id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
value |
|---|---|---|
google_protobuf/comgooglecloudvertex_561_0.txt | [{ "type": "thumb-down", "id": "hardToUnderstand", "label":"Hard to
understand" },{ "type": "thumb-down", "id":
"incorrectInformationOrSampleCode", "label":"Incorrect information or sample
code" },{ "type": "thumb-down", "id": "missingTheInformationSamplesINeed",
"label":"Missing the information/samples I need" },{ "ty... | |
google_protobuf/604925_99_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_273_0.txt | ` deployedModelId ` | ` [ String
](https://docs.oracle.com/javase/8/docs/api/java/lang/String.html) ` | |
google_protobuf/604925_12_0.txt | * [ Apigee ](/gc/Apigee/bd-p/cloud-apigee) | |
google_protobuf/comgooglecloudvertex_136_0.txt | * generateContent(String model, List<Content> contents) | |
google_protobuf/PredictionServiceCli_148_0.txt | Perform an online prediction with an arbitrary HTTP payload. | |
google_protobuf/comgooglecloudvertex_551_0.txt | ### testIamPermissionsCallable() | |
google_protobuf/tabular_223_0.txt | grpc_metadata = []
grpc_metadata.append(("grpc-destination", grpc_destinaion))
grpc_channel = grpc.insecure_channel(grpc_uri)
grpc_stub = prediction_service_pb2_grpc.PredictionServiceStub(grpc_channel) | |
google_protobuf/PredictionServiceCli_70_0.txt | @BetaApi(value="A restructuring of stub classes is planned, so this may break in the future")
protected PredictionServiceClient([PredictionServiceStub](../../../../../com/google/cloud/aiplatform/v1/stub/PredictionServiceStub.html "class in com.google.cloud.aiplatform.v1.stub") stub) | |
google_protobuf/PredictionServiceCli_64_0.txt | * * ### Constructor Detail | |
google_protobuf/tabular_105_0.txt | Validate the model. The expected loss is about 0.45. | |
google_protobuf/comgooglecloudvertex_450_0.txt | * ` X-Vertex-AI-Deployed-Model-Id ` : ID of the Endpoint's DeployedModel that served this prediction. | |
google_protobuf/comgooglecloudvertex_362_0.txt | **Returns**
---
**Type** | **Description**
` [ PredictionServiceSettings ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.PredictionServiceSettings) ` | | |
google_protobuf/comgooglecloudvertex_243_0.txt | Perform an unary online prediction request to a gRPC model server for Vertex
first-party products and frameworks. | |
google_protobuf/comgooglecloudvertex_90_0.txt | Perform an unary online prediction request to a gRPC model server for Vertex
first-party products and frameworks. | |
google_protobuf/tabular_191_0.txt | Deploy models to endpoints
Learn more about enpoint_service.deploy_model. | |
google_protobuf/PredictionServiceCli_138_0.txt | public final com.google.api.HttpBody rawPredict([RawPredictRequest](https://github.com/googleapis/java-/proto-google-cloud-aiplatform-v1/apidocs/com/google/cloud/aiplatform/v1/RawPredictRequest.html?is-external=true "class or interface in com.google.cloud.aiplatform.v1") request) | |
google_protobuf/comgooglecloudvertex_290_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/google_protobuf_3_5.txt | :
Whether the extension is present for this message.
Return type :
[ bool ](https://docs.python.org/3/library/functions.html#bool "\(in Python
v3.10\)")
Raises :
[ **KeyError** ](https://docs.python.org/3/library/exceptions.html#KeyError
"\(in Python v3.10\)") – if the extension is repeated. Si... | |
google_protobuf/comgooglecloudvertex_258_0.txt | Sample code: | |
google_protobuf/tabular_176_0.txt | For deploying a model using Vertex AI Prediction optimized TensorFlow runtime, use the us-docker.pkg.dev/vertex-ai-restricted/prediction/tf_opt-gpu.nightly:latest container. | |
google_protobuf/comgooglecloudvertex_313_0.txt | The request object containing all of the parameters for the API call. | |
google_protobuf/604925_48_0.txt | [ ](/gc/AI-ML/Vertex-AI-Getting-a-GRPC-Exception-when-sending-a-
prediction/m-p/600835#M2093) | |
google_protobuf/comgooglecloudvertex_38_0.txt | * [ AcceleratorType ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.AcceleratorType)
* [ Candidate.FinishReason ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.Candidate.FinishReason)
* [ DeployedModel.PredictionResourcesCase ](/java/docs/reference/... | |
google_protobuf/604925_73_0.txt | I got a _io.grpc.StatusRuntimeException: INTERNAL: RST_STREAM closed stream.
