From 237d97ad134e6e84ec202ce4df2ed6c7c5aef866 Mon Sep 17 00:00:00 2001
From: Torry Yang <sirtorry@users.noreply.github.com>
Date: Fri, 20 Jul 2018 16:24:34 -0700
Subject: [PATCH] automl beta
[(#1575)](https://github.com/GoogleCloudPlatform/python-docs-samples/issues/1575)
* automl initial commit
* lint
* fix import groupings
* add requirements.txt
* address review comments
---
automl/snippets/automl_translation_dataset.py | 278 ++++++++++++++++
automl/snippets/automl_translation_model.py | 300 ++++++++++++++++++
automl/snippets/automl_translation_predict.py | 109 +++++++
automl/snippets/dataset_test.py | 69 ++++
automl/snippets/model_test.py | 78 +++++
automl/snippets/predict_test.py | 31 ++
6 files changed, 865 insertions(+)
create mode 100755 automl/snippets/automl_translation_dataset.py
create mode 100755 automl/snippets/automl_translation_model.py
create mode 100644 automl/snippets/automl_translation_predict.py
create mode 100644 automl/snippets/dataset_test.py
create mode 100644 automl/snippets/model_test.py
create mode 100644 automl/snippets/predict_test.py
diff --git a/automl/snippets/automl_translation_dataset.py b/automl/snippets/automl_translation_dataset.py
new file mode 100755
index 000000000000..e579ac358a21
--- /dev/null
+++ b/automl/snippets/automl_translation_dataset.py
@@ -0,0 +1,278 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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.
+
+"""This application demonstrates how to perform basic operations on dataset
+with the Google AutoML Translation API.
+
+For more information, see the documentation at
+https://cloud.google.com/translate/automl/docs
+"""
+
+import argparse
+import os
+
+
+def create_dataset(project_id, compute_region, dataset_name, source, target):
+ """Create a dataset."""
+ # [START automl_translation_create_dataset]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # dataset_name = 'DATASET_NAME_HERE'
+ # source = 'LANGUAGE_CODE_OF_SOURCE_LANGUAGE'
+ # target = 'LANGUAGE_CODE_OF_TARGET_LANGUAGE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # A resource that represents Google Cloud Platform location.
+ project_location = client.location_path(project_id, compute_region)
+
+ # Specify the source and target language.
+ dataset_metadata = {
+ "source_language_code": source,
+ "target_language_code": target,
+ }
+ # Set dataset name and dataset metadata
+ my_dataset = {
+ "display_name": dataset_name,
+ "translation_dataset_metadata": dataset_metadata,
+ }
+
+ # Create a dataset with the dataset metadata in the region.
+ dataset = client.create_dataset(project_location, my_dataset)
+
+ # Display the dataset information
+ print("Dataset name: {}".format(dataset.name))
+ print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+ print("Dataset display name: {}".format(dataset.display_name))
+ print("Translation dataset Metadata:")
+ print(
+ "\tsource_language_code: {}".format(
+ dataset.translation_dataset_metadata.source_language_code
+ )
+ )
+ print(
+ "\ttarget_language_code: {}".format(
+ dataset.translation_dataset_metadata.target_language_code
+ )
+ )
+ print("Dataset create time:")
+ print("\tseconds: {}".format(dataset.create_time.seconds))
+ print("\tnanos: {}".format(dataset.create_time.nanos))
+
+ # [END automl_translation_create_dataset]
+
+
+def list_datasets(project_id, compute_region, filter_):
+ """List Datasets."""
+ # [START automl_translation_list_datasets]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # filter_ = 'filter expression here'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # A resource that represents Google Cloud Platform location.
+ project_location = client.location_path(project_id, compute_region)
+
+ # List all the datasets available in the region by applying filter.
+ response = client.list_datasets(project_location, filter_)
+
+ print("List of datasets:")
+ for dataset in response:
+ # Display the dataset information
+ print("Dataset name: {}".format(dataset.name))
+ print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+ print("Dataset display name: {}".format(dataset.display_name))
+ print("Translation dataset metadata:")
+ print(
+ "\tsource_language_code: {}".format(
+ dataset.translation_dataset_metadata.source_language_code
+ )
+ )
+ print(
+ "\ttarget_language_code: {}".format(
+ dataset.translation_dataset_metadata.target_language_code
+ )
+ )
+ print("Dataset create time:")
+ print("\tseconds: {}".format(dataset.create_time.seconds))
+ print("\tnanos: {}".format(dataset.create_time.nanos))
+
+ # [END automl_translation_list_datasets]
+
+
+def get_dataset(project_id, compute_region, dataset_id):
+ """Get the dataset."""
