exclude some objc files
This commit is contained in:
rachguo
@@ -1,9 +0,0 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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// this header contains the entire ONNX Runtime training Objective-C API
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// the headers below can also be imported individually
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#import "onnxruntime.h"
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#import "ort_checkpoint.h"
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#import "ort_training_session.h"
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@@ -1,119 +0,0 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#import <Foundation/Foundation.h>
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#include <stdint.h>
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NS_ASSUME_NONNULL_BEGIN
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/**
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* An ORT checkpoint is a snapshot of the state of a model at a given point in time.
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*
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* This class holds the entire training session state that includes model parameters,
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* their gradients, optimizer parameters, and user properties. The `ORTTrainingSession` leverages the
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* `ORTCheckpoint` by accessing and updating the contained training state.
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*
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* Available since 1.16.
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*
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* @note This class is only available when the training APIs are enabled.
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*/
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@interface ORTCheckpoint : NSObject
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- (instancetype)init NS_UNAVAILABLE;
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/**
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* Creates a checkpoint from directory on disk.
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*
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* @param path The path to the checkpoint directory.
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* @param error Optional error information set if an error occurs.
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* @return The instance, or nil if an error occurs.
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*
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* @warning The construction of the checkpoint state requires instantiation of `ORTEnv`.
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* The intialization will fail if the `ORTEnv` is not properly initialized.
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*/
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- (nullable instancetype)initWithPath:(NSString*)path
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error:(NSError**)error NS_DESIGNATED_INITIALIZER;
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/**
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* Saves a checkpoint to directory on disk.
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*
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* @param path The path to the checkpoint directory.
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* @param includeOptimizerState Flag to indicate whether to save the optimizer state or not.
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* @param error Optional error information set if an error occurs.
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* @return Whether the checkpoint was saved successfully.
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*/
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- (BOOL)saveCheckpointToPath:(NSString*)path
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withOptimizerState:(BOOL)includeOptimizerState
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error:(NSError**)error;
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/**
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* Adds an int property to this checkpoint.
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*
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* @param name The name of the property.
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* @param value The value of the property.
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* @param error Optional error information set if an error occurs.
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* @return Whether the property was added successfully.
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*/
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- (BOOL)addIntPropertyWithName:(NSString*)name
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value:(int64_t)value
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error:(NSError**)error;
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/**
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* Adds a float property to this checkpoint.
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*
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* @param name The name of the property.
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* @param value The value of the property.
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* @param error Optional error information set if an error occurs.
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* @return Whether the property was added successfully.
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*/
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- (BOOL)addFloatPropertyWithName:(NSString*)name
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value:(float)value
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error:(NSError**)error;
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/**
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* Adds a string property to this checkpoint.
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*
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* @param name The name of the property.
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* @param value The value of the property.
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* @param error Optional error information set if an error occurs.
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* @return Whether the property was added successfully.
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*/
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- (BOOL)addStringPropertyWithName:(NSString*)name
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value:(NSString*)value
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error:(NSError**)error;
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/**
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* Gets an int property from this checkpoint.
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*
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* @param name The name of the property.
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* @param error Optional error information set if an error occurs.
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* @return The value of the property or 0 if an error occurs.
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*/
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- (int64_t)getIntPropertyWithName:(NSString*)name
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error:(NSError**)error __attribute__((swift_error(nonnull_error)));
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/**
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* Gets a float property from this checkpoint.
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*
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* @param name The name of the property.
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* @param error Optional error information set if an error occurs.
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* @return The value of the property or 0.0f if an error occurs.
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*/
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- (float)getFloatPropertyWithName:(NSString*)name
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error:(NSError**)error __attribute__((swift_error(nonnull_error)));
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/**
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*
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* Gets a string property from this checkpoint.
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*
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* @param name The name of the property.
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* @param error Optional error information set if an error occurs.
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* @return The value of the property.
