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Original file line number | Diff line number | Diff line change |
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from mlflow.deployments import BaseDeploymentClient | ||
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class MLflowDeploymentClient(BaseDeploymentClient): | ||
def create_deployment(self, name, model_uri, flavor=None, config=None, endpoint=None): | ||
""" | ||
.. warning:: | ||
This method is not implemented for `MLflowDeploymentClient`. | ||
""" | ||
raise NotImplementedError | ||
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def update_deployment(self, name, model_uri=None, flavor=None, config=None, endpoint=None): | ||
""" | ||
.. warning:: | ||
This method is not implemented for `MLflowDeploymentClient`. | ||
""" | ||
raise NotImplementedError | ||
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def delete_deployment(self, name, config=None, endpoint=None): | ||
""" | ||
.. warning:: | ||
This method is not implemented for `MLflowDeploymentClient`. | ||
""" | ||
raise NotImplementedError | ||
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def list_deployments(self, endpoint=None): | ||
""" | ||
.. warning:: | ||
This method is not implemented for `MLflowDeploymentClient`. | ||
""" | ||
raise NotImplementedError | ||
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def get_deployment(self, name, endpoint=None): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError | ||
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def predict(self, deployment_name=None, inputs=None, endpoint=None): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def create_endpoint(self, name, config=None): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def update_endpoint(self, endpoint, config=None): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def delete_endpoint(self, endpoint): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def list_endpoints(self): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def get_endpoint(self, endpoint): | ||
""" | ||
TODO | ||
""" | ||
raise NotImplementedError("TODO") | ||
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def run_local(name, model_uri, flavor=None, config=None): | ||
pass | ||
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def target_help(): | ||
pass |
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Original file line number | Diff line number | Diff line change |
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from mlflow.deployments import get_deploy_client | ||
from mlflow.deployments.mlflow import MLflowDeploymentClient | ||
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def test_get_deploy_client(): | ||
client = get_deploy_client("http://localhost:5000") | ||
assert isinstance(client, MLflowDeploymentClient) |