HTTP/2 error code: INTERNAL_ERROR._ | |
google_protobuf/PredictionServiceCli_43_0.txt | Perform an online explanation. | |
google_protobuf/604925_122_0.txt |  | |
google_protobuf/comgooglecloudvertex_241_0.txt | ### directPredictCallable() | |
google_protobuf/604925_26_0.txt | * [ Cloud Learning Logs ](/gc/Cloud-Learning-Logs/bd-p/cloud-learning-logs) | |
google_protobuf/604925_119_0.txt | Posted on \--/--/---- --:-- AM | |
google_protobuf/604925_163_0.txt | Reply posted on \--/--/---- --:-- AM | |
google_protobuf/tabular_196_0.txt |
tf_opt_gpu_deployed_model_dict = {
"model": tf_opt_gpu_model,
"display_name": "Criteo Kaggle optimized TensorFlow runtime GPU model",
"dedicated_resources": {
"min_replica_count": 1,
"max_replica_count": 1,
"machine_spec": {
"machine_type": DEPLOY_COMPUTE,
"accelerator_type": DEPLOY_GPU,
"accelerator_count": 1,
},
},
... | |
google_protobuf/tabular_227_0.txt |
tf27_cpu_results = benchmark_grpc_private_endpoint(
tf27_cpu_endpoint, [10, 20, 30, 40, 50, 55]
)
tf27_cpu_results | |
google_protobuf/comgooglecloudvertex_294_0.txt | Required. The instances that are the input to the explanation call. A
DeployedModel may have an upper limit on the number of instances it supports
per request, and when it is exceeded the explanation call errors in case of
AutoML Models, or, in case of customer created Models, the behaviour is as
documented by that Mod... | |
google_protobuf/google_protobuf_7_7.txt | (../../index.html)
* [ google.protobuf ](../protobuf.html)
* [ google.protobuf.any_pb2 ](any_pb2.html)
* google.protobuf.descriptor
* [ google.protobuf.descriptor_database ](descriptor_database.html)
* [ google.protobuf.descriptor_pb2 ](descriptor_pb2.html)
* [ google.protobuf.descriptor_pool ](descriptor... | |
google_protobuf/comgooglecloudvertex_469_0.txt | You can specify the schema for each instance in the
predict_schemata.instance_schema_uri field when you create a Model . This
schema applies when you deploy the ` Model ` as a ` DeployedModel ` to an
Endpoint and use the ` RawPredict ` method. | |
google_protobuf/comgooglecloudvertex_147_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/PredictionServiceCli_121_0.txt | ` endpoint ` \- Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
` httpBody ` \- The prediction input. Supports HTTP headers and arbitrary data payload. | |
google_protobuf/tabular_17_0.txt | Open this notebook in the Jupyter Notebook Dashboard. | |
google_protobuf/tabular_193_0.txt | tf27_cpu_deployed_model = endpoint_service_client.deploy_model(
endpoint=tf27_cpu_endpoint, deployed_model=tf27_cpu_deployed_model_dict
).result()
tf27_cpu_deployed_model | |
google_protobuf/comgooglecloudvertex_306_0.txt |
**Returns**
---
**Type** | **Description**
` [ UnaryCallable
](https://cloud.google.com/java/docs/reference/gax/latest/com.google.api.gax.rpc.UnaryCallable.html)
< [ ExplainRequest ](/java/docs/reference/google-cloud-
vertexai/latest/com.google.cloud.vertexai.api.ExplainRequest) , [
ExplainResponse ](/java/docs/refer... | |
google_protobuf/604925_82_0.txt | 1 2 1,231 | |
google_protobuf/604925_196_0.txt | * © 2024 Google. All rights reserved.