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*/
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- (nullable NSString*)getStringPropertyWithName:(NSString*)name
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error:(NSError**)error __attribute__((swift_error(nonnull_error)));
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@end
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NS_ASSUME_NONNULL_END
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@@ -1,263 +0,0 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#import <Foundation/Foundation.h>
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#include <stdint.h>
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NS_ASSUME_NONNULL_BEGIN
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@class ORTCheckpoint;
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@class ORTEnv;
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@class ORTValue;
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@class ORTSessionOptions;
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/**
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* Trainer class that provides methods to train, evaluate and optimize ONNX models.
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*
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* The training session requires four training artifacts:
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* 1. Training onnx model
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* 2. Evaluation onnx model (optional)
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* 3. Optimizer onnx model
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* 4. Checkpoint directory
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*
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* [onnxruntime-training python utility](https://github.com/microsoft/onnxruntime/blob/main/orttraining/orttraining/python/training/onnxblock/README.md)
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* can be used to generate above training artifacts.
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*
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* Available since 1.16.
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*
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* @note This class is only available when the training APIs are enabled.
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*/
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@interface ORTTrainingSession : NSObject
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- (instancetype)init NS_UNAVAILABLE;
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/**
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* Creates a training session from the training artifacts that can be used to begin or resume training.
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*
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* The initializer instantiates the training session based on provided env and session options, which can be used to
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* begin or resume training from a given checkpoint state. The checkpoint state represents the parameters of training
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* session which will be moved to the device specified in the session option if needed.
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*
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* @param env The `ORTEnv` instance to use for the training session.
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* @param sessionOptions The `ORTSessionOptions` to use for the training session.
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* @param checkpoint Training states that are used as a starting point for training.
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* @param trainModelPath The path to the training onnx model.
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* @param evalModelPath The path to the evaluation onnx model.
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* @param optimizerModelPath The path to the optimizer onnx model used to perform gradient descent.
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* @param error Optional error information set if an error occurs.
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* @return The instance, or nil if an error occurs.
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*
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* @note Note that the training session created with a checkpoint state uses this state to store the entire training
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* state (including model parameters, its gradients, the optimizer states and the properties). The training session
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* keeps a strong (owning) pointer to the checkpoint state.
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*/
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- (nullable instancetype)initWithEnv:(ORTEnv*)env
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sessionOptions:(ORTSessionOptions*)sessionOptions
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checkpoint:(ORTCheckpoint*)checkpoint
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trainModelPath:(NSString*)trainModelPath
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evalModelPath:(nullable NSString*)evalModelPath
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optimizerModelPath:(nullable NSString*)optimizerModelPath
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error:(NSError**)error NS_DESIGNATED_INITIALIZER;
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/**
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* Performs a training step, which is equivalent to a forward and backward propagation in a single step.
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*
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* The training step computes the outputs of the training model and the gradients of the trainable parameters
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* for the given input values. The train step is performed based on the training model that was provided to the training session.
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* It is equivalent to running forward and backward propagation in a single step. The computed gradients are stored inside
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* the training session state so they can be later consumed by `optimizerStep`. The gradients can be lazily reset by
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* calling `lazyResetGrad` method.
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*
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* @param inputs The input values to the training model.
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* @param error Optional error information set if an error occurs.
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* @return The output values of the training model.
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*/
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- (nullable NSArray<ORTValue*>*)trainStepWithInputValues:(NSArray<ORTValue*>*)inputs
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error:(NSError**)error;
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/**
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* Performs a evaluation step that computes the outputs of the evaluation model for the given inputs.
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* The eval step is performed based on the evaluation model that was provided to the training session.
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*
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* @param inputs The input values to the eval model.
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* @param error Optional error information set if an error occurs.
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* @return The output values of the eval model.
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*
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*/
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- (nullable NSArray<ORTValue*>*)evalStepWithInputValues:(NSArray<ORTValue*>*)inputs
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error:(NSError**)error;
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/**
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* Reset the gradients of all trainable parameters to zero lazily.
