params__ =
input.readMessage(
ParamsDefaultEntryHolder.defaultEntry.getParserForType(),
extensionRegistry);
internalGetMutableParams()
.getMutableMap()
.put(params__.getKey(), params__.getValue());
bitField0_ |= 0x00000008;
break;
} // case 18
case 26:
{
input.readMessage(getGcrDestinationFieldBuilder().getBuilder(), extensionRegistry);
destinationCase_ = 3;
break;
} // case 26
case 34:
{
modelFormat_ = input.readStringRequireUtf8();
bitField0_ |= 0x00000004;
break;
} // case 34
default:
{
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int destinationCase_ = 0;
private java.lang.Object destination_;
public DestinationCase getDestinationCase() {
return DestinationCase.forNumber(destinationCase_);
}
public Builder clearDestination() {
destinationCase_ = 0;
destination_ = null;
onChanged();
return this;
}
private int bitField0_;
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcsDestination,
com.google.cloud.automl.v1beta1.GcsDestination.Builder,
com.google.cloud.automl.v1beta1.GcsDestinationOrBuilder>
gcsDestinationBuilder_;
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*
* @return Whether the gcsDestination field is set.
*/
@java.lang.Override
public boolean hasGcsDestination() {
return destinationCase_ == 1;
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*
* @return The gcsDestination.
*/
@java.lang.Override
public com.google.cloud.automl.v1beta1.GcsDestination getGcsDestination() {
if (gcsDestinationBuilder_ == null) {
if (destinationCase_ == 1) {
return (com.google.cloud.automl.v1beta1.GcsDestination) destination_;
}
return com.google.cloud.automl.v1beta1.GcsDestination.getDefaultInstance();
} else {
if (destinationCase_ == 1) {
return gcsDestinationBuilder_.getMessage();
}
return com.google.cloud.automl.v1beta1.GcsDestination.getDefaultInstance();
}
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
public Builder setGcsDestination(com.google.cloud.automl.v1beta1.GcsDestination value) {
if (gcsDestinationBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
destination_ = value;
onChanged();
} else {
gcsDestinationBuilder_.setMessage(value);
}
destinationCase_ = 1;
return this;
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
public Builder setGcsDestination(
com.google.cloud.automl.v1beta1.GcsDestination.Builder builderForValue) {
if (gcsDestinationBuilder_ == null) {
destination_ = builderForValue.build();
onChanged();
} else {
gcsDestinationBuilder_.setMessage(builderForValue.build());
}
destinationCase_ = 1;
return this;
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
public Builder mergeGcsDestination(com.google.cloud.automl.v1beta1.GcsDestination value) {
if (gcsDestinationBuilder_ == null) {
if (destinationCase_ == 1
&& destination_
!= com.google.cloud.automl.v1beta1.GcsDestination.getDefaultInstance()) {
destination_ =
com.google.cloud.automl.v1beta1.GcsDestination.newBuilder(
(com.google.cloud.automl.v1beta1.GcsDestination) destination_)
.mergeFrom(value)
.buildPartial();
} else {
destination_ = value;
}
onChanged();
} else {
if (destinationCase_ == 1) {
gcsDestinationBuilder_.mergeFrom(value);
} else {
gcsDestinationBuilder_.setMessage(value);
}
}
destinationCase_ = 1;
return this;
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
public Builder clearGcsDestination() {
if (gcsDestinationBuilder_ == null) {
if (destinationCase_ == 1) {
destinationCase_ = 0;
destination_ = null;
onChanged();
}
} else {
if (destinationCase_ == 1) {
destinationCase_ = 0;
destination_ = null;
}
gcsDestinationBuilder_.clear();
}
return this;
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
public com.google.cloud.automl.v1beta1.GcsDestination.Builder getGcsDestinationBuilder() {
return getGcsDestinationFieldBuilder().getBuilder();
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
@java.lang.Override
public com.google.cloud.automl.v1beta1.GcsDestinationOrBuilder getGcsDestinationOrBuilder() {
if ((destinationCase_ == 1) && (gcsDestinationBuilder_ != null)) {
return gcsDestinationBuilder_.getMessageOrBuilder();
} else {
if (destinationCase_ == 1) {
return (com.google.cloud.automl.v1beta1.GcsDestination) destination_;
}
return com.google.cloud.automl.v1beta1.GcsDestination.getDefaultInstance();
}
}
/**
*
*
*
* The Google Cloud Storage location where the model is to be written to.
