Fix method doc signatures for multiline required parameters (#374)
* Fix method doc signatures for multiline required parameters.
Existing doc generator failed to recognize parameters as required when parameter descriptions
extended over more than one line. Besides presenting incorrect information, resulting
inconsistencies broke checks for automated sample generation.
* Regen docs
diff --git a/docs/dyn/ml_v1.projects.jobs.html b/docs/dyn/ml_v1.projects.jobs.html
index 89ffc72..abbb92d 100644
--- a/docs/dyn/ml_v1.projects.jobs.html
+++ b/docs/dyn/ml_v1.projects.jobs.html
@@ -75,23 +75,23 @@
<h1><a href="ml_v1.html">Google Cloud Machine Learning Engine</a> . <a href="ml_v1.projects.html">projects</a> . <a href="ml_v1.projects.jobs.html">jobs</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
- <code><a href="#cancel">cancel(name=None, body, x__xgafv=None)</a></code></p>
+ <code><a href="#cancel">cancel(name, body, x__xgafv=None)</a></code></p>
<p class="firstline">Cancels a running job.</p>
<p class="toc_element">
- <code><a href="#create">create(parent=None, body, x__xgafv=None)</a></code></p>
+ <code><a href="#create">create(parent, body, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a training or a batch prediction job.</p>
<p class="toc_element">
- <code><a href="#get">get(name=None, x__xgafv=None)</a></code></p>
+ <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Describes a job.</p>
<p class="toc_element">
- <code><a href="#list">list(parent=None, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</a></code></p>
+ <code><a href="#list">list(parent, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists the jobs in the project.</p>
<p class="toc_element">
<code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<h3>Method Details</h3>
<div class="method">
- <code class="details" id="cancel">cancel(name=None, body, x__xgafv=None)</code>
+ <code class="details" id="cancel">cancel(name, body, x__xgafv=None)</code>
<pre>Cancels a running job.
Args:
@@ -125,7 +125,7 @@
</div>
<div class="method">
- <code class="details" id="create">create(parent=None, body, x__xgafv=None)</code>
+ <code class="details" id="create">create(parent, body, x__xgafv=None)</code>
<pre>Creates a training or a batch prediction job.
Args:
@@ -136,11 +136,11 @@
The object takes the form of:
{ # Represents a training or prediction job.
- "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
+ "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
- "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -163,8 +163,37 @@
},
},
],
- "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
},
+ "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
+ "modelName": "A String", # Use this field if you want to use the default version for the specified
+ # model. The string must use the following format:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
+ "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
+ # prediction. If not set, Google Cloud ML will pick the runtime version used
+ # during the CreateVersion request for this model version, or choose the
+ # latest stable version when model version information is not available
+ # such as when the model is specified by uri.
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
+ # Defaults to 10 if not specified.
+ "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
+ # the model to use.
+ "outputPath": "A String", # Required. The output Google Cloud Storage location.
+ "dataFormat": "A String", # Required. The format of the input data files.
+ "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
+ # string is formatted the same way as `model_version`, with the addition
+ # of the version information:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ },
+ "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
+ "jobId": "A String", # Required. The user-specified id of the job.
+ "state": "A String", # Output only. The detailed state of a job.
"startTime": "A String", # Output only. When the job processing was started.
"trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
"workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
@@ -243,9 +272,9 @@
"maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
# should be unset if type is `CATEGORICAL`. This value should be integers if
# type is `INTEGER`.
- "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
- "A String",
- ],
+ "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
+ # should be unset if type is `CATEGORICAL`. This value should be integers if
+ # type is INTEGER.
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -255,9 +284,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
- # should be unset if type is `CATEGORICAL`. This value should be integers if
- # type is INTEGER.
+ "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
+ "A String",
+ ],
"type": "A String", # Required. The type of the parameter.
"scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
# Leave unset for categorical parameters.
@@ -313,35 +342,6 @@
# This value can only be used when `scale_tier` is set to `CUSTOM`.If you
# set this value, you must also set `parameter_server_type`.
},
- "jobId": "A String", # Required. The user-specified id of the job.
- "state": "A String", # Output only. The detailed state of a job.
- "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
- "modelName": "A String", # Use this field if you want to use the default version for the specified
- # model. The string must use the following format:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
- "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
- # prediction. If not set, Google Cloud ML will pick the runtime version used
- # during the CreateVersion request for this model version, or choose the
- # latest stable version when model version information is not available
- # such as when the model is specified by uri.
- "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
- # May contain wildcards.
- "A String",
- ],
- "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
- # Defaults to 10 if not specified.