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*
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* Calling this method sets the internal state of the training session such that the gradients of the trainable parameters
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* in the ORTCheckpoint will be scheduled to be reset just before the new gradients are computed on the next
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* invocation of the `trainStep` method.
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*
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* @param error Optional error information set if an error occurs.
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* @return YES if the gradients are set to reset successfully, NO otherwise.
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*/
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- (BOOL)lazyResetGradWithError:(NSError**)error;
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/**
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* Performs the weight updates for the trainable parameters using the optimizer model. The optimizer step is performed
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* based on the optimizer model that was provided to the training session. The updated parameters are stored inside the
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* training state so that they can be used by the next `trainStep` method call.
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*
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* @param error Optional error information set if an error occurs.
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* @return YES if the optimizer step was performed successfully, NO otherwise.
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*/
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- (BOOL)optimizerStepWithError:(NSError**)error;
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/**
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* Returns the names of the user inputs for the training model that can be associated with
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* the `ORTValue` provided to the `trainStep`.
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*
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* @param error Optional error information set if an error occurs.
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* @return The names of the user inputs for the training model.
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*/
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- (nullable NSArray<NSString*>*)getTrainInputNamesWithError:(NSError**)error;
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/**
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* Returns the names of the user inputs for the evaluation model that can be associated with
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* the `ORTValue` provided to the `evalStep`.
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*
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* @param error Optional error information set if an error occurs.
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* @return The names of the user inputs for the evaluation model.
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*/
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- (nullable NSArray<NSString*>*)getEvalInputNamesWithError:(NSError**)error;
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/**
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* Returns the names of the user outputs for the training model that can be associated with
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* the `ORTValue` returned by the `trainStep`.
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*
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* @param error Optional error information set if an error occurs.
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* @return The names of the user outputs for the training model.
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*/
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- (nullable NSArray<NSString*>*)getTrainOutputNamesWithError:(NSError**)error;
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/**
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* Returns the names of the user outputs for the evaluation model that can be associated with
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* the `ORTValue` returned by the `evalStep`.
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*
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* @param error Optional error information set if an error occurs.
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* @return The names of the user outputs for the evaluation model.
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*/
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- (nullable NSArray<NSString*>*)getEvalOutputNamesWithError:(NSError**)error;
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/**
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* Registers a linear learning rate scheduler for the training session.
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*
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* The scheduler gradually decreases the learning rate from the initial value to zero over the course of the training.
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* The decrease is performed by multiplying the current learning rate by a linearly updated factor.
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* Before the decrease, the learning rate is gradually increased from zero to the initial value during a warmup phase.
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*
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* @param warmupStepCount The number of steps to perform the linear warmup.
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* @param totalStepCount The total number of steps to perform the linear decay.
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* @param initialLr The initial learning rate.
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* @param error Optional error information set if an error occurs.
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* @return YES if the scheduler was registered successfully, NO otherwise.
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*/
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- (BOOL)registerLinearLRSchedulerWithWarmupStepCount:(int64_t)warmupStepCount
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totalStepCount:(int64_t)totalStepCount
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initialLr:(float)initialLr
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error:(NSError**)error;
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/**
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* Update the learning rate based on the registered learning rate scheduler.
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*
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* Performs a scheduler step that updates the learning rate that is being used by the training session.
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* This function should typically be called before invoking the optimizer step for each round, or as necessary
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* to update the learning rate being used by the training session.
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*
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* @note A valid predefined learning rate scheduler must be first registered to invoke this method.
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*
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* @param error Optional error information set if an error occurs.
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* @return YES if the scheduler step was performed successfully, NO otherwise.
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*/
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- (BOOL)schedulerStepWithError:(NSError**)error;
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/**
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* Returns the current learning rate being used by the training session.
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*
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* @param error Optional error information set if an error occurs.
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* @return The current learning rate or 0.0f if an error occurs.
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*/
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- (float)getLearningRateWithError:(NSError**)error __attribute__((swift_error(nonnull_error)));
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/**
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* Sets the learning rate being used by the training session.