* This location may only be set for the following model formats:
* "tflite", "edgetpu_tflite", "tf_saved_model", "tf_js", "core_ml".
* Under the directory given as the destination a new one with name
* "model-export-<model-display-name>-<timestamp-of-export-call>",
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format,
* will be created. Inside the model and any of its supporting files
* will be written.
*
*
* .google.cloud.automl.v1beta1.GcsDestination gcs_destination = 1;
*/
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcsDestination,
com.google.cloud.automl.v1beta1.GcsDestination.Builder,
com.google.cloud.automl.v1beta1.GcsDestinationOrBuilder>
getGcsDestinationFieldBuilder() {
if (gcsDestinationBuilder_ == null) {
if (!(destinationCase_ == 1)) {
destination_ = com.google.cloud.automl.v1beta1.GcsDestination.getDefaultInstance();
}
gcsDestinationBuilder_ =
new com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcsDestination,
com.google.cloud.automl.v1beta1.GcsDestination.Builder,
com.google.cloud.automl.v1beta1.GcsDestinationOrBuilder>(
(com.google.cloud.automl.v1beta1.GcsDestination) destination_,
getParentForChildren(),
isClean());
destination_ = null;
}
destinationCase_ = 1;
onChanged();
return gcsDestinationBuilder_;
}
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcrDestination,
com.google.cloud.automl.v1beta1.GcrDestination.Builder,
com.google.cloud.automl.v1beta1.GcrDestinationOrBuilder>
gcrDestinationBuilder_;
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*
* @return Whether the gcrDestination field is set.
*/
@java.lang.Override
public boolean hasGcrDestination() {
return destinationCase_ == 3;
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*
* @return The gcrDestination.
*/
@java.lang.Override
public com.google.cloud.automl.v1beta1.GcrDestination getGcrDestination() {
if (gcrDestinationBuilder_ == null) {
if (destinationCase_ == 3) {
return (com.google.cloud.automl.v1beta1.GcrDestination) destination_;
}
return com.google.cloud.automl.v1beta1.GcrDestination.getDefaultInstance();
} else {
if (destinationCase_ == 3) {
return gcrDestinationBuilder_.getMessage();
}
return com.google.cloud.automl.v1beta1.GcrDestination.getDefaultInstance();
}
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
public Builder setGcrDestination(com.google.cloud.automl.v1beta1.GcrDestination value) {
if (gcrDestinationBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
destination_ = value;
onChanged();
} else {
gcrDestinationBuilder_.setMessage(value);
}
destinationCase_ = 3;
return this;
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
public Builder setGcrDestination(
com.google.cloud.automl.v1beta1.GcrDestination.Builder builderForValue) {
if (gcrDestinationBuilder_ == null) {
destination_ = builderForValue.build();
onChanged();
} else {
gcrDestinationBuilder_.setMessage(builderForValue.build());
}
destinationCase_ = 3;
return this;
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
public Builder mergeGcrDestination(com.google.cloud.automl.v1beta1.GcrDestination value) {
if (gcrDestinationBuilder_ == null) {
if (destinationCase_ == 3
&& destination_
!= com.google.cloud.automl.v1beta1.GcrDestination.getDefaultInstance()) {
destination_ =
com.google.cloud.automl.v1beta1.GcrDestination.newBuilder(
(com.google.cloud.automl.v1beta1.GcrDestination) destination_)
.mergeFrom(value)
.buildPartial();
} else {
destination_ = value;
}
onChanged();
} else {
if (destinationCase_ == 3) {
gcrDestinationBuilder_.mergeFrom(value);
} else {
gcrDestinationBuilder_.setMessage(value);
}
}
destinationCase_ = 3;