+ # [START automl_translation_get_dataset]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # dataset_id = 'DATASET_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the dataset
+ dataset_full_id = client.dataset_path(
+ project_id, compute_region, dataset_id
+ )
+
+ # Get complete detail of the dataset.
+ dataset = client.get_dataset(dataset_full_id)
+
+ # Display the dataset information
+ print("Dataset name: {}".format(dataset.name))
+ print("Dataset id: {}".format(dataset.name.split("/")[-1]))
+ print("Dataset display name: {}".format(dataset.display_name))
+ print("Translation dataset metadata:")
+ print(
+ "\tsource_language_code: {}".format(
+ dataset.translation_dataset_metadata.source_language_code
+ )
+ )
+ print(
+ "\ttarget_language_code: {}".format(
+ dataset.translation_dataset_metadata.target_language_code
+ )
+ )
+ print("Dataset create time:")
+ print("\tseconds: {}".format(dataset.create_time.seconds))
+ print("\tnanos: {}".format(dataset.create_time.nanos))
+
+ # [END automl_translation_get_dataset]
+
+
+def import_data(project_id, compute_region, dataset_id, path):
+ """Import sentence pairs to the dataset."""
+ # [START automl_translation_import_data]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # dataset_id = 'DATASET_ID_HERE'
+ # path = 'gs://path/to/file.csv'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the dataset.
+ dataset_full_id = client.dataset_path(
+ project_id, compute_region, dataset_id
+ )
+
+ # Get the multiple Google Cloud Storage URIs
+ input_uris = path.split(",")
+ input_config = {"gcs_source": {"input_uris": input_uris}}
+
+ # Import data from the input URI
+ response = client.import_data(dataset_full_id, input_config)
+
+ print("Processing import...")
+ # synchronous check of operation status
+ print("Data imported. {}".format(response.result()))
+
+ # [END automl_translation_import_data]
+
+
+def delete_dataset(project_id, compute_region, dataset_id):
+ """Delete a dataset."""
+ # [START automl_translation_delete_dataset]]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # dataset_id = 'DATASET_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the dataset.
+ dataset_full_id = client.dataset_path(
+ project_id, compute_region, dataset_id
+ )
+
+ # Delete a dataset.
+ response = client.delete_dataset(dataset_full_id)
+
+ # synchronous check of operation status
+ print("Dataset deleted. {}".format(response.result()))
+
+ # [END automl_translation_delete_dataset]
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser(
+ description=__doc__,
+ formatter_class=argparse.RawDescriptionHelpFormatter,
+ )
+ subparsers = parser.add_subparsers(dest="command")
+
+ create_dataset_parser = subparsers.add_parser(
+ "create_dataset", help=create_dataset.__doc__
+ )
+ create_dataset_parser.add_argument("dataset_name")
+ create_dataset_parser.add_argument("source")
+ create_dataset_parser.add_argument("target")
+
+ list_datasets_parser = subparsers.add_parser(
+ "list_datasets", help=list_datasets.__doc__
+ )
+ list_datasets_parser.add_argument("filter", nargs="?", default="")
+
+ import_data_parser = subparsers.add_parser(
+ "import_data", help=import_data.__doc__
+ )
+ import_data_parser.add_argument("dataset_id")
+ import_data_parser.add_argument("path")
+
+ delete_dataset_parser = subparsers.add_parser(
+ "delete_dataset", help=delete_dataset.__doc__
+ )
+ delete_dataset_parser.add_argument("dataset_id")
+
+ get_dataset_parser = subparsers.add_parser(
+ "get_dataset", help=get_dataset.__doc__
+ )
+ get_dataset_parser.add_argument("dataset_id")
+
+ project_id = os.environ["PROJECT_ID"]
+ compute_region = os.environ["REGION_NAME"]
+
+ args = parser.parse_args()
+
+ if args.command == "create_dataset":
+ create_dataset(
+ project_id,
+ compute_region,
+ args.dataset_name,
+ args.source,
+ args.target,
+ )
+ if args.command == "list_datasets":
+ list_datasets(project_id, compute_region, args.filter)
+ if args.command == "get_dataset":
+ get_dataset(project_id, compute_region, args.dataset_id)
+ if args.command == "import_data":
+ import_data(project_id, compute_region, args.dataset_id, args.path)
+ if args.command == "delete_dataset":
+ delete_dataset(project_id, compute_region, args.dataset_id)
diff --git a/automl/snippets/automl_translation_model.py b/automl/snippets/automl_translation_model.py
new file mode 100755
index 000000000000..0b9b6f53acaa
--- /dev/null
+++ b/automl/snippets/automl_translation_model.py
@@ -0,0 +1,300 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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.