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*
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* The current learning rate is maintained by the training session and can be overwritten by invoking this method
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* with the desired learning rate. This function should not be used when a valid learning rate scheduler is registered.
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* It should be used either to set the learning rate derived from a custom learning rate scheduler or to set a constant
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* learning rate to be used throughout the training session.
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*
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* @note It does not set the initial learning rate that may be needed by the predefined learning rate schedulers.
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* To set the initial learning rate for learning rate schedulers, use the `registerLinearLRScheduler` method.
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*
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* @param lr The learning rate to be used by the training session.
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* @param error Optional error information set if an error occurs.
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* @return YES if the learning rate was set successfully, NO otherwise.
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*/
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- (BOOL)setLearningRate:(float)lr
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error:(NSError**)error;
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/**
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* Loads the training session model parameters from a contiguous buffer.
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*
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* @param buffer Contiguous buffer to load the parameters from.
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* @param error Optional error information set if an error occurs.
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* @return YES if the parameters were loaded successfully, NO otherwise.
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*/
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- (BOOL)fromBufferWithValue:(ORTValue*)buffer
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error:(NSError**)error;
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||||
|
||||
/**
|
||||
* Returns a contiguous buffer that holds a copy of all training state parameters.
|
||||
*
|
||||
* @param onlyTrainable If YES, returns a buffer that holds only the trainable parameters, otherwise returns a buffer
|
||||
* that holds all the parameters.
|
||||
* @param error Optional error information set if an error occurs.
|
||||
* @return A contiguous buffer that holds a copy of all training state parameters.
|
||||
*/
|
||||
- (nullable ORTValue*)toBufferWithTrainable:(BOOL)onlyTrainable
|
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error:(NSError**)error;
|
||||
|
||||
/**
|
||||
* Exports the training session model that can be used for inference.
|
||||
*
|
||||
* If the training session was provided with an eval model, the training session can generate an inference model if it
|
||||
* knows the inference graph outputs. The input inference graph outputs are used to prune the eval model so that the
|
||||
* inference model's outputs align with the provided outputs. The exported model is saved at the path provided and
|
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* can be used for inferencing with `ORTSession`.
|
||||
*
|
||||
* @note The method reloads the eval model from the path provided to the initializer and expects this path to be valid.
|
||||
*
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||||
* @param inferenceModelPath The path to the serialized the inference model.
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||||
* @param graphOutputNames The names of the outputs that are needed in the inference model.
|
||||
* @param error Optional error information set if an error occurs.
|
||||
* @return YES if the inference model was exported successfully, NO otherwise.
|
||||
*/
|
||||
- (BOOL)exportModelForInferenceWithOutputPath:(NSString*)inferenceModelPath
|
||||
graphOutputNames:(NSArray<NSString*>*)graphOutputNames
|
||||
error:(NSError**)error;
|
||||
@end
|
||||
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
/**
|
||||
* This function sets the seed for generating random numbers.
|
||||
* Use this function to generate reproducible results. It should be noted that completely reproducible results are not guaranteed.
|
||||
*
|
||||
* @param seed Manually set seed to use for random number generation.
|
||||
*/
|
||||
void ORTSetSeed(int64_t seed);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
|
||||
NS_ASSUME_NONNULL_END
|
||||
@@ -1,111 +0,0 @@
|
||||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// Licensed under the MIT License.