return this;
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
public Builder clearGcrDestination() {
if (gcrDestinationBuilder_ == null) {
if (destinationCase_ == 3) {
destinationCase_ = 0;
destination_ = null;
onChanged();
}
} else {
if (destinationCase_ == 3) {
destinationCase_ = 0;
destination_ = null;
}
gcrDestinationBuilder_.clear();
}
return this;
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
public com.google.cloud.automl.v1beta1.GcrDestination.Builder getGcrDestinationBuilder() {
return getGcrDestinationFieldBuilder().getBuilder();
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
@java.lang.Override
public com.google.cloud.automl.v1beta1.GcrDestinationOrBuilder getGcrDestinationOrBuilder() {
if ((destinationCase_ == 3) && (gcrDestinationBuilder_ != null)) {
return gcrDestinationBuilder_.getMessageOrBuilder();
} else {
if (destinationCase_ == 3) {
return (com.google.cloud.automl.v1beta1.GcrDestination) destination_;
}
return com.google.cloud.automl.v1beta1.GcrDestination.getDefaultInstance();
}
}
/**
*
*
*
* The GCR location where model image is to be pushed to. This location
* may only be set for the following model formats:
* "docker".
* The model image will be created under the given URI.
*
*
* .google.cloud.automl.v1beta1.GcrDestination gcr_destination = 3;
*/
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcrDestination,
com.google.cloud.automl.v1beta1.GcrDestination.Builder,
com.google.cloud.automl.v1beta1.GcrDestinationOrBuilder>
getGcrDestinationFieldBuilder() {
if (gcrDestinationBuilder_ == null) {
if (!(destinationCase_ == 3)) {
destination_ = com.google.cloud.automl.v1beta1.GcrDestination.getDefaultInstance();
}
gcrDestinationBuilder_ =
new com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1beta1.GcrDestination,
com.google.cloud.automl.v1beta1.GcrDestination.Builder,
com.google.cloud.automl.v1beta1.GcrDestinationOrBuilder>(
(com.google.cloud.automl.v1beta1.GcrDestination) destination_,
getParentForChildren(),
isClean());
destination_ = null;
}
destinationCase_ = 3;
onChanged();
return gcrDestinationBuilder_;
}
private java.lang.Object modelFormat_ = "";
/**
*
*
*
* The format in which the model must be exported. The available, and default,
* formats depend on the problem and model type (if given problem and type
* combination doesn't have a format listed, it means its models are not
* exportable):
* * For Image Classification mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js",
* "docker".
* * For Image Classification mobile-core-ml-low-latency-1,
* mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1:
* "core_ml" (default).
* * For Image Object Detection mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite", "tf_saved_model", "tf_js".
* * For Video Classification cloud,
* "tf_saved_model".
* * For Video Object Tracking cloud,
* "tf_saved_model".
* * For Video Object Tracking mobile-versatile-1:
* "tflite", "edgetpu_tflite", "tf_saved_model", "docker".
* * For Video Object Tracking mobile-coral-versatile-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-coral-low-latency-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-jetson-versatile-1:
* "tf_saved_model", "docker".
* * For Tables:
* "docker".
* Formats description:
* * tflite - Used for Android mobile devices.
* * edgetpu_tflite - Used for [Edge TPU](https://cloud.google.com/edge-tpu/)
* devices.
* * tf_saved_model - A tensorflow model in SavedModel format.
* * tf_js - A [TensorFlow.js](https://www.tensorflow.org/js) model that can
* be used in the browser and in Node.js using JavaScript.
