v1beta1.AutoMlClient

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
const dataset = {};
const request = {
  parent: formattedParent,
  dataset: dataset,
};
client.createDataset(request)
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
const model = {};
const request = {
  parent: formattedParent,
  model: model,
};

// Handle the operation using the promise pattern.
client.createModel(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
const model = {};
const request = {
  parent: formattedParent,
  model: model,
};

// Handle the operation using the event emitter pattern.
client.createModel(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
const model = {};
const request = {
  parent: formattedParent,
  model: model,
};

// Handle the operation using the await pattern.
const [operation] = await client.createModel(request);

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');

// Handle the operation using the promise pattern.
client.deleteDataset({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');

// Handle the operation using the event emitter pattern.
client.deleteDataset({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');

// Handle the operation using the await pattern.
const [operation] = await client.deleteDataset({name: formattedName});

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the promise pattern.
client.deleteModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the event emitter pattern.
client.deleteModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the await pattern.
const [operation] = await client.deleteModel({name: formattedName});

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the promise pattern.
client.deployModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the event emitter pattern.
client.deployModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the await pattern.
const [operation] = await client.deployModel({name: formattedName});

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the promise pattern.
client.exportData(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the event emitter pattern.
client.exportData(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the await pattern.
const [operation] = await client.exportData(request);

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the promise pattern.
client.exportEvaluatedExamples(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the event emitter pattern.
client.exportEvaluatedExamples(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the await pattern.
const [operation] = await client.exportEvaluatedExamples(request);

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the promise pattern.
client.exportModel(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the event emitter pattern.
client.exportModel(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
const outputConfig = {};
const request = {
  name: formattedName,
  outputConfig: outputConfig,
};

// Handle the operation using the await pattern.
const [operation] = await client.exportModel(request);

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.annotationSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[ANNOTATION_SPEC]');
client.getAnnotationSpec({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.columnSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]', '[COLUMN_SPEC]');
client.getColumnSpec({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
client.getDataset({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
client.getModel({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelEvaluationPath('[PROJECT]', '[LOCATION]', '[MODEL]', '[MODEL_EVALUATION]');
client.getModelEvaluation({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
client.getTableSpec({name: formattedName})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const inputConfig = {};
const request = {
  name: formattedName,
  inputConfig: inputConfig,
};

// Handle the operation using the promise pattern.
client.importData(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const inputConfig = {};
const request = {
  name: formattedName,
  inputConfig: inputConfig,
};

// Handle the operation using the event emitter pattern.
client.importData(request)
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
const inputConfig = {};
const request = {
  name: formattedName,
  inputConfig: inputConfig,
};

// Handle the operation using the await pattern.
const [operation] = await client.importData(request);

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

// Iterate over all elements.
const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');

client.listColumnSpecs({parent: formattedParent})
  .then(responses => {
    const resources = responses[0];
    for (const resource of resources) {
      // doThingsWith(resource)
    }
  })
  .catch(err => {
    console.error(err);
  });

// Or obtain the paged response.
const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');


const options = {autoPaginate: false};
const callback = responses => {
  // The actual resources in a response.
  const resources = responses[0];
  // The next request if the response shows that there are more responses.
  const nextRequest = responses[1];
  // The actual response object, if necessary.
  // const rawResponse = responses[2];
  for (const resource of resources) {
    // doThingsWith(resource);
  }
  if (nextRequest) {
    // Fetch the next page.
    return client.listColumnSpecs(nextRequest, options).then(callback);
  }
}
client.listColumnSpecs({parent: formattedParent}, options)
  .then(callback)
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
client.listColumnSpecsStream({parent: formattedParent})
  .on('data', element => {
    // doThingsWith(element)
  }).on('error', err => {
    console.log(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

// Iterate over all elements.
const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');

client.listDatasets({parent: formattedParent})
  .then(responses => {
    const resources = responses[0];
    for (const resource of resources) {
      // doThingsWith(resource)
    }
  })
  .catch(err => {
    console.error(err);
  });

// Or obtain the paged response.
const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');


const options = {autoPaginate: false};
const callback = responses => {
  // The actual resources in a response.
  const resources = responses[0];
  // The next request if the response shows that there are more responses.
  const nextRequest = responses[1];
  // The actual response object, if necessary.
  // const rawResponse = responses[2];
  for (const resource of resources) {
    // doThingsWith(resource);
  }
  if (nextRequest) {
    // Fetch the next page.
    return client.listDatasets(nextRequest, options).then(callback);
  }
}
client.listDatasets({parent: formattedParent}, options)
  .then(callback)
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
client.listDatasetsStream({parent: formattedParent})
  .on('data', element => {
    // doThingsWith(element)
  }).on('error', err => {
    console.log(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