+
+"""This application demonstrates how to perform basic operations on model
+with the Google AutoML Translation API.
+
+For more information, see the documentation at
+https://cloud.google.com/translate/automl/docs
+"""
+
+import argparse
+import os
+
+
+def create_model(project_id, compute_region, dataset_id, model_name):
+ """Create a model."""
+ # [START automl_translation_create_model]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # dataset_id = 'DATASET_ID_HERE'
+ # model_name = 'MODEL_NAME_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # A resource that represents Google Cloud Platform location.
+ project_location = client.location_path(project_id, compute_region)
+
+ # Set model name and dataset.
+ my_model = {
+ "display_name": model_name,
+ "dataset_id": dataset_id,
+ "translation_model_metadata": {"base_model": ""},
+ }
+
+ # Create a model with the model metadata in the region.
+ response = client.create_model(project_location, my_model)
+
+ print("Training operation name: {}".format(response.operation.name))
+ print("Training started...")
+
+ # [END automl_translation_create_model]
+
+
+def list_models(project_id, compute_region, filter_):
+ """List all models."""
+ # [START automl_translation_list_models]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # filter_ = 'DATASET_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+ from google.cloud.automl_v1beta1 import enums
+
+ client = automl.AutoMlClient()
+
+ # A resource that represents Google Cloud Platform location.
+ project_location = client.location_path(project_id, compute_region)
+
+ # List all the models available in the region by applying filter.
+ response = client.list_models(project_location, filter_)
+
+ print("List of models:")
+ for model in response:
+ # Display the model information.
+ if model.deployment_state == enums.Model.DeploymentState.DEPLOYED:
+ deployment_state = "deployed"
+ else:
+ deployment_state = "undeployed"
+
+ print("Model name: {}".format(model.name))
+ print("Model id: {}".format(model.name.split("/")[-1]))
+ print("Model display name: {}".format(model.display_name))
+ print("Model create time:")
+ print("\tseconds: {}".format(model.create_time.seconds))
+ print("\tnanos: {}".format(model.create_time.nanos))
+ print("Model deployment state: {}".format(deployment_state))
+
+ # [END automl_translation_list_models]
+
+
+def get_model(project_id, compute_region, model_id):
+ """Get model details."""
+ # [START automl_translation_get_model]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # model_id = 'MODEL_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+ from google.cloud.automl_v1beta1 import enums
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the model.
+ model_full_id = client.model_path(project_id, compute_region, model_id)
+
+ # Get complete detail of the model.
+ model = client.get_model(model_full_id)
+
+ # Retrieve deployment state.
+ if model.deployment_state == enums.Model.DeploymentState.DEPLOYED:
+ deployment_state = "deployed"
+ else:
+ deployment_state = "undeployed"
+
+ # Display the model information.
+ print("Model name: {}".format(model.name))
+ print("Model id: {}".format(model.name.split("/")[-1]))
+ print("Model display name: {}".format(model.display_name))
+ print("Model create time:")
+ print("\tseconds: {}".format(model.create_time.seconds))
+ print("\tnanos: {}".format(model.create_time.nanos))
+ print("Model deployment state: {}".format(deployment_state))
+
+ # [END automl_translation_get_model]
+
+
+def list_model_evaluations(project_id, compute_region, model_id, filter_):
+ """List model evaluations."""