* * docker - Used for Docker containers. Use the params field to customize
* the container. The container is verified to work correctly on
* ubuntu 16.04 operating system. See more at
* [containers
* quickstart](https:
* //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
* * core_ml - Used for iOS mobile devices.
*
*
* string model_format = 4;
*
* @return The modelFormat.
*/
public java.lang.String getModelFormat() {
java.lang.Object ref = modelFormat_;
if (!(ref instanceof java.lang.String)) {
com.google.protobuf.ByteString bs = (com.google.protobuf.ByteString) ref;
java.lang.String s = bs.toStringUtf8();
modelFormat_ = s;
return s;
} else {
return (java.lang.String) ref;
}
}
/**
*
*
*
* The format in which the model must be exported. The available, and default,
* formats depend on the problem and model type (if given problem and type
* combination doesn't have a format listed, it means its models are not
* exportable):
* * For Image Classification mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js",
* "docker".
* * For Image Classification mobile-core-ml-low-latency-1,
* mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1:
* "core_ml" (default).
* * For Image Object Detection mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite", "tf_saved_model", "tf_js".
* * For Video Classification cloud,
* "tf_saved_model".
* * For Video Object Tracking cloud,
* "tf_saved_model".
* * For Video Object Tracking mobile-versatile-1:
* "tflite", "edgetpu_tflite", "tf_saved_model", "docker".
* * For Video Object Tracking mobile-coral-versatile-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-coral-low-latency-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-jetson-versatile-1:
* "tf_saved_model", "docker".
* * For Tables:
* "docker".
* Formats description:
* * tflite - Used for Android mobile devices.
* * edgetpu_tflite - Used for [Edge TPU](https://cloud.google.com/edge-tpu/)
* devices.
* * tf_saved_model - A tensorflow model in SavedModel format.
* * tf_js - A [TensorFlow.js](https://www.tensorflow.org/js) model that can
* be used in the browser and in Node.js using JavaScript.
* * docker - Used for Docker containers. Use the params field to customize
* the container. The container is verified to work correctly on
* ubuntu 16.04 operating system. See more at
* [containers
* quickstart](https:
* //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
* * core_ml - Used for iOS mobile devices.
*
*
* string model_format = 4;
*
* @return The bytes for modelFormat.
*/
public com.google.protobuf.ByteString getModelFormatBytes() {
java.lang.Object ref = modelFormat_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
modelFormat_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
*
*
* The format in which the model must be exported. The available, and default,
* formats depend on the problem and model type (if given problem and type
* combination doesn't have a format listed, it means its models are not
* exportable):
* * For Image Classification mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js",
* "docker".
* * For Image Classification mobile-core-ml-low-latency-1,
* mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1:
* "core_ml" (default).
* * For Image Object Detection mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite", "tf_saved_model", "tf_js".
* * For Video Classification cloud,
* "tf_saved_model".
* * For Video Object Tracking cloud,
* "tf_saved_model".
* * For Video Object Tracking mobile-versatile-1:
* "tflite", "edgetpu_tflite", "tf_saved_model", "docker".
* * For Video Object Tracking mobile-coral-versatile-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-coral-low-latency-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-jetson-versatile-1:
* "tf_saved_model", "docker".
* * For Tables:
* "docker".
* Formats description:
* * tflite - Used for Android mobile devices.
* * edgetpu_tflite - Used for [Edge TPU](https://cloud.google.com/edge-tpu/)
* devices.
* * tf_saved_model - A tensorflow model in SavedModel format.
* * tf_js - A [TensorFlow.js](https://www.tensorflow.org/js) model that can
* be used in the browser and in Node.js using JavaScript.
* * docker - Used for Docker containers. Use the params field to customize
* the container. The container is verified to work correctly on
* ubuntu 16.04 operating system. See more at
* [containers
* quickstart](https:
* //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
* * core_ml - Used for iOS mobile devices.
