Language Automl samples (#126)

* intial Natural Language commit

* fixed input path for skipped model test

* removed DS store, attempting linter again

* attempted linter fix

* removed lodash

* package json test directive fix, LLC fix

* dependencies for mathjs, automl in sample file added

* path fixes, project id fixes, test fixes

* comment/test cleanup

* fixed tutorial file

* manual readme update

* readme path fix model

* mefailenglishthat'sunmpossible spelling fix

* style fix for console statements

* Style fixes; thanks Ace!

* path fix!

* Fix ENV variable for project Id (GCLOUD_PROJECT)

* Language AutoML samples

* fixing lint issues

* Converting test to mocha

* Checking if Kokoro failure was a blip

cloud-language/snippets/automl/.eslintrc.yml

@@ -0,0 +1,3 @@
+---
+rules:
+  no-console: off

cloud-language/snippets/automl/automlNaturalLanguageDataset.js

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+/**
+ * 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 Natural Language API.
+ *
+ * For more information, see the documentation at
+ * https://cloud.google.com/natural-language/automl/docs/
+ */
+
+`use strict`;
+
+function createDataset(projectId, computeRegion, datasetName, multilabel) {
+  // [START automl_natural_language_createDataset]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const datasetName = `name of the dataset to create, e.g. “myDataset”`;
+  // const multiLabel = `type of the classification problem, e.g “False”, “True” (multilabel)`;
+
+  // A resource that represents Google Cloud Platform location.
+  const projectLocation = client.locationPath(projectId, computeRegion);
+
+  // Classification type is assigned based on multilabel value.
+  let classificationType = `MULTICLASS`;
+  if (multilabel) {
+    classificationType = `MULTILABEL`;
+  }
+
+  // Set dataset name and metadata.
+  const myDataset = {
+    displayName: datasetName,
+    textClassificationDatasetMetadata: {
+      classificationType: classificationType,
+    },
+  };
+
+  // Create a dataset with the dataset metadata in the region.
+  client
+    .createDataset({parent: projectLocation, dataset: myDataset})
+    .then(responses => {
+      const dataset = responses[0];
+
+      // Display the dataset information.
+      console.log(`Dataset name: ${dataset.name}`);
+      console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+      console.log(`Dataset display name: ${dataset.displayName}`);
+      console.log(`Dataset example count: ${dataset.exampleCount}`);
+      console.log(`Text classification type:`);
+      console.log(
+        `\t ${dataset.textClassificationDatasetMetadata.classificationType}`
+      );
+      console.log(`Dataset create time:`);
+      console.log(`\tseconds: ${dataset.createTime.seconds}`);
+      console.log(`\tnanos: ${dataset.createTime.nanos}`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_createDataset]
+}
+
+function listDatasets(projectId, computeRegion, filter) {
+  // [START automl_natural_language_listDatasets]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const filter_ = `filter expressions, must specify field e.g. “imageClassificationModelMetadata:*”`;
+
+  // A resource that represents a Google Cloud Platform location.
+  const projectLocation = client.locationPath(projectId, computeRegion);
+
+  // List all the datasets available in the region by applying filter.
+  client
+    .listDatasets({parent: projectLocation, filter: filter})
+    .then(responses => {
+      const datasets = responses[0];
+
+      // Display the dataset information.
+      console.log(`List of datasets:`);
+      datasets.forEach(dataset => {
+        console.log(`Dataset name: ${dataset.name}`);
+        console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+        console.log(`Dataset display name: ${dataset.displayName}`);
+        console.log(`Dataset example count: ${dataset.exampleCount}`);
+        console.log(`Text classification type:`);
+        console.log(
+          `\t ${dataset.textClassificationDatasetMetadata.classificationType}`
+        );
+        console.log(`Dataset create time: `);
+        console.log(`\tseconds: ${dataset.createTime.seconds}`);
+        console.log(`\tnanos: ${dataset.createTime.nanos}`);
+        console.log(`\n`);
+      });
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_listDatasets]
+}
+
+function getDataset(projectId, computeRegion, datasetId) {
+  // [START automl_natural_language_getDataset]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const datasetId = `Id of the dataset`;
+
+  // Get the full path of the dataset.
+  const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);
+
+  // Get complete detail of the dataset.
+  client
+    .getDataset({name: datasetFullId})
+    .then(responses => {
+      const dataset = responses[0];
+
+      // Display the dataset information.
+      console.log(`Dataset name: ${dataset.name}`);
+      console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+      console.log(`Dataset display name: ${dataset.displayName}`);
+      console.log(`Dataset example count: ${dataset.exampleCount}`);
+      console.log(
+        `Text classification type: ${
+          dataset.textClassificationDatasetMetadata.classificationType
+        }`
+      );
+      console.log(`Dataset create time: `);
+      console.log(`\tseconds: ${dataset.createTime.seconds}`);
+      console.log(`\tnanos: ${dataset.createTime.nanos}`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_getDataset]
+}
+
+function importData(projectId, computeRegion, datasetId, path) {
+  // [START automl_natural_language_importDataset]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const datasetId = `Id of the dataset`;
+  // const path = `string or array of .csv paths in AutoML Vision CSV format, e.g. “gs://myproject/mytraindata.csv”;`
+
+  // Get the full path of the dataset.
