Magic
Experiment with any imaginable function using our Magic Object
Last updated
Experiment with any imaginable function using our Magic Object
Last updated
Wherever you are, whatever strange function you are building up, Magic Object
allows you to easily develop and interact withInnocuous Book experiment.
Instantiate Magic Object
before use.
Then, enjoy Innocuous Book Magic power
Search the data by filename
from path
, if exist, return the data path.
Example:
Log metrics then you can choose one as optimal standard.
Do not use log
within a Trainable
class.
Example:
so u can read the data with that save ur checkpoints no matter what framework api for every single framework log you metrics
Return the path of checkpoints during each epoch or whenever you want.
Example:
Save checkpoint during each epoch.
Example:
Save checkpoint whenever you want.
Example:
Save checkpoint with the opportunity by on
during each epoch and s
Example:
Arguments
filename
String (name of data with extension which you want to download)
path
String (directory where data put)
Arguments
**kwargs
Arguments to log which must have key
Arguments
path
String (directory where you wnat to save checkpoints)
epoch
integer (number of epochs to save the model as checkpoint. An epoch is an iteration over the entire x
and y
data provided)
Arguments
checkpoint
Dictionary or OrderDictionary (model, weights or anything to save as checkpoint)
path
String (directory where you wnat to save checkpoints)
epoch
Integer (number of epochs to save the model as checkpoint. epoch
would iterate over the entire x
and y
data provided)
Arguments
checkpoint
Sequential object (model to save as checkpoint)
path
String (directory where you wnat to save checkpoints)
Arguments
metrics
Metrics in dictionary to be evaluated by the model during training and testing. Each can be a string (name of a built-in function), function or a tf.keras.metrics.Metric
instance
path
String (directory where you wnat to save checkpoints)
frequency
Integer or List (if an integer n
, checkpoints are saved every n
times of each hook. if a list, it specifies the checkpoint frequencies for each hook individually.)
on
Integer or List (when to trigger checkpoint creations. must be one of the Keras event hooks (less the on_
), e.g. "train_start", or "predict_end". defaults to "epoch_end".)
filename
String (name of checkpoint you want to save)