def create(name, registry_image, registry_tag, data_set_id, entry_point,
git_owner, git_repository, git_branch, git_commit, cpu, memory, gpu,
partition, memo, tags, zip, local_data_set, parent_ids, options,
registry_id, git_id):
"""Submit new training"""
api = rest.TrainingApi(configuration.get_api_client())
container_image = rest.ComponentsContainerImageInputModel(
image=registry_image, registry_id=registry_id, tag=registry_tag)
git_model = rest.ComponentsGitCommitInputModel(branch=git_branch,
commit_id=git_commit,
git_id=git_id,
owner=git_owner,
repository=git_repository)
option_dict = {key: value for key, value in options} if options else None
model = rest.TrainingApiModelsCreateInputModel(
container_image=container_image,
cpu=cpu,
data_set_id=data_set_id,
entry_point=entry_point,
git_model=git_model,
gpu=gpu,
memo=memo,
memory=memory,
name=name,
options=option_dict,
parent_ids=list(parent_ids),
partition=partition,
tags=list(tags),
zip=zip,
local_data_set=local_data_set)
result = api.create_training(model=model)
print('created', result.id)
def list_training(count, id, name, started_at, data_set, memo, status,
entry_point):
"""List training filtered by conditions"""
api = rest.TrainingApi(configuration.get_api_client())
per_page = 1000
command_args = {
'id': id,
'name': name,
'started_at': started_at,
'data_set': data_set,
'memo': memo,
'status': status,
'entry_point': entry_point,
}
args = {
key: value
for key, value in command_args.items() if value is not None
}
if count <= per_page:
result = api.list_training(per_page=count, **args)
else:
total_pages = (count - 1) // per_page + 1
result = []
for page in range(1, total_pages + 1):
page_result = api.list_training(page=page, **args)
result.extend(page_result)
if len(page_result) < per_page:
break
pprint.pp_table(
['id', 'name', 'started_at', 'dataset', 'memo', 'status'],
[[x.id, x.name, x.created_at, x.data_set.name, x.memo, x.status]
for x in result[:count]])
def download_files(id, destination):
"""Download files of training"""
api = rest.TrainingApi(configuration.get_api_client())
result = api.list_training_files(id, with_url=True)
pool_manager = api.api_client.rest_client.pool_manager
for x in result:
object_storage.download_file(pool_manager, x.url, destination,
x.file_name)
def update(id, name, memo, favorite):
"""Update training"""
api = rest.TrainingApi(configuration.get_api_client())
model = rest.TrainingApiModelsEditInputModel(name=name,
memo=memo,
favorite=favorite)
result = api.update_training(id, model=model)
print('updated', result.id)
def upload_file(id, file_path):
"""Upload a file to training"""
api = rest.TrainingApi(configuration.get_api_client())
attached_info = object_storage.upload_file(api.api_client, file_path,
'TrainingHistoryAttachedFiles')
model = rest.ComponentsAddFileInputModel(
file_name=attached_info.file_name,
stored_path=attached_info.stored_path)
api.add_training_file(id, model=model)
def download_container_files(id, destination, source):
"""Download files in a container"""
api = rest.TrainingApi(configuration.get_api_client())
pool_manager = api.api_client.rest_client.pool_manager
def download_entries(path):
result = api.list_training_container_files(id,
path=path,
with_url=True)
for x in result.files:
if os.path.isabs(path):
_, tail = os.path.splitdrive(path)
object_storage.download_file(pool_manager, x.url,
destination + tail, x.file_name)
else:
object_storage.download_file(pool_manager, x.url,
os.path.join(destination, path),
x.file_name)
for x in result.dirs:
download_entries(os.path.join(path, x.dir_name))
source = source if source is not None else '/'
download_entries(source)
def get(id):
"""Get details of training"""
api = rest.TrainingApi(configuration.get_api_client())
result = api.get_training(id)
pprint.pp_dict(util.to_dict(result))
def tensorboard_halt(id):
"""Halt tensorboard"""
api = rest.TrainingApi(configuration.get_api_client())
api.halt_tensorboard(id)
print('halted', id)
def complete(id):
"""Complete training"""
api = rest.TrainingApi(configuration.get_api_client())
result = api.complete_training(id)
print('completed', result.id)
def halt(id):
"""Halt training"""
api = rest.TrainingApi(configuration.get_api_client())
result = api.halt_training(id)
print('halted', result.id)
def delete_file(id, file_id):
"""Delete a file of training"""
api = rest.TrainingApi(configuration.get_api_client())
api.delete_training_file(id, file_id)
print('deleted', file_id)
def list_files(id):
"""List files of training"""
api = rest.TrainingApi(configuration.get_api_client())
result = api.list_training_files(id)
pprint.pp_table(['file_id', 'file_name'],
[[x.file_id, x.file_name] for x in result])
def delete(id):
"""Delete training"""
api = rest.TrainingApi(configuration.get_api_client())
api.delete_training(id)
print('deleted', id)
