How to use the dtlpy.setenv function in dtlpy

To help you get started, we’ve selected a few dtlpy examples, based on popular ways it is used in public projects.

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github dataloop-ai / ZazuML / zazu.py View on Github external
def maybe_login(env):
    try:
        dl.setenv(env)
    except:
        dl.login()
        dl.setenv(env)
github dataloop-ai / ZazuML / delete_plugin.py View on Github external
import dtlpy as dl
dl.setenv('dev')
deployment = dl.projects.get(project_name='buffs_project').deployments.get(deployment_name="trial")
deployment.delete()

# or

plugin = dl.projects.get(project_name='buffs_project').plugins.get(plugin_name="trial")
plugin.delete()
print("erased . . . ")
github dataloop-ai / ZazuML / create_plugins.py View on Github external
def create_trainer():
    dl.setenv('dev')

    plugin_name = 'trainer'
    project_name = 'ZazuProject'

    project = dl.projects.get(project_name=project_name)
    dl.projects.checkout(project_name)
    dl.plugins.checkout(plugin_name)

    ###############
    # push plugin #
    ###############
    plugin = project.plugins.push(plugin_name=plugin_name,
                                  src_path=os.getcwd())

    plugin = project.plugins.get(plugin_name=plugin_name)
github dataloop-ai / ZazuML / download_tiny_coco.py View on Github external
import dtlpy as dl
import os

path = '/home/noam/data'

dl.login_token(
    'insert_token_here')
dl.setenv('dev')
project = dl.projects.get(project_id='buffs_project')
dataset_obj = project.datasets.get('my_data')
# dataset_obj.items.upload(local_path='/Users/noam/tiny_coco', remote_path='')
dataset_obj.items.download(local_path=path)
os.rename(os.path.join(path, 'items', 'tiny_coco'), os.path.join(path, 'tiny_coco'))
github dataloop-ai / ZazuML / dataloop_services / zazu_timer_module.py View on Github external
def __init__(self, configs, time, test_dataset_id, query):
        logger.info('dtlpy version: ' + str(dl.__version__))
        logger.info('dtlpy info: ' + str(dl.info()))
        time = int(time)
        dl.setenv('prod')
        configs = json.loads(configs)
        query = json.loads(query)
        self.configs_input = dl.FunctionIO(type='Json', name='configs', value=configs)
        self.service = dl.services.get('zazu')
        project_name = configs['dataloop']['project']
        self.project = dl.projects.get(project_name)
        test_dataset = self.project.datasets.get(dataset_id=test_dataset_id)
        maybe_download_pred_data(dataset_obj=test_dataset, val_query=query)

        # add gt annotations
        filters = dl.Filters()
        filters.custom_filter = query
        dataset_name = test_dataset.name
        path_to_dataset = os.path.join(os.getcwd(), dataset_name)
        # only download if doesnt exist
        if not os.path.exists(path_to_dataset):
github dataloop-ai / ZazuML / create_plugins.py View on Github external
def create_tuner():
    dl.setenv('prod')

    plugin_name = 'tuner'
    project_name = 'ZazuProject'

    project = dl.projects.get(project_name=project_name)

    ###############
    # push plugin #
    ###############
    plugin = project.plugins.push(plugin_name=plugin_name,
                                  src_path=os.getcwd(),
                                  inputs=[{"type": "Json",
                                           "name": "configs"}])

    plugin = project.plugins.get(plugin_name=plugin_name)