* [ Privacy Policy ](https://policies.google.com/privacy)
* [ Terms of Service ](https://policies.google.com/terms)
* [ Community Guidelines ](/gc/custom/page/page-id/GCC-Community-Guidelines) | |
google_protobuf/comgooglecloudvertex_305_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/comgooglecloudvertex_516_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/comgooglecloudvertex_508_0.txt | Perform a streaming online prediction request to a gRPC model server for
Vertex first-party products and frameworks. | |
google_protobuf/comgooglecloudvertex_117_0.txt | StreamingRawPredict | |
google_protobuf/comgooglecloudvertex_203_0.txt | ### create() | |
google_protobuf/comgooglecloudvertex_418_0.txt | Required. The name of the Endpoint requested to serve the prediction. Format:
` projects/{project}/locations/{location}/endpoints/{endpoint} ` | |
google_protobuf/comgooglecloudvertex_443_0.txt | You can specify the schema for each instance in the
predict_schemata.instance_schema_uri field when you create a Model . This
schema applies when you deploy the ` Model ` as a ` DeployedModel ` to an
Endpoint and use the ` RawPredict ` method. | |
google_protobuf/tabular_21_0.txt | # Vertex AI Workbench Notebook requires dependencies to be installed with '--user'
USER_FLAG = ""
if IS_GOOGLE_CLOUD_NOTEBOOK:
USER_FLAG = "--user" | |
google_protobuf/comgooglecloudvertex_132_0.txt | Generate content with multimodal inputs. | |
google_protobuf/comgooglecloudvertex_183_0.txt |
To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and
receiving requests over the wire: | |
google_protobuf/comgooglecloudvertex_271_0.txt | ` parameters ` | ` [ Value
](https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.Value.html)
` | |
google_protobuf/google_protobuf_23_0.txt | # google.protobuf.descriptor_pb2 ¶
Generated protocol buffer code.
_class_ ` google.protobuf.descriptor_pb2. ` ` DescriptorProto ` ( _**kwargs_
) ¶
` ByteSize ` ( ) ¶
` Clear ` ( ) ¶
` ClearExtension ` ( _extension_handle_ ) ¶
Clears the contents of a given extension.
Parameters... | |
google_protobuf/comgooglecloudvertex_439_0.txt | Required. The name of the Endpoint requested to serve the prediction. Format:
` projects/{project}/locations/{location}/endpoints/{endpoint} ` | |
google_protobuf/comgooglecloudvertex_172_0.txt | Request object method variants only take one parameter, a request object,
which must be constructed before the call. | |
google_protobuf/comgooglecloudvertex_31_0.txt | * [ AcceleratorTypeProto ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.AcceleratorTypeProto)
* [ Attribution ](/java/docs/reference/google-cloud-vertexai/latest/com.google.cloud.vertexai.api.Attribution)
* [ Attribution.Builder ](/java/docs/reference/google-cloud-vertexai/latest/c... | |
google_protobuf/tabular_135_0.txt |
def build_grpc_request(
row_dict, model_name="default", signature_name="serving_default"
):
"""Generate gRPC inference request with payload.""" | |
google_protobuf/comgooglecloudvertex_501_0.txt |
**Returns**
---
**Type** | **Description**
` [ UnaryCallable
](https://cloud.google.com/java/docs/reference/gax/latest/com.google.api.gax.rpc.UnaryCallable.html)
< com.google.iam.v1.SetIamPolicyRequest , com.google.iam.v1.Policy > ` | | |
google_protobuf/comgooglecloudvertex_52_0.txt | * [ Home ](https://cloud.google.com/)
* [ Java ](https://cloud.google.com/java)
* [ Documentation ](https://cloud.google.com/java/docs)
* [ Reference ](https://cloud.google.com/java/docs/reference) | |
google_protobuf/comgooglecloudvertex_242_0.txt | public final UnaryCallable<DirectPredictRequest,DirectPredictResponse> directPredictCallable() | |
google_protobuf/comgooglecloudvertex_499_0.txt | Sample code: | |
google_protobuf/604925_193_0.txt | [
monch1962 
](/gc/user/viewprofilepage/user-id/515366) | |
google_protobuf/tabular_174_0.txt |
tf27_cpu_model_dict = {
"display_name": "Criteo Kaggle TF2.7 CPU model",
"artifact_uri": BUCKET_URI,
"container_spec": {
"image_uri": "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-7:latest",
"args": [
"--port=8500",
"--rest_api_port=8080",
"--model_name=default",
"--model_base_path=$(AIP_STORAGE_URI)",
],
"ports":... | |
google_protobuf/tabular_150_0.txt | client_options = {"api_endpoint": API_ENDPOINT}
model_service_client = aip.ModelServiceClient(client_options=client_options)
endpoint_service_client = aip.EndpointServiceClient(client_options=client_options) | |
google_protobuf/comgooglecloudvertex_80_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/604925_94_0.txt |  | |
google_protobuf/comgooglecloudvertex_101_0.txt | StreamDirectPredict | |
google_protobuf/PredictionServiceCli_141_0.txt | * `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
* `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction. | |
google_protobuf/604925_147_0.txt | Posted on \--/--/---- --:-- AM | |
google_protobuf/PredictionServiceCli_155_0.txt | Perform an online explanation. | |
google_protobuf/google_protobuf_21_0.txt | # google.protobuf.type_pb2 ¶
Generated protocol buffer code.