*
*
* string model_format = 4;
*
* @param value The modelFormat to set.
* @return This builder for chaining.
*/
public Builder setModelFormat(java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
modelFormat_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* The format in which the model must be exported. The available, and default,
* formats depend on the problem and model type (if given problem and type
* combination doesn't have a format listed, it means its models are not
* exportable):
* * For Image Classification mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js",
* "docker".
* * For Image Classification mobile-core-ml-low-latency-1,
* mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1:
* "core_ml" (default).
* * For Image Object Detection mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite", "tf_saved_model", "tf_js".
* * For Video Classification cloud,
* "tf_saved_model".
* * For Video Object Tracking cloud,
* "tf_saved_model".
* * For Video Object Tracking mobile-versatile-1:
* "tflite", "edgetpu_tflite", "tf_saved_model", "docker".
* * For Video Object Tracking mobile-coral-versatile-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-coral-low-latency-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-jetson-versatile-1:
* "tf_saved_model", "docker".
* * For Tables:
* "docker".
* Formats description:
* * tflite - Used for Android mobile devices.
* * edgetpu_tflite - Used for [Edge TPU](https://cloud.google.com/edge-tpu/)
* devices.
* * tf_saved_model - A tensorflow model in SavedModel format.
* * tf_js - A [TensorFlow.js](https://www.tensorflow.org/js) model that can
* be used in the browser and in Node.js using JavaScript.
* * docker - Used for Docker containers. Use the params field to customize
* the container. The container is verified to work correctly on
* ubuntu 16.04 operating system. See more at
* [containers
* quickstart](https:
* //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
* * core_ml - Used for iOS mobile devices.
*
*
* string model_format = 4;
*
* @return This builder for chaining.
*/
public Builder clearModelFormat() {
modelFormat_ = getDefaultInstance().getModelFormat();
bitField0_ = (bitField0_ & ~0x00000004);
onChanged();
return this;
}
/**
*
*
*
* The format in which the model must be exported. The available, and default,
* formats depend on the problem and model type (if given problem and type
* combination doesn't have a format listed, it means its models are not
* exportable):
* * For Image Classification mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite" (default), "edgetpu_tflite", "tf_saved_model", "tf_js",
* "docker".
* * For Image Classification mobile-core-ml-low-latency-1,
* mobile-core-ml-versatile-1, mobile-core-ml-high-accuracy-1:
* "core_ml" (default).
* * For Image Object Detection mobile-low-latency-1, mobile-versatile-1,
* mobile-high-accuracy-1:
* "tflite", "tf_saved_model", "tf_js".
* * For Video Classification cloud,
* "tf_saved_model".
* * For Video Object Tracking cloud,
* "tf_saved_model".
* * For Video Object Tracking mobile-versatile-1:
* "tflite", "edgetpu_tflite", "tf_saved_model", "docker".
* * For Video Object Tracking mobile-coral-versatile-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-coral-low-latency-1:
* "tflite", "edgetpu_tflite", "docker".
* * For Video Object Tracking mobile-jetson-versatile-1:
* "tf_saved_model", "docker".
* * For Tables:
* "docker".
* Formats description:
* * tflite - Used for Android mobile devices.
* * edgetpu_tflite - Used for [Edge TPU](https://cloud.google.com/edge-tpu/)
* devices.
* * tf_saved_model - A tensorflow model in SavedModel format.
* * tf_js - A [TensorFlow.js](https://www.tensorflow.org/js) model that can
* be used in the browser and in Node.js using JavaScript.
* * docker - Used for Docker containers. Use the params field to customize
* the container. The container is verified to work correctly on
* ubuntu 16.04 operating system. See more at
* [containers
* quickstart](https:
* //cloud.google.com/vision/automl/docs/containers-gcs-quickstart)
* * core_ml - Used for iOS mobile devices.
*
*
* string model_format = 4;
*
* @param value The bytes for modelFormat to set.