|
||||
|
||||
#import "ort_checkpoint_internal.h"
|
||||
|
||||
#include <optional>
|
||||
#include <string>
|
||||
#include <variant>
|
||||
#import "cxx_api.h"
|
||||
|
||||
#import "error_utils.h"
|
||||
|
||||
NS_ASSUME_NONNULL_BEGIN
|
||||
|
||||
@implementation ORTCheckpoint {
|
||||
std::optional<Ort::CheckpointState> _checkpoint;
|
||||
}
|
||||
|
||||
- (nullable instancetype)initWithPath:(NSString*)path
|
||||
error:(NSError**)error {
|
||||
if ((self = [super init]) == nil) {
|
||||
return nil;
|
||||
}
|
||||
|
||||
try {
|
||||
_checkpoint = Ort::CheckpointState::LoadCheckpoint(path.UTF8String);
|
||||
return self;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (BOOL)saveCheckpointToPath:(NSString*)path
|
||||
withOptimizerState:(BOOL)includeOptimizerState
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
Ort::CheckpointState::SaveCheckpoint([self CXXAPIOrtCheckpoint], path.UTF8String, includeOptimizerState);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)addIntPropertyWithName:(NSString*)name
|
||||
value:(int64_t)value
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtCheckpoint].AddProperty(name.UTF8String, value);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)addFloatPropertyWithName:(NSString*)name
|
||||
value:(float)value
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtCheckpoint].AddProperty(name.UTF8String, value);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)addStringPropertyWithName:(NSString*)name
|
||||
value:(NSString*)value
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtCheckpoint].AddProperty(name.UTF8String, value.UTF8String);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (nullable NSString*)getStringPropertyWithName:(NSString*)name error:(NSError**)error {
|
||||
try {
|
||||
Ort::Property value = [self CXXAPIOrtCheckpoint].GetProperty(name.UTF8String);
|
||||
if (std::string* str = std::get_if<std::string>(&value)) {
|
||||
return [NSString stringWithUTF8String:str->c_str()];
|
||||
}
|
||||
ORT_CXX_API_THROW("Property is not a string.", ORT_INVALID_ARGUMENT);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (int64_t)getIntPropertyWithName:(NSString*)name error:(NSError**)error {
|
||||
try {
|
||||
Ort::Property value = [self CXXAPIOrtCheckpoint].GetProperty(name.UTF8String);
|
||||
if (int64_t* i = std::get_if<int64_t>(&value)) {
|
||||
return *i;
|
||||
}
|
||||
ORT_CXX_API_THROW("Property is not an integer.", ORT_INVALID_ARGUMENT);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH(error, 0)
|
||||
}
|
||||
|
||||
- (float)getFloatPropertyWithName:(NSString*)name error:(NSError**)error {
|
||||
try {
|
||||
Ort::Property value = [self CXXAPIOrtCheckpoint].GetProperty(name.UTF8String);
|
||||
if (float* f = std::get_if<float>(&value)) {
|
||||
return *f;
|
||||
}
|
||||
ORT_CXX_API_THROW("Property is not a float.", ORT_INVALID_ARGUMENT);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH(error, 0.0f)
|
||||
}
|
||||
|
||||
- (Ort::CheckpointState&)CXXAPIOrtCheckpoint {
|
||||
return *_checkpoint;
|
||||
}
|
||||
|
||||
@end
|
||||
|
||||
NS_ASSUME_NONNULL_END
|
||||
@@ -1,16 +0,0 @@
|
||||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// Licensed under the MIT License.
|
||||
|
||||
#import "ort_checkpoint.h"
|
||||
|
||||
#import "cxx_api.h"
|
||||
|
||||
NS_ASSUME_NONNULL_BEGIN
|
||||
|
||||
@interface ORTCheckpoint ()
|
||||
|
||||
- (Ort::CheckpointState&)CXXAPIOrtCheckpoint;
|
||||
|
||||
@end
|
||||
|
||||
NS_ASSUME_NONNULL_END
|
||||
@@ -1,224 +0,0 @@
|
||||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// Licensed under the MIT License.
