mindspore.train

Model

mindspore.train.Model

High-Level API for training or inference.

Callback

`mindspore.train.BackupAndRestore`	Callback to back up and restore the parameters during training.
`mindspore.train.Callback`	Abstract base class used to build a Callback class.
`mindspore.train.CheckpointConfig`	The configuration of model checkpoint.
`mindspore.train.EarlyStopping`	Stop training when a monitored metric has stopped improving.
`mindspore.train.History`	Records the network outputs and metrics information into a History object.
`mindspore.train.LambdaCallback`	Callback for creating simple, custom callbacks.
`mindspore.train.LearningRateScheduler`	Change the learning_rate during training.
`mindspore.train.LossMonitor`	Monitor the loss in train or monitor the loss and eval metrics in fit.
`mindspore.train.ModelCheckpoint`	The checkpoint callback class.
`mindspore.train.OnRequestExit`	Respond to the user's closing request, exit the training or eval process, and save the checkpoint and mindir.
`mindspore.train.ReduceLROnPlateau`	Reduce learning rate when the monitor has stopped improving.
`mindspore.train.RunContext`	Hold and manage information about the model.
`mindspore.train.TimeMonitor`	Monitor the time in train or eval process.

Evaluation Metrics

API Name	Description	Supported Platforms
`mindspore.train.Accuracy`	Calculates the accuracy for classification and multilabel data.	`Ascend` `GPU` `CPU`
`mindspore.train.BleuScore`	Calculates the BLEU score.	`Ascend` `GPU` `CPU`
`mindspore.train.ConfusionMatrix`	Computes the confusion matrix, which is commonly used to evaluate the performance of classification models, including binary classification and multiple classification.	`Ascend` `GPU` `CPU`
`mindspore.train.ConfusionMatrixMetric`	Computes metrics related to confusion matrix.	`Ascend` `GPU` `CPU`
`mindspore.train.CosineSimilarity`	Computes representation similarity.	`Ascend` `GPU` `CPU`
`mindspore.train.Dice`	The Dice coefficient is a set similarity metric.	`Ascend` `GPU` `CPU`
`mindspore.train.F1`	Calculates the F1 score.	`Ascend` `GPU` `CPU`
`mindspore.train.Fbeta`	Calculates the Fbeta score.	`Ascend` `GPU` `CPU`
`mindspore.train.HausdorffDistance`	Calculates the Hausdorff distance.	`Ascend` `GPU` `CPU`
`mindspore.train.Loss`	Calculates the average of the loss.	`Ascend` `GPU` `CPU`
`mindspore.train.MAE`	Calculates the mean absolute error(MAE).	`Ascend` `GPU` `CPU`
`mindspore.train.MeanSurfaceDistance`	Computes the Average Surface Distance from y_pred to y under the default setting.	`Ascend` `GPU` `CPU`
`mindspore.train.Metric`	Base class of metric, which is used to evaluate metrics.	`Ascend` `GPU` `CPU`
`mindspore.train.MSE`	Measures the mean squared error(MSE).	`Ascend` `GPU` `CPU`
`mindspore.train.OcclusionSensitivity`	Calculates the occlusion sensitivity of the model for a given image, which illustrates which parts of an image are most important for a network's classification.	`Ascend` `GPU` `CPU`
`mindspore.train.Perplexity`	Computes perplexity.	`Ascend` `GPU` `CPU`
`mindspore.train.Precision`	Calculates precision for classification and multilabel data.	`Ascend` `GPU` `CPU`
`mindspore.train.Recall`	Calculates recall for classification and multilabel data.	`Ascend` `GPU` `CPU`
`mindspore.train.ROC`	Calculates the ROC curve.	`Ascend` `GPU` `CPU`
`mindspore.train.RootMeanSquareDistance`	Computes the Root Mean Square Surface Distance from y_pred to y under the default setting.	`Ascend` `GPU` `CPU`
`mindspore.train.Top1CategoricalAccuracy`	Calculates the top-1 categorical accuracy.	`Ascend` `GPU` `CPU`
`mindspore.train.Top5CategoricalAccuracy`	Calculates the top-5 categorical accuracy.	`Ascend` `GPU` `CPU`
`mindspore.train.TopKCategoricalAccuracy`	Calculates the top-k categorical accuracy.	`Ascend` `GPU` `CPU`

Utils

API Name	Description	Supported Platforms
`mindspore.train.auc`	Computes the AUC(Area Under the Curve) using the trapezoidal rule.	`Ascend` `GPU` `CPU`
`mindspore.train.get_metric_fn`	Gets the metric method based on the input name.	`Ascend` `GPU` `CPU`
`mindspore.train.names`	Gets all names of the metric methods.	`Ascend` `GPU` `CPU`
`mindspore.train.rearrange_inputs`	This decorator is used to rearrange the inputs according to its indexes attribute of the class.	`Ascend` `GPU` `CPU`

Thor

`mindspore.train.ConvertModelUtils`	Convert model to thor model.
`mindspore.train.ConvertNetUtils`	Convert net to thor layer net, used to compute and store second-order information matrix.