Automl ga base samples (#2613)

* automl: add base samples

* automl: add base set of samples

* Clean up tests

* License year 2020, drop python2 print statement unicode

* use centralized automl testing project

* Fix GCS path typo

* Use fake dataset for batch predict

* lint: line length

* fix fixture naming and use

* Fix fixture changes

* Catch resource exhausted error

* use fake data for import test

* update how to access an operation id

Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>

automl/cloud-client/batch_predict.py

@@ -0,0 +1,52 @@
+# 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.
+
+
+def batch_predict(project_id, model_id, input_uri, output_uri):
+    """Batch predict"""
+    # [START automl_batch_predict]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+    # model_id = "YOUR_MODEL_ID"
+    # input_uri = "gs://YOUR_BUCKET_ID/path/to/your/input/csv_or_jsonl"
+    # output_uri = "gs://YOUR_BUCKET_ID/path/to/save/results/"
+
+    prediction_client = automl.PredictionServiceClient()
+
+    # Get the full path of the model.
+    model_full_id = prediction_client.model_path(
+        project_id, "us-central1", model_id
+    )
+
+    gcs_source = automl.types.GcsSource(input_uris=[input_uri])
+
+    input_config = automl.types.BatchPredictInputConfig(gcs_source=gcs_source)
+    gcs_destination = automl.types.GcsDestination(output_uri_prefix=output_uri)
+    output_config = automl.types.BatchPredictOutputConfig(
+        gcs_destination=gcs_destination
+    )
+
+    response = prediction_client.batch_predict(
+        model_full_id, input_config, output_config
+    )
+
+    print("Waiting for operation to complete...")
+    print(
+        "Batch Prediction results saved to Cloud Storage bucket. {}".format(
+            response.result()
+        )
+    )
+    # [END automl_batch_predict]

automl/cloud-client/batch_predict_test.py

@@ -0,0 +1,47 @@
+# 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 ladnguage governing permissions and
+# limitations under the License.
+
+import datetime
+import os
+
+import batch_predict
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+BUCKET_ID = "{}-lcm".format(PROJECT_ID)
+MODEL_ID = "TEN0000000000000000000"
+PREFIX = "TEST_EXPORT_OUTPUT_" + datetime.datetime.now().strftime(
+    "%Y%m%d%H%M%S"
+)
+
+
+def test_batch_predict(capsys):
+    # As batch prediction can take a long time. Try to batch predict on a model
+    # and confirm that the model was not found, but other elements of the
+    # request were valid.
+    try:
+        input_uri = "gs://{}/entity-extraction/input.jsonl".format(BUCKET_ID)
+        output_uri = "gs://{}/{}/".format(BUCKET_ID, PREFIX)
+        batch_predict.batch_predict(
+            PROJECT_ID, MODEL_ID, input_uri, output_uri
+        )
+        out, _ = capsys.readouterr()
+        assert (
+            "The model is either not found or not supported for prediction yet"
+            in out
+        )
+    except Exception as e:
+        assert (
+            "The model is either not found or not supported for prediction yet"
+            in e.message
+        )

automl/cloud-client/delete_dataset_test.py

@@ -25,7 +25,7 @@
 
 
 @pytest.fixture(scope="function")
-def create_dataset():
+def dataset_id():
     client = automl.AutoMlClient()
     project_location = client.location_path(PROJECT_ID, "us-central1")
     display_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
@@ -39,8 +39,8 @@ def create_dataset():
     yield dataset_id
 
 
-def test_delete_dataset(capsys, create_dataset):
+def test_delete_dataset(capsys, dataset_id):
     # delete dataset
-    delete_dataset.delete_dataset(PROJECT_ID, create_dataset)
+    delete_dataset.delete_dataset(PROJECT_ID, dataset_id)
     out, _ = capsys.readouterr()
     assert "Dataset deleted." in out

automl/cloud-client/get_model_evaluation_test.py

@@ -24,7 +24,7 @@
 
 
 @pytest.fixture(scope="function")
-def get_evaluation_id():
+def model_evaluation_id():
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
     evaluation = None
@@ -37,9 +37,9 @@ def get_evaluation_id():
     yield model_evaluation_id
 
 
-def test_get_model_evaluation(capsys, get_evaluation_id):
+def test_get_model_evaluation(capsys, model_evaluation_id):
     get_model_evaluation.get_model_evaluation(
-        PROJECT_ID, MODEL_ID, get_evaluation_id
+        PROJECT_ID, MODEL_ID, model_evaluation_id
     )
     out, _ = capsys.readouterr()
     assert "Model evaluation name: " in out

automl/cloud-client/get_operation_status.py

@@ -0,0 +1,34 @@
+# 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.
+
+
+def get_operation_status(operation_full_id):
+    """Get operation status."""
+    # [START automl_get_operation_status]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # operation_full_id = \
+    #     "projects/[projectId]/locations/us-central1/operations/[operationId]"
+
+    client = automl.AutoMlClient()
+    # Get the latest state of a long-running operation.
+    response = client.transport._operations_client.get_operation(
+        operation_full_id
+    )
+
+    print("Name: {}".format(response.name))
+    print("Operation details:")
+    print(response)
+    # [END automl_get_operation_status]

automl/cloud-client/get_operation_status_test.py

@@ -0,0 +1,40 @@
+# 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 os
+
+from google.cloud import automl
+import pytest
+
+import get_operation_status
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+
+
+@pytest.fixture(scope="function")
+def operation_id():
+    client = automl.AutoMlClient()
+    project_location = client.location_path(PROJECT_ID, "us-central1")
+    generator = client.transport._operations_client.list_operations(
+        project_location, filter_=""
+    ).pages
+    page = next(generator)
+    operation = page.next()
+    yield operation.name
+
+
+def test_get_operation_status(capsys, operation_id):
+    get_operation_status.get_operation_status(operation_id)
+    out, _ = capsys.readouterr()
+    assert "Operation details" in out

automl/cloud-client/import_dataset_test.py

@@ -12,49 +12,30 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import datetime
 import os
 