|
||||
|
||||
#import "ort_training_session_internal.h"
|
||||
|
||||
#import <vector>
|
||||
#import <optional>
|
||||
#import <string>
|
||||
|
||||
#import "cxx_api.h"
|
||||
#import "cxx_utils.h"
|
||||
#import "error_utils.h"
|
||||
#import "ort_checkpoint_internal.h"
|
||||
#import "ort_session_internal.h"
|
||||
#import "ort_enums_internal.h"
|
||||
#import "ort_env_internal.h"
|
||||
#import "ort_value_internal.h"
|
||||
|
||||
NS_ASSUME_NONNULL_BEGIN
|
||||
|
||||
@implementation ORTTrainingSession {
|
||||
std::optional<Ort::TrainingSession> _session;
|
||||
ORTCheckpoint* _checkpoint;
|
||||
}
|
||||
|
||||
- (Ort::TrainingSession&)CXXAPIOrtTrainingSession {
|
||||
return *_session;
|
||||
}
|
||||
|
||||
- (nullable instancetype)initWithEnv:(ORTEnv*)env
|
||||
sessionOptions:(ORTSessionOptions*)sessionOptions
|
||||
checkpoint:(ORTCheckpoint*)checkpoint
|
||||
trainModelPath:(NSString*)trainModelPath
|
||||
evalModelPath:(nullable NSString*)evalModelPath
|
||||
optimizerModelPath:(nullable NSString*)optimizerModelPath
|
||||
error:(NSError**)error {
|
||||
if ((self = [super init]) == nil) {
|
||||
return nil;
|
||||
}
|
||||
|
||||
try {
|
||||
std::optional<std::string> evalPath = utils::toStdOptionalString(evalModelPath);
|
||||
std::optional<std::string> optimizerPath = utils::toStdOptionalString(optimizerModelPath);
|
||||
|
||||
_checkpoint = checkpoint;
|
||||
_session = Ort::TrainingSession{
|
||||
[env CXXAPIOrtEnv],
|
||||
[sessionOptions CXXAPIOrtSessionOptions],
|
||||
[checkpoint CXXAPIOrtCheckpoint],
|
||||
trainModelPath.UTF8String,
|
||||
evalPath,
|
||||
optimizerPath};
|
||||
return self;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (nullable NSArray<ORTValue*>*)trainStepWithInputValues:(NSArray<ORTValue*>*)inputs
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
std::vector<const OrtValue*> inputValues = utils::getWrappedCAPIOrtValues(inputs);
|
||||
|
||||
size_t outputCount;
|
||||
Ort::ThrowOnError(Ort::GetTrainingApi().TrainingSessionGetTrainingModelOutputCount(*_session, &outputCount));
|
||||
std::vector<OrtValue*> outputValues(outputCount, nullptr);
|
||||
|
||||
Ort::RunOptions runOptions;
|
||||
Ort::ThrowOnError(Ort::GetTrainingApi().TrainStep(
|
||||
*_session,
|
||||
runOptions,
|
||||
inputValues.size(),
|
||||
inputValues.data(),
|
||||
outputValues.size(),
|
||||
outputValues.data()));
|
||||
|
||||
return utils::wrapUnownedCAPIOrtValues(outputValues, error);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
- (nullable NSArray<ORTValue*>*)evalStepWithInputValues:(NSArray<ORTValue*>*)inputs
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
// create vector of OrtValue from NSArray<ORTValue*> with same size as inputValues
|
||||
std::vector<const OrtValue*> inputValues = utils::getWrappedCAPIOrtValues(inputs);
|
||||
|
||||
size_t outputCount;
|
||||
Ort::ThrowOnError(Ort::GetTrainingApi().TrainingSessionGetEvalModelOutputCount(*_session, &outputCount));
|
||||
std::vector<OrtValue*> outputValues(outputCount, nullptr);
|
||||
|
||||
Ort::RunOptions runOptions;
|
||||
Ort::ThrowOnError(Ort::GetTrainingApi().EvalStep(
|
||||
*_session,
|
||||
runOptions,
|
||||
inputValues.size(),
|
||||
inputValues.data(),
|
||||
outputValues.size(),
|
||||
outputValues.data()));
|
||||
|
||||
return utils::wrapUnownedCAPIOrtValues(outputValues, error);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (BOOL)lazyResetGradWithError:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].LazyResetGrad();
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)optimizerStepWithError:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].OptimizerStep();
