Regen docs (#373)
diff --git a/docs/dyn/ml_v1beta1.projects.jobs.html b/docs/dyn/ml_v1beta1.projects.jobs.html
index 57245ca..0399c35 100644
--- a/docs/dyn/ml_v1beta1.projects.jobs.html
+++ b/docs/dyn/ml_v1beta1.projects.jobs.html
@@ -137,9 +137,6 @@
{ # Represents a training or prediction job.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
- "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
@@ -162,39 +159,11 @@
},
},
],
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
+ # Only set for hyperparameter tuning jobs.
},
- "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
# job's worker nodes.
@@ -245,7 +214,7 @@
# <dd>
# A machine equivalent to <code suppresswarning="true">standard</code> that
# also includes a
- # <a href="ml/docs/how-tos/using-gpus">
+ # <a href="/ml-engine/docs/how-tos/using-gpus">
# GPU that you can use in your trainer</a>.
# </dd>
# <dt>complex_model_m_gpu</dt>
@@ -272,9 +241,9 @@
"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
@@ -284,9 +253,9 @@
],
"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.
@@ -294,10 +263,6 @@
# parameters (e.g., `UNIT_LINEAR_SCALE`).
},
],
- "goal": "A String", # Required. The type of goal to use for tuning. Available types are
- # `MAXIMIZE` and `MINIMIZE`.
- #
- # Defaults to `MAXIMIZE`.
"maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
# You can reduce the time it takes to perform hyperparameter tuning by adding
# trials in parallel. However, each trail only benefits from the information
@@ -308,6 +273,10 @@
# Each trial will use the same scale tier and machine types.
#
# Defaults to one.
+ "goal": "A String", # Required. The type of goal to use for tuning. Available types are
+ # `MAXIMIZE` and `MINIMIZE`.
+ #
+ # Defaults to `MAXIMIZE`.
},
"region": "A String", # Required. The Google Compute Engine region to run the training job in.
"args": [ # Optional. Command line arguments to pass to the program.
@@ -342,6 +311,37 @@
# 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`.
},
+ "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.
"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.
@@ -362,9 +362,6 @@
{ # Represents a training or prediction job.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
- "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
@@ -387,39 +384,11 @@
},
},
],
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
+ # Only set for hyperparameter tuning jobs.
},
- "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
# job's worker nodes.
@@ -470,7 +439,7 @@
# <dd>
# A machine equivalent to <code suppresswarning="true">standard</code> that
# also includes a
- # <a href="ml/docs/how-tos/using-gpus">
+ # <a href="/ml-engine/docs/how-tos/using-gpus">
# GPU that you can use in your trainer</a>.
# </dd>
# <dt>complex_model_m_gpu</dt>
@@ -497,9 +466,9 @@
"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
@@ -509,9 +478,9 @@
],
"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.
@@ -519,10 +488,6 @@
# parameters (e.g., `UNIT_LINEAR_SCALE`).
},
],
- "goal": "A String", # Required. The type of goal to use for tuning. Available types are
- # `MAXIMIZE` and `MINIMIZE`.
- #
- # Defaults to `MAXIMIZE`.
"maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
# You can reduce the time it takes to perform hyperparameter tuning by adding
# trials in parallel. However, each trail only benefits from the information
@@ -533,6 +498,10 @@
# Each trial will use the same scale tier and machine types.
#
# Defaults to one.
+ "goal": "A String", # Required. The type of goal to use for tuning. Available types are
+ # `MAXIMIZE` and `MINIMIZE`.
+ #
+ # Defaults to `MAXIMIZE`.
},
"region": "A String", # Required. The Google Compute Engine region to run the training job in.
"args": [ # Optional. Command line arguments to pass to the program.
@@ -567,6 +536,37 @@
# 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`.
},
+ "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.
"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.
@@ -596,9 +596,6 @@
{ # Represents a training or prediction job.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
- "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
@@ -621,39 +618,11 @@
},
},
],
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
+ # Only set for hyperparameter tuning jobs.
},
- "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
# job's worker nodes.
@@ -704,7 +673,7 @@
# <dd>
# A machine equivalent to <code suppresswarning="true">standard</code> that
# also includes a
- # <a href="ml/docs/how-tos/using-gpus">
+ # <a href="/ml-engine/docs/how-tos/using-gpus">
# GPU that you can use in your trainer</a>.
# </dd>
# <dt>complex_model_m_gpu</dt>
@@ -731,9 +700,9 @@
"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
@@ -743,9 +712,9 @@
],
"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.
@@ -753,10 +722,6 @@
# parameters (e.g., `UNIT_LINEAR_SCALE`).
},
],
- "goal": "A String", # Required. The type of goal to use for tuning. Available types are
- # `MAXIMIZE` and `MINIMIZE`.
- #
- # Defaults to `MAXIMIZE`.
"maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
# You can reduce the time it takes to perform hyperparameter tuning by adding
# trials in parallel. However, each trail only benefits from the information
@@ -767,6 +732,10 @@
# Each trial will use the same scale tier and machine types.
#
# Defaults to one.
+ "goal": "A String", # Required. The type of goal to use for tuning. Available types are
+ # `MAXIMIZE` and `MINIMIZE`.
+ #
+ # Defaults to `MAXIMIZE`.
},
"region": "A String", # Required. The Google Compute Engine region to run the training job in.
"args": [ # Optional. Command line arguments to pass to the program.
@@ -801,6 +770,37 @@
# 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`.
},
+ "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.
"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.
@@ -844,9 +844,6 @@
"jobs": [ # The list of jobs.
{ # Represents a training or prediction job.
"trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
- "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
@@ -869,39 +866,11 @@
},
},
],
+ "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
"consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
+ "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
+ # Only set for hyperparameter tuning jobs.
},
- "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
# job's worker nodes.
@@ -952,7 +921,7 @@
# <dd>
# A machine equivalent to <code suppresswarning="true">standard</code> that
# also includes a
- # <a href="ml/docs/how-tos/using-gpus">
+ # <a href="/ml-engine/docs/how-tos/using-gpus">
# GPU that you can use in your trainer</a>.
# </dd>
# <dt>complex_model_m_gpu</dt>
@@ -979,9 +948,9 @@
"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
@@ -991,9 +960,9 @@
],
"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.
@@ -1001,10 +970,6 @@
# parameters (e.g., `UNIT_LINEAR_SCALE`).
},
],
- "goal": "A String", # Required. The type of goal to use for tuning. Available types are
- # `MAXIMIZE` and `MINIMIZE`.
- #
- # Defaults to `MAXIMIZE`.
"maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
# You can reduce the time it takes to perform hyperparameter tuning by adding
# trials in parallel. However, each trail only benefits from the information
@@ -1015,6 +980,10 @@
# Each trial will use the same scale tier and machine types.
#
# Defaults to one.
+ "goal": "A String", # Required. The type of goal to use for tuning. Available types are
+ # `MAXIMIZE` and `MINIMIZE`.
+ #
+ # Defaults to `MAXIMIZE`.
},
"region": "A String", # Required. The Google Compute Engine region to run the training job in.
"args": [ # Optional. Command line arguments to pass to the program.
@@ -1049,6 +1018,37 @@
# 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`.
},
+ "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.
"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.