# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import proto  # type: ignore

from google.protobuf import timestamp_pb2  # type: ignore


__protobuf__ = proto.module(
    package="google.cloud.aiplatform.v1", manifest={"TensorboardRun",},
)


class TensorboardRun(proto.Message):
    r"""TensorboardRun maps to a specific execution of a training job
    with a given set of hyperparameter values, model definition,
    dataset, etc

    Attributes:
        name (str):
            Output only. Name of the TensorboardRun. Format:
            ``projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}``
        display_name (str):
            Required. User provided name of this
            TensorboardRun. This value must be unique among
            all TensorboardRuns belonging to the same parent
            TensorboardExperiment.
        description (str):
            Description of this TensorboardRun.
        create_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp when this
            TensorboardRun was created.
        update_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp when this
            TensorboardRun was last updated.
        labels (Sequence[google.cloud.aiplatform_v1.types.TensorboardRun.LabelsEntry]):
            The labels with user-defined metadata to organize your
            TensorboardRuns.

            This field will be used to filter and visualize Runs in the
            Tensorboard UI. For example, a Vertex AI training job can
            set a label aiplatform.googleapis.com/training_job_id=xxxxx
            to all the runs created within that job. An end user can set
            a label experiment_id=xxxxx for all the runs produced in a
            Jupyter notebook. These runs can be grouped by a label value
            and visualized together in the Tensorboard UI.

            Label keys and values can be no longer than 64 characters
            (Unicode codepoints), can only contain lowercase letters,
            numeric characters, underscores and dashes. International
            characters are allowed. No more than 64 user labels can be
            associated with one TensorboardRun (System labels are
            excluded).

            See https://goo.gl/xmQnxf for more information and examples
            of labels. System reserved label keys are prefixed with
            "aiplatform.googleapis.com/" and are immutable.
        etag (str):
            Used to perform a consistent read-modify-
            rite updates. If not set, a blind "overwrite"
            update happens.
    """

    name = proto.Field(proto.STRING, number=1,)
    display_name = proto.Field(proto.STRING, number=2,)
    description = proto.Field(proto.STRING, number=3,)
    create_time = proto.Field(proto.MESSAGE, number=6, message=timestamp_pb2.Timestamp,)
    update_time = proto.Field(proto.MESSAGE, number=7, message=timestamp_pb2.Timestamp,)
    labels = proto.MapField(proto.STRING, proto.STRING, number=8,)
    etag = proto.Field(proto.STRING, number=9,)


__all__ = tuple(sorted(__protobuf__.manifest))