+ # [START automl_translation_list_model_evaluations]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # model_id = 'MODEL_ID_HERE'
+ # filter_ = 'filter expression here'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the model.
+ model_full_id = client.model_path(project_id, compute_region, model_id)
+
+ print("List of model evaluations:")
+ for element in client.list_model_evaluations(model_full_id, filter_):
+ print(element)
+
+ # [END automl_translation_list_model_evaluations]
+
+
+def get_model_evaluation(
+ project_id, compute_region, model_id, model_evaluation_id
+):
+ """Get model evaluation."""
+ # [START automl_translation_get_model_evaluation]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # model_id = 'MODEL_ID_HERE'
+ # model_evaluation_id = 'MODEL_EVALUATION_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the model evaluation.
+ model_evaluation_full_id = client.model_evaluation_path(
+ project_id, compute_region, model_id, model_evaluation_id
+ )
+
+ # Get complete detail of the model evaluation.
+ response = client.get_model_evaluation(model_evaluation_full_id)
+
+ print(response)
+
+ # [END automl_translation_get_model_evaluation]
+
+
+def delete_model(project_id, compute_region, model_id):
+ """Delete a model."""
+ # [START automl_translation_delete_model]
+ # TODO(developer): Uncomment and set the following variables
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # model_id = 'MODEL_ID_HERE'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the full path of the model.
+ model_full_id = client.model_path(project_id, compute_region, model_id)
+
+ # Delete a model.
+ response = client.delete_model(model_full_id)
+
+ # synchronous check of operation status.
+ print("Model deleted. {}".format(response.result()))
+
+ # [END automl_translation_delete_model]
+
+
+def get_operation_status(operation_full_id):
+ """Get operation status."""
+ # [START automl_translation_get_operation_status]
+ # TODO(developer): Uncomment and set the following variables
+ # operation_full_id =
+ # 'projects/<projectId>/locations/<region>/operations/<operationId>'
+
+ from google.cloud import automl_v1beta1 as automl
+
+ client = automl.AutoMlClient()
+
+ # Get the latest state of a long-running operation.
+ response = client.transport._operations_client.get_operation(
+ operation_full_id
+ )
+
+ print("Operation status: {}".format(response))
+
+ # [END automl_translation_get_operation_status]
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser(
+ description=__doc__,
+ formatter_class=argparse.RawDescriptionHelpFormatter,
+ )
+ subparsers = parser.add_subparsers(dest="command")
+
+ create_model_parser = subparsers.add_parser(
+ "create_model", help=create_model.__doc__
+ )
+ create_model_parser.add_argument("dataset_id")
+ create_model_parser.add_argument("model_name")
+
+ list_model_evaluations_parser = subparsers.add_parser(
+ "list_model_evaluations", help=list_model_evaluations.__doc__
+ )
+ list_model_evaluations_parser.add_argument("model_id")
+ list_model_evaluations_parser.add_argument("filter", nargs="?", default="")
+
+ get_model_evaluation_parser = subparsers.add_parser(
+ "get_model_evaluation", help=get_model_evaluation.__doc__
+ )
+ get_model_evaluation_parser.add_argument("model_id")
+ get_model_evaluation_parser.add_argument("model_evaluation_id")
+
+ get_model_parser = subparsers.add_parser(
+ "get_model", help=get_model.__doc__
+ )
+ get_model_parser.add_argument("model_id")
+
+ get_operation_status_parser = subparsers.add_parser(
+ "get_operation_status", help=get_operation_status.__doc__
+ )
+ get_operation_status_parser.add_argument("operation_full_id")
+
+ list_models_parser = subparsers.add_parser(
+ "list_models", help=list_models.__doc__
+ )
+ list_models_parser.add_argument("filter", nargs="?", default="")
+
+ delete_model_parser = subparsers.add_parser(
+ "delete_model", help=delete_model.__doc__
+ )
+ delete_model_parser.add_argument("model_id")
+
+ project_id = os.environ["PROJECT_ID"]
+ compute_region = os.environ["REGION_NAME"]
+
+ args = parser.parse_args()
+
+ if args.command == "create_model":
+ create_model(
+ project_id, compute_region, args.dataset_id, args.model_name
+ )
+ if args.command == "list_models":
+ list_models(project_id, compute_region, args.filter)
+ if args.command == "get_model":
+ get_model(project_id, compute_region, args.model_id)
+ if args.command == "list_model_evaluations":
+ list_model_evaluations(
+ project_id, compute_region, args.model_id, args.filter
+ )
+ if args.command == "get_model_evaluation":
+ get_model_evaluation(
+ project_id, compute_region, args.model_id, args.model_evaluation_id
+ )
+ if args.command == "delete_model":
+ delete_model(project_id, compute_region, args.model_id)
+ if args.command == "get_operation_status":
+ get_operation_status(args.operation_full_id)
diff --git a/automl/snippets/automl_translation_predict.py b/automl/snippets/automl_translation_predict.py
new file mode 100644
index 000000000000..1dac70b78d55
--- /dev/null
+++ b/automl/snippets/automl_translation_predict.py
@@ -0,0 +1,109 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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.
