Clean and regen docs (#401)
diff --git a/docs/dyn/ml_v1.projects.jobs.html b/docs/dyn/ml_v1.projects.jobs.html
index abbb92d..50e5559 100644
--- a/docs/dyn/ml_v1.projects.jobs.html
+++ b/docs/dyn/ml_v1.projects.jobs.html
@@ -137,10 +137,6 @@
{ # Represents a training or prediction job.
"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.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -163,38 +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.
@@ -251,7 +220,7 @@
# <dt>complex_model_m_gpu</dt>
# <dd>
# A machine equivalent to
- # <code suppresswarning="true">coplex_model_m</code> that also includes
+ # <code suppresswarning="true">complex_model_m</code> that also includes
# four GPUs.
# </dd>
# </dl>
@@ -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`.
- "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",
+ ],
"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".
- "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.
"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.
@@ -294,6 +263,10 @@
# 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
@@ -304,10 +277,6 @@
# 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.
@@ -320,6 +289,7 @@
# this field is that Cloud ML validates the path for use in training.
"packageUris": [ # Required. The Google Cloud Storage location of the packages with
# the training program and any additional dependencies.
+ # The maximum number of package URIs is 100.
"A String",
],
"workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
@@ -342,6 +312,37 @@
# 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.
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ "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>"`
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ },
+ "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.
@@ -362,10 +363,6 @@
{ # Represents a training or prediction job.
"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.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -388,38 +385,11 @@
},
},
],
+ "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.
@@ -476,7 +446,7 @@
# <dt>complex_model_m_gpu</dt>
# <dd>
# A machine equivalent to
- # <code suppresswarning="true">coplex_model_m</code> that also includes
+ # <code suppresswarning="true">complex_model_m</code> that also includes
# four GPUs.
# </dd>
# </dl>
@@ -497,9 +467,9 @@
"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`.
- "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",
+ ],
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -509,9 +479,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "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.
"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.
@@ -519,6 +489,10 @@
# 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
@@ -529,10 +503,6 @@
# 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.
@@ -545,6 +515,7 @@
# this field is that Cloud ML validates the path for use in training.
"packageUris": [ # Required. The Google Cloud Storage location of the packages with
# the training program and any additional dependencies.
+ # The maximum number of package URIs is 100.
"A String",
],
"workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
@@ -567,6 +538,37 @@
# 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.
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ "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>"`
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ },
+ "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.
@@ -596,10 +598,6 @@
{ # Represents a training or prediction job.
"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.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -622,38 +620,11 @@
},
},
],
+ "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.
@@ -710,7 +681,7 @@
# <dt>complex_model_m_gpu</dt>
# <dd>
# A machine equivalent to
- # <code suppresswarning="true">coplex_model_m</code> that also includes
+ # <code suppresswarning="true">complex_model_m</code> that also includes
# four GPUs.
# </dd>
# </dl>
@@ -731,9 +702,9 @@
"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`.
- "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",
+ ],
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -743,9 +714,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "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.
"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.
@@ -753,6 +724,10 @@
# 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
@@ -763,10 +738,6 @@
# 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.
@@ -779,6 +750,7 @@
# this field is that Cloud ML validates the path for use in training.
"packageUris": [ # Required. The Google Cloud Storage location of the packages with
# the training program and any additional dependencies.
+ # The maximum number of package URIs is 100.
"A String",
],
"workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
@@ -801,6 +773,37 @@
# 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.
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ "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>"`
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ },
+ "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.
@@ -844,10 +847,6 @@
"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.
- "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.
"trials": [ # Results for individual Hyperparameter trials.
# Only set for hyperparameter tuning jobs.
{ # Represents the result of a single hyperparameter tuning trial from a
@@ -870,38 +869,11 @@
},
},
],
+ "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.
@@ -958,7 +930,7 @@
# <dt>complex_model_m_gpu</dt>
# <dd>
# A machine equivalent to
- # <code suppresswarning="true">coplex_model_m</code> that also includes
+ # <code suppresswarning="true">complex_model_m</code> that also includes
# four GPUs.
# </dd>
# </dl>
@@ -979,9 +951,9 @@
"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`.
- "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",
+ ],
"discreteValues": [ # Required if type is `DISCRETE`.
# A list of feasible points.
# The list should be in strictly increasing order. For instance, this
@@ -991,9 +963,9 @@
],
"parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
# a HyperparameterSpec message. E.g., "learning_rate".
- "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.
"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.
@@ -1001,6 +973,10 @@
# 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
@@ -1011,10 +987,6 @@
# 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.
@@ -1027,6 +999,7 @@
# this field is that Cloud ML validates the path for use in training.
"packageUris": [ # Required. The Google Cloud Storage location of the packages with
# the training program and any additional dependencies.
+ # The maximum number of package URIs is 100.
"A String",
],
"workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
@@ -1049,6 +1022,37 @@
# 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.
+ "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
+ "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>"`
+ "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
+ # May contain wildcards.
+ "A String",
+ ],
+ },
+ "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.