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (nullable NSArray<NSString*>*)getTrainInputNamesWithError:(NSError**)error {
|
||||
try {
|
||||
std::vector<std::string> inputNames = [self CXXAPIOrtTrainingSession].InputNames(true);
|
||||
return utils::toNSStringNSArray(inputNames);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (nullable NSArray<NSString*>*)getTrainOutputNamesWithError:(NSError**)error {
|
||||
try {
|
||||
std::vector<std::string> outputNames = [self CXXAPIOrtTrainingSession].OutputNames(true);
|
||||
return utils::toNSStringNSArray(outputNames);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (nullable NSArray<NSString*>*)getEvalInputNamesWithError:(NSError**)error {
|
||||
try {
|
||||
std::vector<std::string> inputNames = [self CXXAPIOrtTrainingSession].InputNames(false);
|
||||
return utils::toNSStringNSArray(inputNames);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (nullable NSArray<NSString*>*)getEvalOutputNamesWithError:(NSError**)error {
|
||||
try {
|
||||
std::vector<std::string> outputNames = [self CXXAPIOrtTrainingSession].OutputNames(false);
|
||||
return utils::toNSStringNSArray(outputNames);
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (BOOL)registerLinearLRSchedulerWithWarmupStepCount:(int64_t)warmupStepCount
|
||||
totalStepCount:(int64_t)totalStepCount
|
||||
initialLr:(float)initialLr
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].RegisterLinearLRScheduler(warmupStepCount, totalStepCount, initialLr);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)schedulerStepWithError:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].SchedulerStep();
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (float)getLearningRateWithError:(NSError**)error {
|
||||
try {
|
||||
return [self CXXAPIOrtTrainingSession].GetLearningRate();
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH(error, 0.0f);
|
||||
}
|
||||
|
||||
- (BOOL)setLearningRate:(float)lr
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].SetLearningRate(lr);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (BOOL)fromBufferWithValue:(ORTValue*)buffer
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].FromBuffer([buffer CXXAPIOrtValue]);
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
- (nullable ORTValue*)toBufferWithTrainable:(BOOL)onlyTrainable
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
Ort::Value val = [self CXXAPIOrtTrainingSession].ToBuffer(onlyTrainable);
|
||||
return [[ORTValue alloc] initWithCXXAPIOrtValue:std::move(val)
|
||||
externalTensorData:nil
|
||||
error:error];
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_NULLABLE(error)
|
||||
}
|
||||
|
||||
- (BOOL)exportModelForInferenceWithOutputPath:(NSString*)inferenceModelPath
|
||||
graphOutputNames:(NSArray<NSString*>*)graphOutputNames
|
||||
error:(NSError**)error {
|
||||
try {
|
||||
[self CXXAPIOrtTrainingSession].ExportModelForInferencing(utils::toStdString(inferenceModelPath),
|
||||
utils::toStdStringVector(graphOutputNames));
|
||||
return YES;
|
||||
}
|
||||
ORT_OBJC_API_IMPL_CATCH_RETURNING_BOOL(error)
|
||||
}
|
||||
|
||||
@end
|
||||
|
||||
void ORTSetSeed(int64_t seed) {
|
||||
Ort::SetSeed(seed);
|
||||
}
|
||||
|
||||
NS_ASSUME_NONNULL_END
|
||||
@@ -1,16 +0,0 @@
|
||||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// Licensed under the MIT License.
|
||||
|
||||
#import "ort_training_session.h"
|
||||
|
||||
#import "cxx_api.h"
|
||||
|
||||
NS_ASSUME_NONNULL_BEGIN
|
||||
|
||||
@interface ORTTrainingSession ()
|
||||
|
||||
- (Ort::TrainingSession&)CXXAPIOrtTrainingSession;
|
||||
|
||||
@end
|
||||
|
||||
NS_ASSUME_NONNULL_END
|
||||
Reference in New Issue
Block a user