metric¶
Metric is the abstract class that every ash metric must implement.
Classes
Metric is the abstract class that every ash Metric must implement. |
-
class
ashpy.metrics.metric.
Metric
(name, metric, model_selection_operator=None, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.2.0/docs/source/log')[source]¶ Bases:
abc.ABC
Metric is the abstract class that every ash Metric must implement.
AshPy Metrics wrap and extend Keras Metrics.
-
__init__
(name, metric, model_selection_operator=None, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.2.0/docs/source/log')[source]¶ Initialize the Metric object.
- Parameters
name (str) – The name of the metric.
metric (
tf.keras.metrics.Metric
) – The Keras metric to use.model_selection_operator (
typing.Callable
) –The operation that will be used when model_selection is triggered to compare the metrics, used by the update_state. Any
typing.Callable
behaving like anoperator
is accepted.Note
Model selection is done ONLY if an model_selection_operator is specified here.
logdir (str) – Path to the log dir, defaults to a log folder in the current directory.
- Return type
None
-
property
best_folder
¶ Retrieve the folder used to save the best model when doing model selection.
- Return type
-
property
best_model_sel_file
¶ Retrieve the path to JSON file containing the measured performance of the best model.
- Return type
-
static
json_read
(filename)[source]¶ Read a JSON file.
- Parameters
filename (str) – The path to the JSON file to read.
- Return type
- Returns
typing.Dict
– Dictionary containing the content of the JSON file.
-
static
json_write
(filename, what_to_write)[source]¶ Write inside the specified JSON file the mean and stddev.
-
property
metric
¶ Retrieve the
tf.keras.metrics.Metric
object.- Return type
Metric
-
model_selection
(checkpoint, global_step)[source]¶ Perform model selection.
- Parameters
checkpoint (
tf.train.Checkpoint
) – Checkpoint object that contains the model status.global_step (
tf.Variable
) – current training step
- Return type
None
-
property
model_selection_operator
¶ Retrieve the operator used for model selection.
-
result
()[source]¶ Get the result of the metric.
- Returns
numpy.ndarray
– The current value of the metric.
-