* @return This builder for chaining.
*/
public Builder setModelFormatBytes(com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
modelFormat_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
private com.google.protobuf.MapField params_;
private com.google.protobuf.MapField internalGetParams() {
if (params_ == null) {
return com.google.protobuf.MapField.emptyMapField(ParamsDefaultEntryHolder.defaultEntry);
}
return params_;
}
private com.google.protobuf.MapField
internalGetMutableParams() {
if (params_ == null) {
params_ = com.google.protobuf.MapField.newMapField(ParamsDefaultEntryHolder.defaultEntry);
}
if (!params_.isMutable()) {
params_ = params_.copy();
}
bitField0_ |= 0x00000008;
onChanged();
return params_;
}
public int getParamsCount() {
return internalGetParams().getMap().size();
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
@java.lang.Override
public boolean containsParams(java.lang.String key) {
if (key == null) {
throw new NullPointerException("map key");
}
return internalGetParams().getMap().containsKey(key);
}
/** Use {@link #getParamsMap()} instead. */
@java.lang.Override
@java.lang.Deprecated
public java.util.Map getParams() {
return getParamsMap();
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
@java.lang.Override
public java.util.Map getParamsMap() {
return internalGetParams().getMap();
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
@java.lang.Override
public /* nullable */ java.lang.String getParamsOrDefault(
java.lang.String key,
/* nullable */
java.lang.String defaultValue) {
if (key == null) {
throw new NullPointerException("map key");
}
java.util.Map map = internalGetParams().getMap();
return map.containsKey(key) ? map.get(key) : defaultValue;
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
@java.lang.Override
public java.lang.String getParamsOrThrow(java.lang.String key) {
if (key == null) {
throw new NullPointerException("map key");
}
java.util.Map map = internalGetParams().getMap();
if (!map.containsKey(key)) {
throw new java.lang.IllegalArgumentException();
}
return map.get(key);
}
public Builder clearParams() {
bitField0_ = (bitField0_ & ~0x00000008);
internalGetMutableParams().getMutableMap().clear();
return this;
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
public Builder removeParams(java.lang.String key) {
if (key == null) {
throw new NullPointerException("map key");
}
internalGetMutableParams().getMutableMap().remove(key);
return this;
}
/** Use alternate mutation accessors instead. */
@java.lang.Deprecated
public java.util.Map getMutableParams() {
bitField0_ |= 0x00000008;
return internalGetMutableParams().getMutableMap();
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
public Builder putParams(java.lang.String key, java.lang.String value) {
if (key == null) {
throw new NullPointerException("map key");
}
if (value == null) {
throw new NullPointerException("map value");
}
internalGetMutableParams().getMutableMap().put(key, value);
bitField0_ |= 0x00000008;
return this;
}
/**
*
*
*
* Additional model-type and format specific parameters describing the
* requirements for the to be exported model files, any string must be up to
* 25000 characters long.
* * For `docker` format:
* `cpu_architecture` - (string) "x86_64" (default).
* `gpu_architecture` - (string) "none" (default), "nvidia".
*
*
* map<string, string> params = 2;
*/
public Builder putAllParams(java.util.Map values) {
internalGetMutableParams().getMutableMap().putAll(values);
bitField0_ |= 0x00000008;
return this;
}
@java.lang.Override
public final Builder setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:google.cloud.automl.v1beta1.ModelExportOutputConfig)
}
// @@protoc_insertion_point(class_scope:google.cloud.automl.v1beta1.ModelExportOutputConfig)
private static final com.google.cloud.automl.v1beta1.ModelExportOutputConfig DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new com.google.cloud.automl.v1beta1.ModelExportOutputConfig();
}
public static com.google.cloud.automl.v1beta1.ModelExportOutputConfig getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public ModelExportOutputConfig parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.cloud.automl.v1beta1.ModelExportOutputConfig getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}