- "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
- # the model to use.
- "outputPath": "A String", # Required. The output Google Cloud Storage location.
- "dataFormat": "A String", # Required. The format of the input data files.
- "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
- # string is formatted the same way as `model_version`, with the addition
- # of the version information:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
- "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
- },
"endTime": "A String", # Output only. When the job processing was completed.
"predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
"outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
@@ -361,11 +361,11 @@
An object of the form:
{ # Represents a training or prediction job.
- "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
+ "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
- "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -388,8 +388,37 @@
},
},
],
- "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
},
+ "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
+ "modelName": "A String", # Use this field if you want to use the default version for the specified
+ # model. The string must use the following format:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
+ "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
+ # prediction. If not set, Google Cloud ML will pick the runtime version used
+ # during the CreateVersion request for this model version, or choose the
+ # latest stable version when model version information is not available
+ # such as when the model is specified by uri.
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
+ # Defaults to 10 if not specified.
+ "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
+ # the model to use.
+ "outputPath": "A String", # Required. The output Google Cloud Storage location.
+ "dataFormat": "A String", # Required. The format of the input data files.
+ "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
+ # string is formatted the same way as `model_version`, with the addition
+ # of the version information:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ },
+ "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
+ "jobId": "A String", # Required. The user-specified id of the job.
+ "state": "A String", # Output only. The detailed state of a job.
"startTime": "A String", # Output only. When the job processing was started.
"trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
"workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
@@ -468,9 +497,9 @@
"maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
# should be unset if type is `CATEGORICAL`. This value should be integers if
# type is `INTEGER`.
- "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
- "A String",
- ],
+ "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
+ # should be unset if type is `CATEGORICAL`. This value should be integers if
+ # type is INTEGER.
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -480,9 +509,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
- # should be unset if type is `CATEGORICAL`. This value should be integers if
- # type is INTEGER.
+ "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
+ "A String",
+ ],
"type": "A String", # Required. The type of the parameter.
"scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
# Leave unset for categorical parameters.
@@ -538,35 +567,6 @@
# This value can only be used when `scale_tier` is set to `CUSTOM`.If you
# set this value, you must also set `parameter_server_type`.
},
- "jobId": "A String", # Required. The user-specified id of the job.
- "state": "A String", # Output only. The detailed state of a job.
- "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
- "modelName": "A String", # Use this field if you want to use the default version for the specified
- # model. The string must use the following format:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
- "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
- # prediction. If not set, Google Cloud ML will pick the runtime version used
- # during the CreateVersion request for this model version, or choose the
- # latest stable version when model version information is not available
- # such as when the model is specified by uri.
- "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
- # May contain wildcards.
- "A String",
- ],
- "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
- # Defaults to 10 if not specified.
- "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
- # the model to use.
- "outputPath": "A String", # Required. The output Google Cloud Storage location.
- "dataFormat": "A String", # Required. The format of the input data files.
- "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
- # string is formatted the same way as `model_version`, with the addition
- # of the version information:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
- "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
- },
"endTime": "A String", # Output only. When the job processing was completed.
"predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
"outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
@@ -579,7 +579,7 @@
</div>
<div class="method">
- <code class="details" id="get">get(name=None, x__xgafv=None)</code>
+ <code class="details" id="get">get(name, x__xgafv=None)</code>
<pre>Describes a job.
Args:
@@ -595,11 +595,11 @@
An object of the form:
{ # Represents a training or prediction job.
- "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
+ "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
- "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -622,8 +622,37 @@
},
},
],
- "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
},
+ "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
+ "modelName": "A String", # Use this field if you want to use the default version for the specified
+ # model. The string must use the following format:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
+ "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
+ # prediction. If not set, Google Cloud ML will pick the runtime version used
+ # during the CreateVersion request for this model version, or choose the
+ # latest stable version when model version information is not available
+ # such as when the model is specified by uri.
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
+ # Defaults to 10 if not specified.
+ "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
+ # the model to use.
+ "outputPath": "A String", # Required. The output Google Cloud Storage location.
+ "dataFormat": "A String", # Required. The format of the input data files.
+ "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
+ # string is formatted the same way as `model_version`, with the addition
+ # of the version information:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ },
+ "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
+ "jobId": "A String", # Required. The user-specified id of the job.
+ "state": "A String", # Output only. The detailed state of a job.
"startTime": "A String", # Output only. When the job processing was started.
"trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
"workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
@@ -702,9 +731,9 @@
"maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
# should be unset if type is `CATEGORICAL`. This value should be integers if
# type is `INTEGER`.
- "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
- "A String",
- ],
+ "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
+ # should be unset if type is `CATEGORICAL`. This value should be integers if
+ # type is INTEGER.
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -714,9 +743,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
- # should be unset if type is `CATEGORICAL`. This value should be integers if
- # type is INTEGER.
+ "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
+ "A String",
+ ],
"type": "A String", # Required. The type of the parameter.
"scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
# Leave unset for categorical parameters.
@@ -772,35 +801,6 @@
# This value can only be used when `scale_tier` is set to `CUSTOM`.If you
# set this value, you must also set `parameter_server_type`.
},
- "jobId": "A String", # Required. The user-specified id of the job.
- "state": "A String", # Output only. The detailed state of a job.
- "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
- "modelName": "A String", # Use this field if you want to use the default version for the specified
- # model. The string must use the following format:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
- "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
- # prediction. If not set, Google Cloud ML will pick the runtime version used
- # during the CreateVersion request for this model version, or choose the
- # latest stable version when model version information is not available
- # such as when the model is specified by uri.
- "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
- # May contain wildcards.
- "A String",
- ],
- "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
- # Defaults to 10 if not specified.
- "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
- # the model to use.
- "outputPath": "A String", # Required. The output Google Cloud Storage location.
- "dataFormat": "A String", # Required. The format of the input data files.
- "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
- # string is formatted the same way as `model_version`, with the addition
- # of the version information:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
- "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
- },
"endTime": "A String", # Output only. When the job processing was completed.
"predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
"outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
@@ -813,7 +813,7 @@
</div>
<div class="method">
- <code class="details" id="list">list(parent=None, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</code>
+ <code class="details" id="list">list(parent, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</code>
<pre>Lists the jobs in the project.
Args:
@@ -843,11 +843,11 @@
# subsequent call.
"jobs": [ # The list of jobs.
{ # Represents a training or prediction job.
- "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
+ "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
- "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -870,8 +870,37 @@
},
},
],
- "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
},
+ "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
+ "modelName": "A String", # Use this field if you want to use the default version for the specified
+ # model. The string must use the following format:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
+ "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
+ # prediction. If not set, Google Cloud ML will pick the runtime version used
+ # during the CreateVersion request for this model version, or choose the
+ # latest stable version when model version information is not available
+ # such as when the model is specified by uri.
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
+ # Defaults to 10 if not specified.
+ "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
+ # the model to use.
+ "outputPath": "A String", # Required. The output Google Cloud Storage location.
+ "dataFormat": "A String", # Required. The format of the input data files.
+ "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
+ # string is formatted the same way as `model_version`, with the addition
+ # of the version information:
+ #
+ # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ },
+ "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
+ "jobId": "A String", # Required. The user-specified id of the job.
+ "state": "A String", # Output only. The detailed state of a job.
"startTime": "A String", # Output only. When the job processing was started.
"trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
"workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
@@ -950,9 +979,9 @@
"maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
# should be unset if type is `CATEGORICAL`. This value should be integers if
# type is `INTEGER`.
- "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
- "A String",
- ],
+ "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
+ # should be unset if type is `CATEGORICAL`. This value should be integers if
+ # type is INTEGER.
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -962,9 +991,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
- # should be unset if type is `CATEGORICAL`. This value should be integers if
- # type is INTEGER.
+ "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
+ "A String",
+ ],
"type": "A String", # Required. The type of the parameter.
"scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
# Leave unset for categorical parameters.
@@ -1020,35 +1049,6 @@
# This value can only be used when `scale_tier` is set to `CUSTOM`.If you
# set this value, you must also set `parameter_server_type`.
},
- "jobId": "A String", # Required. The user-specified id of the job.
- "state": "A String", # Output only. The detailed state of a job.
- "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
- "modelName": "A String", # Use this field if you want to use the default version for the specified
- # model. The string must use the following format:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
- "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
- # prediction. If not set, Google Cloud ML will pick the runtime version used
- # during the CreateVersion request for this model version, or choose the
- # latest stable version when model version information is not available
- # such as when the model is specified by uri.
- "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
- # May contain wildcards.
- "A String",
- ],
- "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
- # Defaults to 10 if not specified.
- "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
- # the model to use.
- "outputPath": "A String", # Required. The output Google Cloud Storage location.
- "dataFormat": "A String", # Required. The format of the input data files.
- "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
- # string is formatted the same way as `model_version`, with the addition
- # of the version information:
- #
- # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
- "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
- },
"endTime": "A String", # Output only. When the job processing was completed.
"predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
"outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.