id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
google_protobuf/comgooglecloudvertex_389_0.txt | Sample code: | |
google_protobuf/tabular_146_0.txt | The AI Platform Python client library works as a client/server model. | |
google_protobuf/tabular_245_0.txt |
tf27_gpu_predictions = get_predictions(
tf27_gpu_endpoint, f"{LOCAL_DIRECTORY_FULL}/requests/requests_100_512.jsonl"
) | |
google_protobuf/comgooglecloudvertex_456_0.txt | ### rawPredict(String endpoint, HttpBody httpBody) | |
google_protobuf/PredictionServiceCli_9_0.txt | ## Class PredictionServiceClient | |
google_protobuf/604925_97_0.txt |   | |
google_protobuf/comgooglecloudvertex_6_0.txt | * [ Access and resources management ](https://cloud.google.com/docs/access-resources)
* [ Cloud SDK, languages, frameworks, and tools ](https://cloud.google.com/docs/devtools)
* [ Costs and usage management ](https://cloud.google.com/docs/costs-usage)
* [ Infrastructure as code ](https://cloud.google.com/docs/iac)
... | |
google_protobuf/comgooglecloudvertex_282_0.txt |
**Parameter**
---
**Name** | **Description**
` request ` | ` [ ExplainRequest ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.ExplainRequest) ` | |
google_protobuf/604925_171_0.txt | [ Reply ]() | |
google_protobuf/tabular_69_0.txt | The final step for your Cloud Storage bucket is to validate access to your Cloud Storage bucket by examining its contents: | |
google_protobuf/tabular_200_0.txt | (optional) Compare performance of deployed models
To access private endpoints, the VM used to send requests must be deployed in the same network where you setup VPC peering. Because of this, you can't send requests to your models that are deployed with private endpoints from Colab. | |
google_protobuf/604925_133_0.txt | Post Options | |
google_protobuf/tabular_48_0.txt | In the Cloud Console, go to the Create service account key page. | |
google_protobuf/google_protobuf_3_2.txt | re is no separate notion of presence: a “not present” repeated
extension is an empty list.
` HasField ` ( _field_name_ ) ¶
` IsInitialized ` ( _errors=None_ ) ¶
Checks if all required fields of a message are set.
Parameters :
**errors** – A list which, if provided, will be populated with the... | |
google_protobuf/google_protobuf_23_1.txt | s was a state change.
` UnknownFields ` ( ) ¶
` WhichOneof ` ( _oneof_name_ ) ¶
Returns the name of the currently set field inside a oneof, or None.
_property_ ` end ` ¶
_property_ ` options ` ¶
_property_ ` start ` ¶
` FIELD_FIELD_NUMBER ` _= 2_ ¶
` FindInitializationErr... | |
google_protobuf/tabular_109_0.txt | Check the model signature to see which fields prediction request should have. | |
google_protobuf/comgooglecloudvertex_93_0.txt | Callable method variants take no parameters and return an immutable API
callable object, which can be used to initiate calls to the service. | |
google_protobuf/comgooglecloudvertex_291_0.txt |
**Parameters**
---
**Name** | **Description**
` endpoint ` | ` [ String
](https://docs.oracle.com/javase/8/docs/api/java/lang/String.html) ` | |
google_protobuf/PredictionServiceCli_180_0.txt | If
[deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id]
is specified, the corresponding DeployModel must have
[explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
populated. If
[deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id]
is not sp... | |
google_protobuf/tabular_204_0.txt |
from benchmark import benchmark | |
google_protobuf/PredictionServiceCli_127_0.txt | Perform an online prediction with an arbitrary HTTP payload. | |
google_protobuf/604925_108_0.txt | Post Options | |
google_protobuf/comgooglecloudvertex_325_0.txt | **Returns**
---
**Type** | **Description**
` [ GenerateContentResponse ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.GenerateContentResponse) ` | | |
google_protobuf/tabular_140_0.txt |
!gsutil rm -r $BUCKET_URI/* | |
google_protobuf/604925_87_0.txt | [
](https://www.googlecloudcommunity.com/gc/forums/v5/forumtopicpage.kudosbuttonv2.kudoentity:kudoentity/kudosable-
gid/600835?t:ac=board-id/cloud-ai-ml/message-
id/2198&t:cp=kudos/contributions/tapletcontributionspage "Click here to give
likes to this post.") | |
google_protobuf/comgooglecloudvertex_349_0.txt | Sample code: | |
google_protobuf/comgooglecloudvertex_37_0.txt | * [ XraiAttribution ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.XraiAttribution)