+  const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);
+
+  // Get the multiple Google Cloud Storage URIs.
+  const inputUris = path.split(`,`);
+  const inputConfig = {
+    gcsSource: {
+      inputUris: inputUris,
+    },
+  };
+
+  // Import the dataset from the input URI.
+  client
+    .importData({name: datasetFullId, inputConfig: inputConfig})
+    .then(responses => {
+      const operation = responses[0];
+      console.log(`Processing import...`);
+      return operation.promise();
+    })
+    .then(responses => {
+      // The final result of the operation.
+      if (responses[2].done === true) console.log(`Data imported.`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_importDataset]
+}
+
+function exportData(projectId, computeRegion, datasetId, outputUri) {
+  // [START automl_natural_language_exportDataset]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const datasetId = `Id of the dataset`;
+  // const outputUri = `Google Cloud Storage URI for the export directory, e.g. “gs://myproject/output”;`
+
+  // Get the full path of the dataset.
+  const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);
+
+  // Set the output URI
+  const outputConfig = {
+    gcsDestination: {
+      outputUriPrefix: outputUri,
+    },
+  };
+
+  // Export the data to the output URI.
+  client
+    .exportData({name: datasetFullId, outputConfig: outputConfig})
+    .then(responses => {
+      const operation = responses[0];
+      console.log(`Processing export...`);
+      return operation.promise();
+    })
+    .then(responses => {
+      // The final result of the operation.
+      if (responses[2].done === true) console.log(`Data exported.`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_exportDataset]
+}
+
+function deleteDataset(projectId, computeRegion, datasetId) {
+  // [START automl_natural_language_deleteDataset]
+  const automl = require(`@google-cloud/automl`);
+
+  const client = new automl.v1beta1.AutoMlClient();
+
+  /**
+   * TODO(developer): Uncomment the following line before running the sample.
+   */
+  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
+  // const computeRegion = `region-name, e.g. "us-central1"`;
+  // const datasetId = `Id of the dataset`;
+
+  // Get the full path of the dataset.
+  const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);
+
+  // Delete a dataset.
+  client
+    .deleteDataset({name: datasetFullId})
+    .then(responses => {
+      const operation = responses[0];
+      return operation.promise();
+    })
+    .then(responses => {
+      // The final result of the operation.
+      if (responses[2].done === true) console.log(`Dataset deleted.`);
+    })
+    .catch(err => {
+      console.error(err);
+    });
+  // [END automl_natural_language_deleteDataset]
+}
+
+require(`yargs`)
+  .demand(1)
+  .options({
+    computeRegion: {
+      alias: `c`,
+      type: `string`,
+      default: process.env.REGION_NAME,
+      requiresArg: true,
+      description: `region name e.g. "us-central1"`,
+    },
+    datasetName: {
+      alias: `n`,
+      type: `string`,
+      default: `testDataSet`,
+      requiresArg: true,
+      description: `Name of the Dataset`,
+    },
+    datasetId: {
+      alias: `i`,
+      type: `string`,
+      requiresArg: true,
+      description: `Id of the dataset`,
+    },
+    filter: {
+      alias: `f`,
+      default: `text_classification_dataset_metadata:*`,
+      type: `string`,
+      requiresArg: false,
+      description: `filter expression`,
+    },
+    multilabel: {
+      alias: `m`,
+      type: `string`,
+      default: false,
+      requiresArg: true,
+      description:
+        `Type of the classification problem, ` +
+        `False - MULTICLASS, True - MULTILABEL.`,
+    },
+    outputUri: {
+      alias: `o`,
+      type: `string`,
+      requiresArg: true,
+      description: `URI (or local path) to export dataset`,
+    },
+    path: {
+      alias: `p`,
+      type: `string`,
+      global: true,
+      default: `gs://nodejs-docs-samples-vcm/flowerTraindataMini.csv`,
+      requiresArg: true,
+      description: `URI or local path to input .csv, or array of .csv paths`,
+    },
+    projectId: {
+      alias: `z`,
+      type: `number`,
+      default: process.env.GCLOUD_PROJECT,
+      requiresArg: true,
+      description: `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`,
+    },
+  })
+  .command(`create-dataset`, `creates a new Dataset`, {}, opts =>
+    createDataset(
+      opts.projectId,
+      opts.computeRegion,
+      opts.datasetName,
+      opts.multilabel
+    )
+  )
+  .command(`list-datasets`, `list all Datasets`, {}, opts =>
+    listDatasets(opts.projectId, opts.computeRegion, opts.filter)
+  )
+  .command(`get-dataset`, `Get a Dataset`, {}, opts =>
+    getDataset(opts.projectId, opts.computeRegion, opts.datasetId)
+  )
+  .command(`delete-dataset`, `Delete a dataset`, {}, opts =>
+    deleteDataset(opts.projectId, opts.computeRegion, opts.datasetId)
+  )
+  .command(`import-data`, `Import labeled items into dataset`, {}, opts =>
+    importData(opts.projectId, opts.computeRegion, opts.datasetId, opts.path)
+  )
+  .command(
+    `export-data`,
+    `Export a dataset to a Google Cloud Storage Bucket`,
+    {},
+    opts =>
+      exportData(
+        opts.projectId,
+        opts.computeRegion,
+        opts.datasetId,
+        opts.outputUri
+      )
+  )
+  .example(`node $0 create-dataset -n "newDataSet"`)
+  .example(`node $0 list-datasets -f "imageClassificationDatasetMetadata:*"`)
+  .example(`node $0 get-dataset -i "DATASETID"`)
+  .example(`node $0 delete-dataset -i "DATASETID"`)
+  .example(
+    `node $0 import-data -i "dataSetId" -p "gs://myproject/mytraindata.csv"`
+  )
+  .example(
+    `node $0 export-data -i "dataSetId" -o "gs://myproject/outputdestination.csv"`
+  )
+  .wrap(120)
+  .recommendCommands()
+  .help()
+  .strict().argv;