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3193ef1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 | # -*- coding: utf-8 -*-
# Copyright 2024 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.
#
"""The vertexai resources module."""
from google.cloud.aiplatform import initializer
from google.cloud.aiplatform.datasets import (
ImageDataset,
TabularDataset,
TextDataset,
TimeSeriesDataset,
VideoDataset,
)
from google.cloud.aiplatform import explain
from google.cloud.aiplatform import gapic
from google.cloud.aiplatform import hyperparameter_tuning
from google.cloud.aiplatform.featurestore import (
EntityType,
Feature,
Featurestore,
)
from google.cloud.aiplatform.matching_engine import (
MatchingEngineIndex,
MatchingEngineIndexEndpoint,
)
from google.cloud.aiplatform import metadata
from google.cloud.aiplatform.tensorboard import uploader_tracker
from google.cloud.aiplatform.models import DeploymentResourcePool
from google.cloud.aiplatform.models import Endpoint
from google.cloud.aiplatform.models import PrivateEndpoint
from google.cloud.aiplatform.models import Model
from google.cloud.aiplatform.models import ModelRegistry
from google.cloud.aiplatform.model_evaluation import ModelEvaluation
from google.cloud.aiplatform.jobs import (
BatchPredictionJob,
CustomJob,
HyperparameterTuningJob,
ModelDeploymentMonitoringJob,
)
from google.cloud.aiplatform.pipeline_jobs import PipelineJob
from google.cloud.aiplatform.pipeline_job_schedules import (
PipelineJobSchedule,
)
from google.cloud.aiplatform.tensorboard import (
Tensorboard,
TensorboardExperiment,
TensorboardRun,
TensorboardTimeSeries,
)
from google.cloud.aiplatform.training_jobs import (
CustomTrainingJob,
CustomContainerTrainingJob,
CustomPythonPackageTrainingJob,
AutoMLTabularTrainingJob,
AutoMLForecastingTrainingJob,
SequenceToSequencePlusForecastingTrainingJob,
TemporalFusionTransformerForecastingTrainingJob,
TimeSeriesDenseEncoderForecastingTrainingJob,
AutoMLImageTrainingJob,
AutoMLTextTrainingJob,
AutoMLVideoTrainingJob,
)
from google.cloud.aiplatform import helpers
"""
Usage:
import vertexai
vertexai.init(project='my_project')
"""
init = initializer.global_config.init
get_pipeline_df = metadata.metadata._LegacyExperimentService.get_pipeline_df
log_params = metadata.metadata._experiment_tracker.log_params
log_metrics = metadata.metadata._experiment_tracker.log_metrics
log_classification_metrics = (
metadata.metadata._experiment_tracker.log_classification_metrics
)
log_model = metadata.metadata._experiment_tracker.log_model
get_experiment_df = metadata.metadata._experiment_tracker.get_experiment_df
start_run = metadata.metadata._experiment_tracker.start_run
autolog = metadata.metadata._experiment_tracker.autolog
start_execution = metadata.metadata._experiment_tracker.start_execution
log = metadata.metadata._experiment_tracker.log
log_time_series_metrics = metadata.metadata._experiment_tracker.log_time_series_metrics
end_run = metadata.metadata._experiment_tracker.end_run
upload_tb_log = uploader_tracker._tensorboard_tracker.upload_tb_log
start_upload_tb_log = uploader_tracker._tensorboard_tracker.start_upload_tb_log
end_upload_tb_log = uploader_tracker._tensorboard_tracker.end_upload_tb_log
save_model = metadata._models.save_model
get_experiment_model = metadata.schema.google.artifact_schema.ExperimentModel.get
Experiment = metadata.experiment_resources.Experiment
ExperimentRun = metadata.experiment_run_resource.ExperimentRun
Artifact = metadata.artifact.Artifact
Execution = metadata.execution.Execution
Context = metadata.context.Context
__all__ = (
"end_run",
"explain",
"gapic",
"init",
"helpers",
"hyperparameter_tuning",
"log",
"log_params",
"log_metrics",
"log_classification_metrics",
"log_model",
"log_time_series_metrics",
"get_experiment_df",
"get_pipeline_df",
"start_run",
"start_execution",
"save_model",
"get_experiment_model",
"autolog",
"upload_tb_log",
"start_upload_tb_log",
"end_upload_tb_log",
"Artifact",
"AutoMLImageTrainingJob",
"AutoMLTabularTrainingJob",
"AutoMLForecastingTrainingJob",
"AutoMLTextTrainingJob",
"AutoMLVideoTrainingJob",
"BatchPredictionJob",
"CustomJob",
"CustomTrainingJob",
"CustomContainerTrainingJob",
"CustomPythonPackageTrainingJob",
"DeploymentResourcePool",
"Endpoint",
"EntityType",
"Execution",
"Experiment",
"ExperimentRun",
"Feature",
"Featurestore",
"MatchingEngineIndex",
"MatchingEngineIndexEndpoint",
"ImageDataset",
"HyperparameterTuningJob",
"Model",
"ModelRegistry",
"ModelEvaluation",
"ModelDeploymentMonitoringJob",
"PipelineJob",
"PipelineJobSchedule",
"PrivateEndpoint",
"SequenceToSequencePlusForecastingTrainingJob",
"TabularDataset",
"Tensorboard",
"TensorboardExperiment",
"TensorboardRun",
"TensorboardTimeSeries",
"TextDataset",
"TemporalFusionTransformerForecastingTrainingJob",
"TimeSeriesDataset",
"TimeSeriesDenseEncoderForecastingTrainingJob",
"VideoDataset",
)
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