* [ XraiAttribution.Builder ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.XraiAttribution.Builder)
* Enums | |
google_protobuf/PredictionServiceCli_27_0.txt |
Please refer to the GitHub repository's samples for more quickstart code
snippets. | |
google_protobuf/comgooglecloudvertex_445_0.txt | ### rawPredict(RawPredictRequest request) | |
google_protobuf/comgooglecloudvertex_130_0.txt | * explainCallable() | |
google_protobuf/comgooglecloudvertex_15_0.txt | [  ](/) | |
google_protobuf/comgooglecloudvertex_518_0.txt | ### streamGenerateContentCallable() | |
google_protobuf/604925_76_0.txt | * I call another Vertex model endpoint (with a simpler model inside a Docker image)
* I use a HTTP REST request (with curl) to get the prediction from the initial model (instead of Java code) | |
google_protobuf/tabular_28_0.txt | Select or create a Google Cloud project. When you first create an account, you get a $300 credit towards your compute and storage costs. | |
google_protobuf/tabular_154_0.txt | For the best performance, use a Vertex AI Prediction private endpoint. | |
google_protobuf/comgooglecloudvertex_339_0.txt | **Returns**
---
**Type** | **Description**
` com.google.iam.v1.Policy ` | | |
google_protobuf/comgooglecloudvertex_528_0.txt | // This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://clo... | |
google_protobuf/tabular_103_0.txt | Train the model. The expected loss is about 0.35. | |
google_protobuf/google_protobuf_23_22.txt | ndex.html)
* Previous: [ google.protobuf.descriptor_database ](descriptor_database.html "previous chapter")
* Next: [ google.protobuf.descriptor_pool ](descriptor_pool.html "next chapter")
### This Page
* [ Show Source ](../../_sources/google/protobuf/descriptor_pb2.rst.txt)
©2008, Google LLC. | Powered b... | |
google_protobuf/604925_6_0.txt | * [ Google Cloud Home ](https://www.googlecloudcommunity.com/gc/Google-Cloud/ct-p/google-cloud) | |
google_protobuf/google_protobuf_18_2.txt | – If set, a colon will be added after the field name even if the field is a proto message.
` google.protobuf.text_format. ` ` PrintField ` ( _field_ , _value_ , _out_ ,
_indent=0_ , _as_utf8=False_ , _as_one_line=False_ ,
_use_short_repeated_primitives=False_ , _pointy_brackets=False_ ,
_use_index_order=False_ , _f... | |
google_protobuf/comgooglecloudvertex_459_0.txt | The response includes the following HTTP headers: | |
google_protobuf/comgooglecloudvertex_35_0.txt | * [ MutateDeployedModelOperationMetadata ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.MutateDeployedModelOperationMetadata)
* [ MutateDeployedModelOperationMetadata.Builder ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.MutateDeployedModelOperati... | |
google_protobuf/tabular_169_0.txt | Upload model to Vertex AI Prediction
Learn more about model_service.upload_model. | |
google_protobuf/comgooglecloudvertex_360_0.txt | ### getSettings() | |
google_protobuf/comgooglecloudvertex_288_0.txt | If deployed_model_id is specified, the corresponding DeployModel must have
explanation_spec populated. If deployed_model_id is not specified, all
DeployedModels must have explanation_spec populated. | |
google_protobuf/604925_191_0.txt | [
 angel_perez 
](/gc/user/viewprofilepage/user-id/505719) | |
google_protobuf/comgooglecloudvertex_560_0.txt | Last updated 2024-05-01 UTC. | |
google_protobuf/tabular_203_0.txt |
!curl https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/benchmark.py -o benchmark.py | |
google_protobuf/comgooglecloudvertex_276_0.txt | ### explain(ExplainRequest request) | |
google_protobuf/comgooglecloudvertex_351_0.txt |
**Parameter**
---
**Name** | **Description**
` request ` | ` com.google.cloud.location.GetLocationRequest ` | |
google_protobuf/comgooglecloudvertex_277_0.txt | public final ExplainResponse explain(ExplainRequest request) | |
google_protobuf/comgooglecloudvertex_250_0.txt | Sample code: | |
google_protobuf/PredictionServiceCli_42_0.txt | ` [ ExplainResponse ](https://github.com/googleapis/java-/proto-google-cloud-
aiplatform-v1/apidocs/com/google/cloud/aiplatform/v1/ExplainResponse.html?is-
external=true "class or interface in com.google.cloud.aiplatform.v1") ` | ` [
explain
](../../../../../com/google/cloud/aiplatform/v1/PredictionServiceClient.html#... | |
google_protobuf/comgooglecloudvertex_88_0.txt | * streamRawPredictCallable() | |
google_protobuf/google_protobuf_3_6.txt | seFromString ` ( _serialized_ ) ¶
Parse serialized protocol buffer data into this message.
