, so an optional is
// used. Do not add std::nullopt values to these maps.
const NamedOperandDescriptors input_constraints_;
const NamedOperandDescriptors output_constraints_;
Member<MLContext> ml_context_;
// The `WebNNGraph` is a compiled graph that can be executed by the hardware
// accelerated OS machine learning API.
HeapMojoAssociatedRemote<webnn::mojom::blink::WebNNGraph> remote_graph_;
// Devices that will be used when dispatching the graph.
Vector<V8MLDeviceType> devices_;
};
} // namespace blink
#endif // THIRD_PARTY_BLINK_RENDERER_MODULES_ML_WEBNN_ML_GRAPH_H_
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