+
+"""This application demonstrates how to perform basic operations on prediction
+with the Google AutoML Translation API.
+
+For more information, see the documentation at
+https://cloud.google.com/translate/automl/docs
+"""
+
+import argparse
+import os
+
+
+def predict(
+ project_id,
+ compute_region,
+ model_id,
+ file_path,
+ translation_allow_fallback=False,
+):
+ """Translate the content."""
+ # [START automl_translation_predict]
+ # project_id = 'PROJECT_ID_HERE'
+ # compute_region = 'COMPUTE_REGION_HERE'
+ # model_id = 'MODEL_ID_HERE'
+ # file_path = '/local/path/to/file'
+ # translation_allow_fallback = True allows fallback to Google Translate
+
+ from google.cloud import automl_v1beta1 as automl
+
+ automl_client = automl.AutoMlClient()
+
+ # Create client for prediction service.
+ prediction_client = automl.PredictionServiceClient()
+
+ # Get the full path of the model.
+ model_full_id = automl_client.model_path(
+ project_id, compute_region, model_id
+ )
+
+ # Read the file content for translation.
+ with open(file_path, "rb") as content_file:
+ content = content_file.read()
+ content.decode("utf-8")
+
+ # Set the payload by giving the content of the file.
+ payload = {"text_snippet": {"content": content}}
+
+ # params is additional domain-specific parameters.
+ # translation_allow_fallback allows to use Google translation model.
+ params = {}
+ if translation_allow_fallback:
+ params = {"translation_allow_fallback": "True"}
+
+ response = prediction_client.predict(model_full_id, payload, params)
+ translated_content = response.payload[0].translation.translated_content
+
+ print(u"Translated content: {}".format(translated_content.content))
+
+ # [END automl_translation_predict]
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser(
+ description=__doc__,
+ formatter_class=argparse.RawDescriptionHelpFormatter,
+ )
+ subparsers = parser.add_subparsers(dest="command")
+
+ predict_parser = subparsers.add_parser("predict", help=predict.__doc__)
+ predict_parser.add_argument("model_id")
+ predict_parser.add_argument("file_path")
+ predict_parser.add_argument(
+ "translation_allow_fallback",
+ nargs="?",
+ choices=["False", "True"],
+ default="False",
+ )
+
+ project_id = os.environ["PROJECT_ID"]
+ compute_region = os.environ["REGION_NAME"]
+
+ args = parser.parse_args()
+
+ if args.command == "predict":
+ translation_allow_fallback = (
+ True if args.translation_allow_fallback == "True" else False
+ )
+ predict(
+ project_id,
+ compute_region,
+ args.model_id,
+ args.file_path,
+ translation_allow_fallback,
+ )
diff --git a/automl/snippets/dataset_test.py b/automl/snippets/dataset_test.py
new file mode 100644
index 000000000000..29e3e5c9fe97
--- /dev/null
+++ b/automl/snippets/dataset_test.py
@@ -0,0 +1,69 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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 datetime
+import os
+
+import pytest
+
+import automl_translation_dataset
+
+project_id = os.environ["GCLOUD_PROJECT"]
+compute_region = "us-central1"
+
+
+@pytest.mark.slow
+def test_dataset_create_import_delete(capsys):
+ # create dataset
+ dataset_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+ automl_translation_dataset.create_dataset(
+ project_id, compute_region, dataset_name, "en", "ja"
+ )
+ out, _ = capsys.readouterr()
+ create_dataset_output = out.splitlines()
+ assert "Dataset id: " in create_dataset_output[1]
+
+ # import data
+ dataset_id = create_dataset_output[1].split()[2]
+ data = "gs://{}-vcm/en-ja.csv".format(project_id)
+ automl_translation_dataset.import_data(