Like ` MergeFromString() ` , except we clear the object first.
Raises :
**message.DecodeError if the input cannot be parsed.** –
_static_ ` RegisterExtension ` ( _extension_handle_ ) ¶
` SerializePa... | |
google_protobuf/604925_79_0.txt | Any idea how to debug/fix this? | |
google_protobuf/604925_85_0.txt | [ Jump to Solution ](/gc/AI-ML/Vertex-AI-Getting-a-GRPC-Exception-when-
sending-a-prediction/m-p/604925#M2198) | |
google_protobuf/comgooglecloudvertex_526_0.txt | Perform a streaming online prediction with an arbitrary HTTP payload. | |
google_protobuf/google_protobuf_22_0.txt | # google.protobuf.struct_pb2 ¶
Generated protocol buffer code.
_class_ ` google.protobuf.struct_pb2. ` ` ListValue ` ( _**kwargs_ ) ¶
` ByteSize ` ( ) ¶
` Clear ` ( ) ¶
` ClearExtension ` ( _extension_handle_ ) ¶
Clears the contents of a given extension.
Parameters :
**e... | |
google_protobuf/PredictionServiceCli_137_0.txt | ` com.google.api.gax.rpc.ApiException ` \- if the remote call fails
* #### rawPredict | |
google_protobuf/604925_127_0.txt | ](http://twitter.com/share?text=Vertex AI: Getting a GRPC Exception when
sending a prediction request in
Java&url=https://www.googlecloudcommunity.com/gc/AI-ML/Vertex-AI-Getting-a-
GRPC-Exception-when-sending-a-prediction/m-p/604925) | |
google_protobuf/comgooglecloudvertex_208_0.txt | public static final PredictionServiceClient create(PredictionServiceSettings settings) | |
google_protobuf/PredictionServiceCli_91_0.txt |
try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
List<Value> instances = new ArrayList<>();
Value parameters = Value.newBuilder().build();
PredictResponse response = predictionServiceClient.predi... | |
google_protobuf/tabular_250_0.txt | Cleanup
After you are done, it's safe to remove the endpoints you created and the model you deployed. | |
google_protobuf/comgooglecloudvertex_108_0.txt | * streamDirectRawPredictCallable() | |
google_protobuf/comgooglecloudvertex_361_0.txt | public final PredictionServiceSettings getSettings() | |
google_protobuf/604925_129_0.txt | https://www.googlecloudcommunity.com/html/@BA4B8F5B12739C28A35AEDB252AA7576/assets/google-
copy-url-icon.png) Copy URL | |
google_protobuf/comgooglecloudvertex_33_0.txt | * [ Examples.ExampleGcsSource ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.Examples.ExampleGcsSource)
* [ Examples.ExampleGcsSource.Builder ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.Examples.ExampleGcsSource.Builder)
* [ ExamplesOverride ](... | |
google_protobuf/PredictionServiceCli_51_0.txt | Perform an online prediction. | |
google_protobuf/comgooglecloudvertex_4_0.txt | [ Cross-product tools ](https://cloud.google.com/docs/cross-product-overviews) | |
google_protobuf/tabular_183_0.txt | List all models. | |
google_protobuf/PredictionServiceCli_131_0.txt |
try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
String endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString();
HttpBody httpBody = HttpBody.newBuilder().build();
HttpBody response = predictionServiceClient.rawPredict(endpoint, httpBody);
} | |
google_protobuf/tabular_118_0.txt |
!saved_model_cli show --dir $estimator_path --all | |
google_protobuf/604925_80_0.txt | Solved! [ Go to Solution. ](/gc/AI-ML/Vertex-AI-Getting-a-GRPC-Exception-when-
sending-a-prediction/m-p/604925#M2198) | |
google_protobuf/tabular_198_0.txt |
tf_opt_lossy_gpu_deployed_model_dict = {
"model": tf_opt_lossy_gpu_model,
"display_name": "Criteo Kaggle optimized TensorFlow runtime GPU model with lossy optimizations",
"dedicated_resources": {
"min_replica_count": 1,
"max_replica_count": 1,
"machine_spec": {
"machine_type": DEPLOY_COMPUTE,
"accelerator_type": DEPLO... | |
google_protobuf/tabular_1_0.txt | Colab logo Run in Colab GitHub logo View on GitHub Vertex AI logo Open in Vertex AI Workbench
Training a tabular Criteo model and deploying it to Vertex AI Predictions using the optimized TensorFlow runtime
Overview
In this sample you learn how to train a tabular model using TensorFlow Keras or Estimator API using Crit... | |
google_protobuf/PredictionServiceCli_67_0.txt | Constructs an instance of PredictionServiceClient, using the given settings.
