batchCreate(parent, body=None, x__xgafv=None)

Batch create TensorboardRuns.

Args:
parent: string, Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field. (required)
body: object, The request body.
The object takes the form of:

{ # Request message for TensorboardService.BatchCreateTensorboardRuns.
"requests": [ # Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch.
{ # Request message for TensorboardService.CreateTensorboardRun.
"parent": "A String", # Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
"tensorboardRun": { # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc # Required. The TensorboardRun to create.
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
},
"tensorboardRunId": "A String", # Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
},
],
}

x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # Response message for TensorboardService.BatchCreateTensorboardRuns.
"tensorboardRuns": [ # The created TensorboardRuns.
{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
},
],
}

close()

Close httplib2 connections.

create(parent, body=None, tensorboardRunId=None, x__xgafv=None)

Creates a TensorboardRun.

Args:
parent: string, Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` (required)
body: object, The request body.
The object takes the form of:

{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
}

tensorboardRunId: string, Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
}

delete(name, x__xgafv=None)

Deletes a TensorboardRun.

Args:
name: string, Required. The name of the TensorboardRun to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

get(name, x__xgafv=None)

Gets a TensorboardRun.

Args:
name: string, Required. The name of the TensorboardRun resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
}

list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, readMask=None, x__xgafv=None)

Lists TensorboardRuns in a Location.

Args:
parent: string, Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` (required)
filter: string, Lists the TensorboardRuns that match the filter expression.
orderBy: string, Field to use to sort the list.
pageSize: integer, The maximum number of TensorboardRuns to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardRuns are returned. The maximum value is 1000; values above 1000 are coerced to 1000.
pageToken: string, A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token.
readMask: string, Mask specifying which fields to read.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # Response message for TensorboardService.ListTensorboardRuns.
"nextPageToken": "A String", # A token, which can be sent as ListTensorboardRunsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.
"tensorboardRuns": [ # The TensorboardRuns mathching the request.
{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
},
],
}

list_next()

Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates a TensorboardRun.

Args:
name: string, Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` (required)
body: object, The request body.
The object takes the form of:

{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
}

updateMask: string, Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
"createTime": "A String", # Output only. Timestamp when this TensorboardRun was created.
"description": "A String", # Description of this TensorboardRun.
"displayName": "A String", # Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
"etag": "A String", # Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
"updateTime": "A String", # Output only. Timestamp when this TensorboardRun was last updated.
}

write(tensorboardRun, body=None, x__xgafv=None)

Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.

Args:
  tensorboardRun: string, Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for TensorboardService.WriteTensorboardRunData.
  "tensorboardRun": "A String", # Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
  "timeSeriesData": [ # Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000.
    { # All the data stored in a TensorboardTimeSeries.
      "tensorboardTimeSeriesId": "A String", # Required. The ID of the TensorboardTimeSeries, which will become the final component of the TensorboardTimeSeries' resource name
      "valueType": "A String", # Required. Immutable. The value type of this time series. All the values in this time series data must match this value type.
      "values": [ # Required. Data points in this time series.
        { # A TensorboardTimeSeries data point.
          "blobs": { # One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields. # A blob sequence value.
            "values": [ # List of blobs contained within the sequence.
              { # One blob (e.g, image, graph) viewable on a blob metric plot.
                "data": "A String", # Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint.
                "id": "A String", # Output only. A URI safe key uniquely identifying a blob. Can be used to locate the blob stored in the Cloud Storage bucket of the consumer project.
              },
            ],
          },
          "scalar": { # One point viewable on a scalar metric plot. # A scalar value.
            "value": 3.14, # Value of the point at this step / timestamp.
          },
          "step": "A String", # Step index of this data point within the run.
          "tensor": { # One point viewable on a tensor metric plot. # A tensor value.
            "value": "A String", # Required. Serialized form of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto
            "versionNumber": 42, # Optional. Version number of TensorProto used to serialize value.
          },
          "wallTime": "A String", # Wall clock timestamp when this data point is generated by the end user.
        },
      ],
    },
  ],
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for TensorboardService.WriteTensorboardRunData.
}

Vertex AI API . projects . locations . tensorboards . experiments . runs

Instance Methods

Method Details