File size: 5,759 Bytes
09d8e80 | 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 | # -*- 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.
#
"""Namespaced Vertex AI Schemas."""
class training_job:
class definition:
custom_task = "gs://google-cloud-aiplatform/schema/trainingjob/definition/custom_task_1.0.0.yaml"
automl_tabular = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_tabular_1.0.0.yaml"
automl_forecasting = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_time_series_forecasting_1.0.0.yaml"
seq2seq_plus_forecasting = "gs://google-cloud-aiplatform/schema/trainingjob/definition/seq2seq_plus_time_series_forecasting_1.0.0.yaml"
tft_forecasting = "gs://google-cloud-aiplatform/schema/trainingjob/definition/temporal_fusion_transformer_time_series_forecasting_1.0.0.yaml"
tide_forecasting = "gs://google-cloud-aiplatform/schema/trainingjob/definition/time_series_dense_encoder_forecasting_1.0.0.yaml"
automl_image_classification = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_image_classification_1.0.0.yaml"
automl_image_object_detection = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_image_object_detection_1.0.0.yaml"
automl_text_classification = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_text_classification_1.0.0.yaml"
automl_text_extraction = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_text_extraction_1.0.0.yaml"
automl_text_sentiment = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_text_sentiment_1.0.0.yaml"
automl_video_action_recognition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_video_action_recognition_1.0.0.yaml"
automl_video_classification = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_video_classification_1.0.0.yaml"
automl_video_object_tracking = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_video_object_tracking_1.0.0.yaml"
class dataset:
class metadata:
tabular = (
"gs://google-cloud-aiplatform/schema/dataset/metadata/tabular_1.0.0.yaml"
)
time_series = "gs://google-cloud-aiplatform/schema/dataset/metadata/time_series_1.0.0.yaml"
image = "gs://google-cloud-aiplatform/schema/dataset/metadata/image_1.0.0.yaml"
text = "gs://google-cloud-aiplatform/schema/dataset/metadata/text_1.0.0.yaml"
video = "gs://google-cloud-aiplatform/schema/dataset/metadata/video_1.0.0.yaml"
class ioformat:
class image:
multi_label_classification = "gs://google-cloud-aiplatform/schema/dataset/ioformat/image_classification_multi_label_io_format_1.0.0.yaml"
single_label_classification = "gs://google-cloud-aiplatform/schema/dataset/ioformat/image_classification_single_label_io_format_1.0.0.yaml"
bounding_box = "gs://google-cloud-aiplatform/schema/dataset/ioformat/image_bounding_box_io_format_1.0.0.yaml"
image_segmentation = "gs://google-cloud-aiplatform/schema/dataset/ioformat/image_segmentation_io_format_1.0.0.yaml"
class text:
multi_label_classification = "gs://google-cloud-aiplatform/schema/dataset/ioformat/text_classification_multi_label_io_format_1.0.0.yaml"
single_label_classification = "gs://google-cloud-aiplatform/schema/dataset/ioformat/text_classification_single_label_io_format_1.0.0.yaml"
extraction = "gs://google-cloud-aiplatform/schema/dataset/ioformat/text_extraction_io_format_1.0.0.yaml"
sentiment = "gs://google-cloud-aiplatform/schema/dataset/ioformat/text_sentiment_io_format_1.0.0.yaml"
class video:
action_recognition = "gs://google-cloud-aiplatform/schema/dataset/ioformat/video_action_recognition_io_format_1.0.0.yaml"
classification = "gs://google-cloud-aiplatform/schema/dataset/ioformat/video_classification_io_format_1.0.0.yaml"
object_tracking = "gs://google-cloud-aiplatform/schema/dataset/ioformat/video_object_tracking_io_format_1.0.0.yaml"
class annotation:
class image:
classification = "gs://google-cloud-aiplatform/schema/dataset/annotation/image_classification_1.0.0.yaml"
bounding_box = "gs://google-cloud-aiplatform/schema/dataset/annotation/image_bounding_box_1.0.0.yaml"
segmentation = "gs://google-cloud-aiplatform/schema/dataset/annotation/image_segmentation_1.0.0.yaml"
class text:
classification = "gs://google-cloud-aiplatform/schema/dataset/annotation/text_classification_1.0.0.yaml"
extraction = "gs://google-cloud-aiplatform/schema/dataset/annotation/text_extraction_1.0.0.yaml"
sentiment = "gs://google-cloud-aiplatform/schema/dataset/annotation/text_sentiment_1.0.0.yaml"
class video:
classification = "gs://google-cloud-aiplatform/schema/dataset/annotation/video_classification_1.0.0.yaml"
object_tracking = "gs://google-cloud-aiplatform/schema/dataset/annotation/video_object_tracking_1.0.0.yaml"
action_recognition = "gs://google-cloud-aiplatform/schema/dataset/annotation/video_action_recognition_1.0.0.yaml"
|