// Copyright 2018 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
// Next MinVersion: 6
// Datatypes and interfaces of models for the Machine Learning API.
// NOTE: This mojom exists in two places and must be kept in sync:
// Chromium: //chromeos/services/machine_learning/public/mojom/
// Chrome OS: src/platform2/ml/mojom/
// Note: Other repos downstream of Chromium might also use this mojom.
// Example: A backwards-compatible mojom change (and corresponding
// implementation change) can be made in Chrome OS first, then replicated to the
// clients (Chromium, other downstream repos) later.
// Use //chromeos/services/machine_learning/public/mojom/roll_mojoms.sh to help
// replicate Chrome OS-side changes over to Chromium.
module chromeos.machine_learning.mojom;
// NOTE: The base directory for 'import' statements is expected to differ
// between Chromium and Chrome OS versions of this file.
import "chromeos/services/machine_learning/public/mojom/graph_executor.mojom";
// These values are persisted to logs. Entries should not be renumbered and
// numeric values should never be reused.
// ModelIds prefixed with UNSUPPORTED_ are no longer supported. Attempts to load
// them will produce an error.
[Stable, Extensible]
enum BuiltinModelId {
// Unknown ML model. It is marked as unsupported.
UNSUPPORTED_UNKNOWN = 0,
// Test ML model.
TEST_MODEL = 1,
// The Smart Dim (20181115) ML model.
UNSUPPORTED_SMART_DIM_20181115 = 2,
// The Smart Dim (20190221) ML model.
UNSUPPORTED_SMART_DIM_20190221 = 3,
// The Top Cat (20190722) ML model.
UNSUPPORTED_TOP_CAT_20190722 = 4,
// The Smart Dim (20190521) ML model.
SMART_DIM_20190521 = 5,
// The Search Ranker (20190923) ML model.
UNSUPPORTED_SEARCH_RANKER_20190923 = 6,
// The Adaptive Charging (20211105) ML model.
[MinVersion=1] UNSUPPORTED_ADAPTIVE_CHARGING_20211105 = 7,
// The Poncho Palm Rejection ML test model.
[MinVersion=2] UNSUPPORTED_PONCHO_PALM_REJECTION_20230213 = 8,
// The Adaptive Charging (20230314) ML model.
[MinVersion=3] ADAPTIVE_CHARGING_20230314= 9,
// The Poncho Palm Rejection ML model v0.
[MinVersion=4] PONCHO_PALM_REJECTION_20230907 = 10,
// Poncho Geralt first test model
[MinVersion=5] PONCHO_PALM_REJECTION_20240313 = 11,
};
// Graphics API to use with the GPU delegate.
[Stable, Extensible]
enum GpuDelegateApi {
// Unknown value or not specified.
[Default] UNKNOWN = 0,
// Use OpenGL.
OPENGL = 1,
// Use OpenCL.
OPENCL = 2,
};
// Options for creating the executor. Options are used for testing and
// development. They are not typically used in normal, production code.
[Stable]
struct GraphExecutorOptions {
// Use NNAPI delegate.
bool use_nnapi = false;
// Use GPU delegate.
[MinVersion=1] bool use_gpu = false;
// Graphics API to use with GPU delegate.
[MinVersion=2] GpuDelegateApi gpu_delegate_api = OPENGL;
};
// These values are persisted to logs. Entries should not be renumbered and
// numeric values should never be reused.
// Keep this enum in sync with
// MachineLearningServiceCreateGraphExecutorResultEvent in
// tools/metrics/histograms/metadata/cros_ml/enums.xml.
[Stable, Extensible]
enum CreateGraphExecutorResult {
OK = 0,
MODEL_INTERPRETATION_ERROR = 1,
MEMORY_ALLOCATION_ERROR = 2,
NNAPI_UNAVAILABLE = 3,
NNAPI_USE_ERROR = 4,
[MinVersion=1] GPU_UNAVAILABLE = 5,
[MinVersion=1] GPU_USE_ERROR = 6,
[MinVersion=1] DELEGATE_CONFIG_ERROR = 7,
[MinVersion=1] NOT_FULLY_DELEGABLE = 8,
};
// Model specification for builtin models.
// Because ml-service can retrieve a builtin model's content and metadata, only
// an `id` is needed to specify it.
[Stable]
struct BuiltinModelSpec {
BuiltinModelId id;
};
// Model specification for downloaded models.
// For a downloaded model, both of the model content and metadata must be
// specified.
[Stable]
struct FlatBufferModelSpec {
// The content of the model's tflite model file.
string model_string;
// A map from input nodes' names to their indices.
map<string, int32> inputs;
// A map from output nodes' names to their indices.
map<string, int32> outputs;
// Used in naming the UMA metric histograms of the model. An example of the
// names of the histograms is:
//
// MachineLearningService.`metrics_model_name`.ExecuteResult.CpuTimeMicrosec
//
// This variable must NOT be empty.
string metrics_model_name;
};
// The lifetime of the cached model is tied to the lifetime of the Model
// interface pipe. The Model interface pipe can be used to acquire multiple
// separate GraphExecutor instances.
// Next ordinal: 2
[Stable]
interface Model {
// Deprecated messages:
REMOVED_0@0(pending_receiver<GraphExecutor> receiver) =>
(CreateGraphExecutorResult result);
// Creates a new GraphExecutor with the specified `options` and binds it to
// `receiver`. The GraphExecutor can be used to repeatedly evaluate this
// `Model`.
// * A Model can have more than one GraphExecutor.
// * Releasing this GraphExecutor frees the associated memory (but
// doesn't free the Model unless its pipe is also closed).
CreateGraphExecutor@1(GraphExecutorOptions options,
pending_receiver<GraphExecutor> receiver) =>
(CreateGraphExecutorResult result);
};