// Iterate over all elements.
const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

client.listModelEvaluations({parent: formattedParent})
  .then(responses => {
    const resources = responses[0];
    for (const resource of resources) {
      // doThingsWith(resource)
    }
  })
  .catch(err => {
    console.error(err);
  });

// Or obtain the paged response.
const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');


const options = {autoPaginate: false};
const callback = responses => {
  // The actual resources in a response.
  const resources = responses[0];
  // The next request if the response shows that there are more responses.
  const nextRequest = responses[1];
  // The actual response object, if necessary.
  // const rawResponse = responses[2];
  for (const resource of resources) {
    // doThingsWith(resource);
  }
  if (nextRequest) {
    // Fetch the next page.
    return client.listModelEvaluations(nextRequest, options).then(callback);
  }
}
client.listModelEvaluations({parent: formattedParent}, options)
  .then(callback)
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
client.listModelEvaluationsStream({parent: formattedParent})
  .on('data', element => {
    // doThingsWith(element)
  }).on('error', err => {
    console.log(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

// Iterate over all elements.
const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');

client.listModels({parent: formattedParent})
  .then(responses => {
    const resources = responses[0];
    for (const resource of resources) {
      // doThingsWith(resource)
    }
  })
  .catch(err => {
    console.error(err);
  });

// Or obtain the paged response.
const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');


const options = {autoPaginate: false};
const callback = responses => {
  // The actual resources in a response.
  const resources = responses[0];
  // The next request if the response shows that there are more responses.
  const nextRequest = responses[1];
  // The actual response object, if necessary.
  // const rawResponse = responses[2];
  for (const resource of resources) {
    // doThingsWith(resource);
  }
  if (nextRequest) {
    // Fetch the next page.
    return client.listModels(nextRequest, options).then(callback);
  }
}
client.listModels({parent: formattedParent}, options)
  .then(callback)
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
client.listModelsStream({parent: formattedParent})
  .on('data', element => {
    // doThingsWith(element)
  }).on('error', err => {
    console.log(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

// Iterate over all elements.
const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');

client.listTableSpecs({parent: formattedParent})
  .then(responses => {
    const resources = responses[0];
    for (const resource of resources) {
      // doThingsWith(resource)
    }
  })
  .catch(err => {
    console.error(err);
  });

// Or obtain the paged response.
const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');


const options = {autoPaginate: false};
const callback = responses => {
  // The actual resources in a response.
  const resources = responses[0];
  // The next request if the response shows that there are more responses.
  const nextRequest = responses[1];
  // The actual response object, if necessary.
  // const rawResponse = responses[2];
  for (const resource of resources) {
    // doThingsWith(resource);
  }
  if (nextRequest) {
    // Fetch the next page.
    return client.listTableSpecs(nextRequest, options).then(callback);
  }
}
client.listTableSpecs({parent: formattedParent}, options)
  .then(callback)
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
client.listTableSpecsStream({parent: formattedParent})
  .on('data', element => {
    // doThingsWith(element)
  }).on('error', err => {
    console.log(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the promise pattern.
client.undeployModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Operation#promise starts polling for the completion of the LRO.
    return operation.promise();
  })
  .then(responses => {
    const result = responses[0];
    const metadata = responses[1];
    const finalApiResponse = responses[2];
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the event emitter pattern.
client.undeployModel({name: formattedName})
  .then(responses => {
    const [operation, initialApiResponse] = responses;

    // Adding a listener for the "complete" event starts polling for the
    // completion of the operation.
    operation.on('complete', (result, metadata, finalApiResponse) => {
      // doSomethingWith(result);
    });

    // Adding a listener for the "progress" event causes the callback to be
    // called on any change in metadata when the operation is polled.
    operation.on('progress', (metadata, apiResponse) => {
      // doSomethingWith(metadata)
    });

    // Adding a listener for the "error" event handles any errors found during polling.
    operation.on('error', err => {
      // throw(err);
    });
  })
  .catch(err => {
    console.error(err);
  });

const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');

// Handle the operation using the await pattern.
const [operation] = await client.undeployModel({name: formattedName});

const [response] = await operation.promise();

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const columnSpec = {};
client.updateColumnSpec({columnSpec: columnSpec})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const dataset = {};
client.updateDataset({dataset: dataset})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });

const automl = require('@google-cloud/automl');

const client = new automl.v1beta1.AutoMlClient({
  // optional auth parameters.
});

const tableSpec = {};
client.updateTableSpec({tableSpec: tableSpec})
  .then(responses => {
    const response = responses[0];
    // doThingsWith(response)
  })
  .catch(err => {
    console.error(err);
  });