svm-model
will be created under the ml_repo iris-demo
.
You can view these runs in the TrueFoundry dashboard.
TrueFoundry Dashboard
Create and end a run
Add tags to a run
Log parameters
learning_rate
, cache_size
.
The parameter values are stringified before storing.You can log parameters using the log_params
as shown below:argparse.Namespace
object.Log metrics
accuracy
, f1 score
. You can log any output of your script as a metric.You can capture metrics using the log_metrics
method.Metrics Overview
Filter runs on the basis of metrics
step
argument.Step-wise metrics
step
argument?step
argument. To capture epoch-level metric aggregates, you can use the following pattern.Log Artifacts
Log Models
Log Images
PIL
package is needed to log images. To install the PIL package, runtruefoundry.ml.Image
by either by using a local path or you can use a numpy array / PIL.Image object.You can also log caption and the actual and predicted values for an image as shown in the examples below.Log Plots
Get a Run by ID
get_run_by_id
method:Get a Run by Fully Qualified Name (FQN)
get_run_by_fqn
method:Get All Runs for a Project
get_all_runs
method:Search Runs
search_runs
method:Get Tags for a Run
Get Parameters for a Run
get_params
method. It returns a dictionaryGet Metrics for a Run
get_metrics
method. It returns a dictionary.Can anyone create a run under my ml_repo?
Project Editor
role to create a run under a ml_repo. Project Viewer
role does not have permission to create a run.Can I use runs as a context manager?
with
block.Are run names unique?
How runs are identified?
id
.