+ project_id, compute_region, dataset_id, data
+ )
+ out, _ = capsys.readouterr()
+ assert "Data imported." in out
+
+ # delete dataset
+ automl_translation_dataset.delete_dataset(
+ project_id, compute_region, dataset_id
+ )
+ out, _ = capsys.readouterr()
+ assert "Dataset deleted." in out
+
+
+def test_dataset_list_get(capsys):
+ # list datasets
+ automl_translation_dataset.list_datasets(project_id, compute_region, "")
+ out, _ = capsys.readouterr()
+ list_dataset_output = out.splitlines()
+ assert "Dataset id: " in list_dataset_output[2]
+
+ # get dataset
+ dataset_id = list_dataset_output[2].split()[2]
+ automl_translation_dataset.get_dataset(
+ project_id, compute_region, dataset_id
+ )
+ out, _ = capsys.readouterr()
+ assert "Dataset name: " in out
diff --git a/automl/snippets/model_test.py b/automl/snippets/model_test.py
new file mode 100644
index 000000000000..7f915c5dddf3
--- /dev/null
+++ b/automl/snippets/model_test.py
@@ -0,0 +1,78 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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 datetime
+import os
+
+from google.cloud import automl_v1beta1 as automl
+
+import automl_translation_model
+
+project_id = os.environ["GCLOUD_PROJECT"]
+compute_region = "us-central1"
+
+
+def test_model_create_status_delete(capsys):
+ # create model
+ client = automl.AutoMlClient()
+ model_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+ project_location = client.location_path(project_id, compute_region)
+ my_model = {
+ "display_name": model_name,
+ "dataset_id": "3876092572857648864",
+ "translation_model_metadata": {"base_model": ""},
+ }
+ response = client.create_model(project_location, my_model)
+ operation_name = response.operation.name
+ assert operation_name
+
+ # get operation status
+ automl_translation_model.get_operation_status(operation_name)
+ out, _ = capsys.readouterr()
+ assert "Operation status: " in out
+
+ # cancel operation
+ response.cancel()
+
+
+def test_model_list_get_evaluate(capsys):
+ # list models
+ automl_translation_model.list_models(project_id, compute_region, "")
+ out, _ = capsys.readouterr()
+ list_models_output = out.splitlines()
+ assert "Model id: " in list_models_output[2]
+
+ # get model
+ model_id = list_models_output[2].split()[2]
+ automl_translation_model.get_model(project_id, compute_region, model_id)
+ out, _ = capsys.readouterr()
+ assert "Model name: " in out
+
+ # list model evaluations
+ automl_translation_model.list_model_evaluations(
+ project_id, compute_region, model_id, ""
+ )
+ out, _ = capsys.readouterr()
+ list_evals_output = out.splitlines()
+ assert "name: " in list_evals_output[1]
+
+ # get model evaluation
+ model_evaluation_id = list_evals_output[1].split("/")[-1][:-1]
+ automl_translation_model.get_model_evaluation(
+ project_id, compute_region, model_id, model_evaluation_id
+ )
+ out, _ = capsys.readouterr()
+ assert "evaluation_metric" in out
diff --git a/automl/snippets/predict_test.py b/automl/snippets/predict_test.py
new file mode 100644
index 000000000000..87aea8faa5b0
--- /dev/null
+++ b/automl/snippets/predict_test.py
@@ -0,0 +1,31 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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 os
+
+import automl_translation_predict
+
+project_id = os.environ["GCLOUD_PROJECT"]
+compute_region = "us-central1"
+
+
+def test_predict(capsys):
+ model_id = "3128559826197068699"
+ automl_translation_predict.predict(
+ project_id, compute_region, model_id, "resources/input.txt", False
+ )
+ out, _ = capsys.readouterr()
+ assert "Translated content: " in out