chore: Update discovery artifacts (#2298)

## Deleted keys were detected in the following stable discovery artifacts:
aiplatform v1 https://togithub.com/googleapis/google-api-python-client/commit/6f772fd6a95bf5b75b513ee971d67e9d65d45198
batch v1 https://togithub.com/googleapis/google-api-python-client/commit/dfe37392b9264470dbac3a0fe76d63d18b2f8dfd
connectors v1 https://togithub.com/googleapis/google-api-python-client/commit/7f2654064fa1a2ecafb4b77f59fa466ad1dbfc4a
datacatalog v1 https://togithub.com/googleapis/google-api-python-client/commit/2be21be6bced617d7649810ba7bbd750e5e876a0
gkehub v1 https://togithub.com/googleapis/google-api-python-client/commit/b1823e826dd40c4d9504374478887cc8f8ae5d9b
metastore v1 https://togithub.com/googleapis/google-api-python-client/commit/03d9f29e20ea4909b11777dbff60b5b2c2f0d957

## Deleted keys were detected in the following pre-stable discovery artifacts:
aiplatform v1beta1 https://togithub.com/googleapis/google-api-python-client/commit/6f772fd6a95bf5b75b513ee971d67e9d65d45198
datacatalog v1beta1 https://togithub.com/googleapis/google-api-python-client/commit/2be21be6bced617d7649810ba7bbd750e5e876a0
gkehub v1alpha https://togithub.com/googleapis/google-api-python-client/commit/b1823e826dd40c4d9504374478887cc8f8ae5d9b
gkehub v1beta https://togithub.com/googleapis/google-api-python-client/commit/b1823e826dd40c4d9504374478887cc8f8ae5d9b
metastore v1alpha https://togithub.com/googleapis/google-api-python-client/commit/03d9f29e20ea4909b11777dbff60b5b2c2f0d957
metastore v1beta https://togithub.com/googleapis/google-api-python-client/commit/03d9f29e20ea4909b11777dbff60b5b2c2f0d957
networksecurity v1beta1 https://togithub.com/googleapis/google-api-python-client/commit/a2e83231ab8ff47ce376869820872a02c6dbefed

