def disconnect(config, dataset):
"""
Disconnect and clean-up dataset upload.
DATASET may be specified by name or ID, but ID is preferred.
"""
datasets = config.trainml.run(config.trainml.client.datasets.list())
found = search_by_id_name(dataset, datasets)
if None is found:
raise click.UsageError("Cannot find specified dataset.")
return config.trainml.run(found.disconnect())
def remove(config, dataset):
"""
Remove a dataset.
DATASET may be specified by name or ID, but ID is preferred.
"""
datasets = config.trainml.run(config.trainml.client.datasets.list())
found = search_by_id_name(dataset, datasets)
if None is found:
raise click.UsageError("Cannot find specified dataset.")
return config.trainml.run(found.remove())
def disconnect(config, job):
"""
Disconnect and clean-up job.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find specified job.")
return config.trainml.run(found.disconnect())
def remove(config, project):
"""
Remove a project.
PROJECT may be specified by name or ID, but ID is preferred.
"""
projects = config.trainml.run(config.trainml.client.projects.list())
found = search_by_id_name(project, projects)
if None is found:
raise click.UsageError("Cannot find specified project.")
return config.trainml.run(found.remove())
def remove(config, model):
"""
Remove a model.
MODEL may be specified by name or ID, but ID is preferred.
"""
models = config.trainml.run(config.trainml.client.models.list())
found = search_by_id_name(model, models)
if None is found:
raise click.UsageError("Cannot find specified model.")
return config.trainml.run(found.remove())
def disconnect(config, model):
"""
Disconnect and clean-up model upload.
MODEL may be specified by name or ID, but ID is preferred.
"""
models = config.trainml.run(config.trainml.client.models.list())
found = search_by_id_name(model, models)
if None is found:
raise click.UsageError("Cannot find specified model.")
return config.trainml.run(found.disconnect())
def remove(config, id):
"""Remove connection."""
connections = config.trainml.run(config.trainml.client.connections.list())
found = search_by_id_name(id, connections)
if None is found:
raise click.UsageError("Connection ID specified does not exist.")
if found.type == "dataset":
this = config.trainml.run(config.trainml.client.datasets.get(id))
elif found.type == "job":
this = config.trainml.run(config.trainml.client.jobs.get(id))
else:
raise click.UsageError("Unknown connection type.")
return config.trainml.run(this.disconnect())
def connect(config, job, attach):
"""
Connect to job.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find specified job.")
if found.type != "notebook":
try:
if attach:
config.trainml.run(found.connect(), found.attach())
return config.trainml.run(found.disconnect())
else:
return config.trainml.run(found.connect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
else:
if found.status == "waiting for data/model download":
try:
if attach:
config.trainml.run(found.connect(), found.attach())
config.trainml.run(found.disconnect())
click.echo("Launching...", file=config.stdout)
browse(found.notebook_url)
else:
return config.trainml.run(found.connect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
else:
config.trainml.run(found.wait_for("running"))
click.echo("Launching...", file=config.stdout)
browse(found.notebook_url)
def stop(config, job, wait):
"""
Stop a running job.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find specified job.")
if wait:
config.trainml.run(found.stop())
click.echo("Waiting for job to stop...", file=config.stdout)
return config.trainml.run(found.wait_for("stopped"))
else:
return config.trainml.run(found.stop())
def start(config, job, connect):
"""
Start a previously stopped job.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find specified job.")
if connect:
config.trainml.run(found.start())
click.echo("Waiting for job to start...", file=config.stdout)
config.trainml.run(found.wait_for("running"))
click.echo("Launching...", file=config.stdout)
browse(found.notebook_url)
else:
return config.trainml.run(found.start())
def attach(config, dataset):
"""
Attach to dataset and show creation logs.
DATASET may be specified by name or ID, but ID is preferred.
"""
datasets = config.trainml.run(config.trainml.client.datasets.list())
found = search_by_id_name(dataset, datasets)
if None is found:
raise click.UsageError("Cannot find specified dataset.")
try:
config.trainml.run(found.attach())
return config.trainml.run(found.disconnect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
def attach(config, job):
"""
Attach to job and show logs.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find specified job.")
try:
config.trainml.run(found.attach())
return config.trainml.run(found.disconnect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
def attach(config, model):
"""
Attach to model and show creation logs.
MODEL may be specified by name or ID, but ID is preferred.
"""
models = config.trainml.run(config.trainml.client.models.list())
found = search_by_id_name(model, models)
if None is found:
raise click.UsageError("Cannot find specified model.")
try:
config.trainml.run(found.attach())
return config.trainml.run(found.disconnect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
def connect(config, dataset, attach):
"""
Connect local source to dataset and begin upload.
DATASET may be specified by name or ID, but ID is preferred.
"""
datasets = config.trainml.run(config.trainml.client.datasets.list())
found = search_by_id_name(dataset, datasets)
if None is found:
raise click.UsageError("Cannot find specified dataset.")
try:
if attach:
config.trainml.run(found.connect(), found.attach())
return config.trainml.run(found.disconnect())
else:
return config.trainml.run(found.connect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise
def connect(config, model, attach):
"""
Connect local source to model and begin upload.
MODEL may be specified by name or ID, but ID is preferred.
"""
models = config.trainml.run(config.trainml.client.models.list())
found = search_by_id_name(model, models)
if None is found:
raise click.UsageError("Cannot find specified model.")
try:
if attach:
config.trainml.run(found.connect(), found.attach())
return config.trainml.run(found.disconnect())
else:
return config.trainml.run(found.connect())
except:
try:
config.trainml.run(found.disconnect())
except:
pass
raise