This is protected so that it is easy to make a subclass, but otherwise, the
static factory methods should be preferred. | |
google_protobuf/tabular_178_0.txt | allow_precompilation - turns on model pre-compilation for better performance. Note that model precompilation happens when the first request with the new batch size arrives, and the response for that request is sent after precompilation is complete. To mitigate this, specify a warmup file (see the section earlier in thi... | |
google_protobuf/PredictionServiceCli_160_0.txt | ` endpoint ` \- Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
` instances ` \- Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it support... | |
google_protobuf/comgooglecloudvertex_167_0.txt | Callable method variants take no parameters and return an immutable API
callable object, which can be used to initiate calls to the service. | |
google_protobuf/comgooglecloudvertex_403_0.txt | **Returns**
---
**Type** | **Description**
` [ PredictResponse ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.PredictResponse) ` | | |
google_protobuf/PredictionServiceCli_54_0.txt | ` com.google.api.HttpBody ` | ` [ rawPredict
](../../../../../com/google/cloud/aiplatform/v1/PredictionServiceClient.html#rawPredict-
com.google.cloud.aiplatform.v1.EndpointName-com.google.api.HttpBody-) ( [
EndpointName ](https://github.com/googleapis/java-/proto-google-cloud-
aiplatform-v1/apidocs/com/google/cloud/a... | |
google_protobuf/tabular_74_0.txt | logging = tf.get_logger()
logging.propagate = False
logging.setLevel("INFO") | |
google_protobuf/604925_9_0.txt | * [ AI/ML ](/gc/AI-ML/bd-p/cloud-ai-ml) | |
google_protobuf/comgooglecloudvertex_50_0.txt | * [ Access and resources management ](/docs/access-resources)
* [ Cloud SDK, languages, frameworks, and tools ](/docs/devtools)
* [ Costs and usage management ](/docs/costs-usage)
* [ Infrastructure as code ](/docs/iac)
* [ Migration ](/docs/migration) | |
google_protobuf/604925_95_0.txt | https://www.googlecloudcommunity.com/html/@17707BECA4EAD3896FBAF17C64C2ABD8/assets/gcc-linkedin.svg) LinkedIn | |
google_protobuf/comgooglecloudvertex_260_0.txt |
**Returns**
---
**Type** | **Description**
` [ UnaryCallable
](https://cloud.google.com/java/docs/reference/gax/latest/com.google.api.gax.rpc.UnaryCallable.html)
< [ DirectRawPredictRequest ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.DirectRawPredictRequest) , [
DirectRawPredict... | |
google_protobuf/comgooglecloudvertex_125_0.txt | * explain(ExplainRequest request) | |
google_protobuf/comgooglecloudvertex_419_0.txt | ` instances ` | ` [ List
](https://docs.oracle.com/javase/8/docs/api/java/util/List.html) < [ Value
](https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.Value.html)
> ` | |
google_protobuf/604925_152_0.txt | ](https://www.linkedin.com/shareArticle?mini=true&url=https://www.googlecloudcommunity.com/gc/AI-
ML/Vertex-AI-Getting-a-GRPC-Exception-when-sending-a-
prediction/m-p/604925&title=Vertex AI: Getting a GRPC Exception when sending a
prediction request in Java) [ | |
google_protobuf/comgooglecloudvertex_142_0.txt | * streamGenerateContentCallable() | |
google_protobuf/google_protobuf_19_2.txt | e.html)
* [ google.protobuf.text_encoding ](text_encoding.html)
* [ google.protobuf.text_format ](text_format.html)
* [ google.protobuf.timestamp_pb2 ](timestamp_pb2.html)
* [ google.protobuf.type_pb2 ](type_pb2.html)
* [ google.protobuf.unknown_fields ](unknown_fields.html)
* [ google.protobuf.wrappers_pb2... | |
google_protobuf/comgooglecloudvertex_68_0.txt | "Flattened" method variants have converted the fields of the request object
into function parameters to enable multiple ways to call the same method. | |
google_protobuf/PredictionServiceCli_196_0.txt | public void shutdownNow() | |
google_protobuf/PredictionServiceCli_3_0.txt | * [ Prev Class ](../../../../../com/google/cloud/aiplatform/v1/PipelineServiceSettings.Builder.html "class in com.google.cloud.aiplatform.v1")
* [ Next Class ](../../../../../com/google/cloud/aiplatform/v1/PredictionServiceSettings.html "class in com.google.cloud.aiplatform.v1") | |
google_protobuf/comgooglecloudvertex_428_0.txt | // This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://clo... | |
google_protobuf/tabular_173_0.txt | Please note that gRPC support in Vertex AI Prediction is still experimental. |
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