-from google.cloud import automl
-import pytest
-
 import import_dataset
 
 PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
 BUCKET_ID = "{}-lcm".format(PROJECT_ID)
-
-
-@pytest.fixture(scope="function")
-def create_dataset():
-    client = automl.AutoMlClient()
-    project_location = client.location_path(PROJECT_ID, "us-central1")
-    display_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
-    metadata = automl.types.TextSentimentDatasetMetadata(
-        sentiment_max=4
-    )
-    dataset = automl.types.Dataset(
-        display_name=display_name, text_sentiment_dataset_metadata=metadata
-    )
-    response = client.create_dataset(project_location, dataset)
-    dataset_id = response.result().name.split("/")[-1]
-
-    yield dataset_id
-
-
-@pytest.mark.slow
-def test_import_dataset(capsys, create_dataset):
-    data = (
-        "gs://{}/sentiment-analysis/dataset.csv".format(BUCKET_ID)
-    )
-    dataset_id = create_dataset
-    import_dataset.import_dataset(PROJECT_ID, dataset_id, data)
-    out, _ = capsys.readouterr()
-    assert "Data imported." in out
-
-    # delete created dataset
-    client = automl.AutoMlClient()
-    dataset_full_id = client.dataset_path(
-        PROJECT_ID, "us-central1", dataset_id
-    )
-    response = client.delete_dataset(dataset_full_id)
-    response.result()
+DATASET_ID = "TEN0000000000000000000"
+
+
+def test_import_dataset(capsys):
+    # As importing a dataset can take a long time and only four operations can
+    # be run on a dataset at once. Try to import into a nonexistent dataset and
+    # confirm that the dataset was not found, but other elements of the request
+    # were valid.
+    try:
+        data = "gs://{}/sentiment-analysis/dataset.csv".format(BUCKET_ID)
+        import_dataset.import_dataset(PROJECT_ID, DATASET_ID, data)
+        out, _ = capsys.readouterr()
+        assert (
+            "The Dataset doesn't exist or is inaccessible for use with AutoMl."
+            in out
+        )
+    except Exception as e:
+        assert (
+            "The Dataset doesn't exist or is inaccessible for use with AutoMl."
+            in e.message
+        )

automl/cloud-client/language_sentiment_analysis_predict_test.py

@@ -23,8 +23,9 @@
 MODEL_ID = os.environ["SENTIMENT_ANALYSIS_MODEL_ID"]
 
 
-@pytest.fixture(scope="function")
-def verify_model_state():
+@pytest.fixture(scope="function", autouse=True)
+def setup():
+    # Verify the model is deployed before trying to predict
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
 
@@ -35,8 +36,7 @@ def verify_model_state():
         response.result()
 
 
-def test_sentiment_analysis_predict(capsys, verify_model_state):
-    verify_model_state
+def test_sentiment_analysis_predict(capsys):
     text = "Hopefully this Claritin kicks in soon"
     language_sentiment_analysis_predict.predict(PROJECT_ID, MODEL_ID, text)
     out, _ = capsys.readouterr()

automl/cloud-client/list_operation_status.py

@@ -0,0 +1,37 @@
+# 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.
+
+
+def list_operation_status(project_id):
+    """List operation status."""
+    # [START automl_list_operation_status]
+    from google.cloud import automl
+
+    # TODO(developer): Uncomment and set the following variables
+    # project_id = "YOUR_PROJECT_ID"
+
+    client = automl.AutoMlClient()
+    # A resource that represents Google Cloud Platform location.
+    project_location = client.location_path(project_id, "us-central1")
+    # List all the operations names available in the region.
+    response = client.transport._operations_client.list_operations(
+        project_location, ""
+    )
+
+    print("List of operations:")
+    for operation in response:
+        print("Name: {}".format(operation.name))
+        print("Operation details:")
+        print(operation)
+    # [END automl_list_operation_status]

automl/cloud-client/list_operation_status_test.py

@@ -0,0 +1,28 @@
+# 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 os
+
+import pytest
+
+import list_operation_status
+
+PROJECT_ID = os.environ["AUTOML_PROJECT_ID"]
+
+
+@pytest.mark.slow
+def test_list_operation_status(capsys):
+    list_operation_status.list_operation_status(PROJECT_ID)
+    out, _ = capsys.readouterr()
+    assert "Operation details" in out

automl/cloud-client/translate_predict_test.py

@@ -23,8 +23,9 @@
 MODEL_ID = os.environ["TRANSLATION_MODEL_ID"]
 
 
-@pytest.fixture(scope="function")
-def verify_model_state():
+@pytest.fixture(scope="function", autouse=True)
+def setup():
+    # Verify the model is deployed before trying to predict
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
 
@@ -35,8 +36,7 @@ def verify_model_state():
         response.result()
 
 
-def test_translate_predict(capsys, verify_model_state):
-    verify_model_state
+def test_translate_predict(capsys):
     translate_predict.predict(PROJECT_ID, MODEL_ID, "resources/input.txt")
     out, _ = capsys.readouterr()
     assert "Translated content: " in out