_class_ ` google.protobuf.type_pb2. ` ` Enum ` ( _**kwargs_ ) ¶
` ByteSize ` ( ) ¶
` Clear ` ( ) ¶
` ClearExtension ` ( _extension_handle_ ) ¶
Clears the contents of a given extension.
Parameters :
**extension_... | |
google_protobuf/tabular_238_0.txt | (Optional) Compare performance of deployed models using MLPerf Inference loadgen
MLPerf Inference is a benchmark suite for measuring how fast systems can run models in a variety of deployment scenarios. MLPerf is now an industry standard way of measuring model performance. You can follow instructions at https://github.... | |
google_protobuf/tabular_99_0.txt |
def create_keras_model_sequential():
feature_columns = create_feature_columns() | |
google_protobuf/comgooglecloudvertex_110_0.txt | Perform a streaming online prediction request for Vertex first-party products
and frameworks. | |
google_protobuf/604925_93_0.txt | https://www.googlecloudcommunity.com/html/@7EEB446AFD303232B17DB09B0B668FB1/assets/sharelog.png) Share this topic | |
google_protobuf/tabular_38_0.txt | PROJECT_ID = "" | |
google_protobuf/comgooglecloudvertex_111_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/PredictionServiceCli_83_0.txt | * #### getSettings | |
google_protobuf/PredictionServiceCli_186_0.txt | ` [ close ](https://docs.oracle.com/javase/8/docs/api/java/lang/AutoCloseable.html?is-external=true#close-- "class or interface in java.lang") ` in interface ` [ AutoCloseable ](https://docs.oracle.com/javase/8/docs/api/java/lang/AutoCloseable.html?is-external=true "class or interface in java.lang") `
* #### shutdown | |
google_protobuf/comgooglecloudvertex_176_0.txt | See the individual methods for example code. | |
google_protobuf/PredictionServiceCli_74_0.txt | Constructs an instance of PredictionServiceClient with default settings. | |
google_protobuf/comgooglecloudvertex_201_0.txt | [ Object.wait(long,int)
](https://docs.oracle.com/javase/8/docs/api/java/lang/Object.html#wait-long-
int-) | |
google_protobuf/comgooglecloudvertex_531_0.txt | public final BidiStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> streamingPredictCallable() | |
google_protobuf/google_protobuf_3_3.txt | ) ¶
` SerializeToString ` ( _**kwargs_ ) ¶
` SetInParent ` ( ) ¶
Sets the _cached_byte_size_dirty bit to true, and propagates this to our
listener iff this was a state change.
` UnknownFields ` ( ) ¶
` VALUE_FIELD_NUMBER ` _= 1_ ¶
` WhichOneof ` ( _oneof_name_ ) ¶
Ret... | |
google_protobuf/google_protobuf_23_3.txt | ialized.
Returns :
A list of strings. Each string is a path to an uninitialized field from the
top-level message, e.g. “foo.bar[5].baz”.
_static_ ` FromString ` ( _s_ ) ¶
` HasExtension ` ( _extension_handle_ ) ¶
Checks if a certain extension is present for this message.
Extensions are retr... | |
google_protobuf/comgooglecloudvertex_329_0.txt | Sample code: | |
google_protobuf/comgooglecloudvertex_237_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/comgooglecloudvertex_521_0.txt | Sample code: | |
google_protobuf/PredictionServiceCli_82_0.txt | Constructs an instance of PredictionServiceClient, using the given stub for
making calls. This is for advanced usage - prefer using
create(PredictionServiceSettings). | |
google_protobuf/google_protobuf_1_0.txt | # google.protobuf.symbol_database ¶
A database of Python protocol buffer generated symbols.
SymbolDatabase is the MessageFactory for messages generated at compile time,
and makes it easy to create new instances of a registered type, given only the
type’s protocol buffer symbol name.
Example usage:
d... | |
google_protobuf/PredictionServiceCli_189_0.txt | ` shutdown ` in interface ` com.google.api.gax.core.BackgroundResource `
* #### isShutdown | |
google_protobuf/comgooglecloudvertex_354_0.txt | ### getLocationCallable() | |
google_protobuf/PredictionServiceCli_25_0.txt |
To customize the endpoint: | |
google_protobuf/comgooglecloudvertex_13_0.txt | [ Overview ](https://cloud.google.com/java/docs) [ Guides
](https://cloud.google.com/java/docs/setup) [ Reference
](https://cloud.google.com/java/docs/reference) [ Samples
](https://cloud.google.com/docs/samples/?language=java) | |
google_protobuf/comgooglecloudvertex_229_0.txt | ` unit ` | ` [ TimeUnit
](https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/TimeUnit.html)
` |
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