## Discovery Artifact Change Summary:
feat(aiplatform): update the api https://togithub.com/googleapis/google-api-python-client/commit/6f772fd6a95bf5b75b513ee971d67e9d65d45198
feat(alloydb): update the api https://togithub.com/googleapis/google-api-python-client/commit/4ee2fcb08390011f600e0eb10c7ca187e0541241
feat(androidpublisher): update the api https://togithub.com/googleapis/google-api-python-client/commit/dc4e5e9fa277266469125fd34157059b6b5c47fb
feat(baremetalsolution): update the api https://togithub.com/googleapis/google-api-python-client/commit/79aa42dc6cea9849f6c675829e4d3a0c44f32a7d
feat(batch): update the api https://togithub.com/googleapis/google-api-python-client/commit/dfe37392b9264470dbac3a0fe76d63d18b2f8dfd
feat(bigquery): update the api https://togithub.com/googleapis/google-api-python-client/commit/804ef48218f875432437922e32706d1321019539
feat(cloudbilling): update the api https://togithub.com/googleapis/google-api-python-client/commit/bc285d7f5a537459962f76caa86c53a5aa24065d
feat(clouddeploy): update the api https://togithub.com/googleapis/google-api-python-client/commit/97509bb1c146902091c9ad3162160a7ef23009a2
feat(connectors): update the api https://togithub.com/googleapis/google-api-python-client/commit/7f2654064fa1a2ecafb4b77f59fa466ad1dbfc4a
feat(container): update the api https://togithub.com/googleapis/google-api-python-client/commit/67a8d7a791104026e5d15328f00adf072a2f3b88
feat(datacatalog): update the api https://togithub.com/googleapis/google-api-python-client/commit/2be21be6bced617d7649810ba7bbd750e5e876a0
feat(dataflow): update the api https://togithub.com/googleapis/google-api-python-client/commit/0c5d8136b39cc9d4fc41ffc146ef335f5799f655
feat(dns): update the api https://togithub.com/googleapis/google-api-python-client/commit/35ef8109d1a46bdd98d85412b4d705a45ce028f7
feat(gkehub): update the api https://togithub.com/googleapis/google-api-python-client/commit/b1823e826dd40c4d9504374478887cc8f8ae5d9b
feat(gkeonprem): update the api https://togithub.com/googleapis/google-api-python-client/commit/14b80769f732372d3b04497d0ca34303e7c98d1f
feat(metastore): update the api https://togithub.com/googleapis/google-api-python-client/commit/03d9f29e20ea4909b11777dbff60b5b2c2f0d957
feat(monitoring): update the api https://togithub.com/googleapis/google-api-python-client/commit/ab03f9c7832ef722bdbff6bec1b1c4fb893c9420
feat(networkmanagement): update the api https://togithub.com/googleapis/google-api-python-client/commit/3ddf64cdd3002df20b6ba1d0225d2e641291230a
feat(networksecurity): update the api https://togithub.com/googleapis/google-api-python-client/commit/a2e83231ab8ff47ce376869820872a02c6dbefed
feat(networkservices): update the api https://togithub.com/googleapis/google-api-python-client/commit/9490509110585776a9f4676fd76248308494cc29
feat(playdeveloperreporting): update the api https://togithub.com/googleapis/google-api-python-client/commit/8e799b77800cfaa3f759cc52ef36b73533fe66d0
feat(pubsub): update the api https://togithub.com/googleapis/google-api-python-client/commit/ce81218ef023be0c925ba73512faa25cd96a4a70
feat(script): update the api https://togithub.com/googleapis/google-api-python-client/commit/a2c6f6f73228ce5612ce238b25b8ad95895d9eee
feat(securitycenter): update the api https://togithub.com/googleapis/google-api-python-client/commit/9d79a685e826b937ca8f4aa5e83fac3c940976c0
feat(vpcaccess): update the api https://togithub.com/googleapis/google-api-python-client/commit/7e2f29aeef1f60b36d310664a709f7bc911f16d6

docs/dyn/aiplatform_v1.projects.locations.batchPredictionJobs.html

@@ -288,10 +288,10 @@ <h3>Method Details</h3>
     &quot;instancesFormat&quot;: &quot;A String&quot;, # Required. The format in which instances are given, must be one of the Model&#x27;s supported_input_storage_formats.
   },
   &quot;instanceConfig&quot;: { # Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. # Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
-    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
-    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
     &quot;instanceType&quot;: &quot;A String&quot;, # The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the file.
@@ -558,10 +558,10 @@ <h3>Method Details</h3>
     &quot;instancesFormat&quot;: &quot;A String&quot;, # Required. The format in which instances are given, must be one of the Model&#x27;s supported_input_storage_formats.
   },
   &quot;instanceConfig&quot;: { # Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. # Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
-    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
-    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
     &quot;instanceType&quot;: &quot;A String&quot;, # The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the file.
@@ -870,10 +870,10 @@ <h3>Method Details</h3>
     &quot;instancesFormat&quot;: &quot;A String&quot;, # Required. The format in which instances are given, must be one of the Model&#x27;s supported_input_storage_formats.
   },
   &quot;instanceConfig&quot;: { # Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. # Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
-    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
-    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+    &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
       &quot;A String&quot;,
     ],
     &quot;instanceType&quot;: &quot;A String&quot;, # The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the file.
@@ -1153,10 +1153,10 @@ <h3>Method Details</h3>
         &quot;instancesFormat&quot;: &quot;A String&quot;, # Required. The format in which instances are given, must be one of the Model&#x27;s supported_input_storage_formats.
       },
       &quot;instanceConfig&quot;: { # Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. # Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
-        &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+        &quot;excludedFields&quot;: [ # Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
           &quot;A String&quot;,
         ],
-        &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
+        &quot;includedFields&quot;: [ # Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.
           &quot;A String&quot;,
         ],
         &quot;instanceType&quot;: &quot;A String&quot;, # The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{&quot;b64&quot;: }`, where `` is the Base64-encoded string of the content of the file.