dcase_models.util.TaggingCallback¶
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class
dcase_models.util.
TaggingCallback
(data, file_weights=None, best_F1=0, early_stopping=0, considered_improvement=0.01, label_list=[])[source]¶ Bases:
tensorflow.python.keras.callbacks.Callback
Keras callback to calculate acc after each epoch and save file with the weights if the evaluation improves
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__init__
(data, file_weights=None, best_F1=0, early_stopping=0, considered_improvement=0.01, label_list=[])[source]¶ Initialize the keras callback
Parameters: - data : tuple or KerasDataGenerator
Validation data for model evaluation (X_val, Y_val) or KerasDataGenerator
- file_weights : string
Path to the file with the weights
- best_acc : float
Last accuracy value, only if continue
- early_stopping : int
Number of epochs for cut the training if not improves if 0, do not use it
Methods
__init__
(data[, file_weights, best_F1, …])Initialize the keras callback on_batch_begin
(batch[, logs])A backwards compatibility alias for on_train_batch_begin. on_batch_end
(batch[, logs])A backwards compatibility alias for on_train_batch_end. on_epoch_begin
(epoch[, logs])Called at the start of an epoch. on_epoch_end
(epoch[, logs])This function is run when each epoch ends. on_predict_batch_begin
(batch[, logs])Called at the beginning of a batch in predict methods. on_predict_batch_end
(batch[, logs])Called at the end of a batch in predict methods. on_predict_begin
([logs])Called at the beginning of prediction. on_predict_end
([logs])Called at the end of prediction. on_test_batch_begin
(batch[, logs])Called at the beginning of a batch in evaluate methods. on_test_batch_end
(batch[, logs])Called at the end of a batch in evaluate methods. on_test_begin
([logs])Called at the beginning of evaluation or validation. on_test_end
([logs])Called at the end of evaluation or validation. on_train_batch_begin
(batch[, logs])Called at the beginning of a training batch in fit methods. on_train_batch_end
(batch[, logs])Called at the end of a training batch in fit methods. on_train_begin
([logs])Called at the beginning of training. on_train_end
([logs])Called at the end of training. set_model
(model)set_params
(params)-
on_batch_begin
(batch, logs=None)¶ A backwards compatibility alias for on_train_batch_begin.
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on_batch_end
(batch, logs=None)¶ A backwards compatibility alias for on_train_batch_end.
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on_epoch_begin
(epoch, logs=None)¶ Called at the start of an epoch.
Subclasses should override for any actions to run. This function should only be called during TRAIN mode.
- Arguments:
epoch: Integer, index of epoch. logs: Dict. Currently no data is passed to this argument for this method
but that may change in the future.
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on_epoch_end
(epoch, logs={})[source]¶ This function is run when each epoch ends. The metrics are calculated, printed and saved to the log file.
Parameters: - epoch : int
number of epoch (from Callback class)
- logs : dict
log data (from Callback class)
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on_predict_batch_begin
(batch, logs=None)¶ Called at the beginning of a batch in predict methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
batch: Integer, index of batch within the current epoch. logs: Dict, contains the return value of model.predict_step,
it typically returns a dict with a key ‘outputs’ containing the model’s outputs.
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on_predict_batch_end
(batch, logs=None)¶ Called at the end of a batch in predict methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
- batch: Integer, index of batch within the current epoch. logs: Dict. Aggregated metric results up until this batch.
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on_predict_begin
(logs=None)¶ Called at the beginning of prediction.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently no data is passed to this argument for this method
- but that may change in the future.
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on_predict_end
(logs=None)¶ Called at the end of prediction.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently no data is passed to this argument for this method
- but that may change in the future.
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on_test_batch_begin
(batch, logs=None)¶ Called at the beginning of a batch in evaluate methods.
Also called at the beginning of a validation batch in the fit methods, if validation data is provided.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
batch: Integer, index of batch within the current epoch. logs: Dict, contains the return value of model.test_step. Typically,
the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.
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on_test_batch_end
(batch, logs=None)¶ Called at the end of a batch in evaluate methods.
Also called at the end of a validation batch in the fit methods, if validation data is provided.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
- batch: Integer, index of batch within the current epoch. logs: Dict. Aggregated metric results up until this batch.
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on_test_begin
(logs=None)¶ Called at the beginning of evaluation or validation.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently no data is passed to this argument for this method
- but that may change in the future.
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on_test_end
(logs=None)¶ Called at the end of evaluation or validation.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently the output of the last call to
- on_test_batch_end() is passed to this argument for this method but that may change in the future.
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on_train_batch_begin
(batch, logs=None)¶ Called at the beginning of a training batch in fit methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
batch: Integer, index of batch within the current epoch. logs: Dict, contains the return value of model.train_step. Typically,
the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.
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on_train_batch_end
(batch, logs=None)¶ Called at the end of a training batch in fit methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Arguments:
- batch: Integer, index of batch within the current epoch. logs: Dict. Aggregated metric results up until this batch.
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on_train_begin
(logs=None)¶ Called at the beginning of training.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently no data is passed to this argument for this method
- but that may change in the future.
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on_train_end
(logs=None)¶ Called at the end of training.
Subclasses should override for any actions to run.
- Arguments:
- logs: Dict. Currently the output of the last call to on_epoch_end()
- is passed to this argument for this method but that may change in the future.
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set_model
(model)¶
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set_params
(params)¶
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