Clean and regen docs (#401)
diff --git a/docs/dyn/ml_v1beta1.projects.jobs.html b/docs/dyn/ml_v1beta1.projects.jobs.html
index 4980b42..cd6f67a 100644
--- a/docs/dyn/ml_v1beta1.projects.jobs.html
+++ b/docs/dyn/ml_v1beta1.projects.jobs.html
@@ -136,7 +136,6 @@
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.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
@@ -165,7 +164,6 @@
],
"consumedMLUnits": 3.14, # The amount of ML units consumed by the 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.
@@ -222,7 +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>
@@ -243,9 +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
@@ -255,9 +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.
@@ -291,6 +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
@@ -313,6 +312,8 @@
# 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`.
},
+ "startTime": "A String", # Output only. When the job processing was started.
+ "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.
"predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
@@ -361,7 +362,6 @@
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.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
@@ -390,7 +390,6 @@
],
"consumedMLUnits": 3.14, # The amount of ML units consumed by the 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.
@@ -447,7 +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>
@@ -468,9 +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
@@ -480,9 +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.
@@ -516,6 +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
@@ -538,6 +538,8 @@
# 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`.
},
+ "startTime": "A String", # Output only. When the job processing was started.
+ "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.
"predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
@@ -595,7 +597,6 @@
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.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
@@ -624,7 +625,6 @@
],
"consumedMLUnits": 3.14, # The amount of ML units consumed by the 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.
@@ -681,7 +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>
@@ -702,9 +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
@@ -714,9 +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.
@@ -750,6 +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
@@ -772,6 +773,8 @@
# 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`.
},
+ "startTime": "A String", # Output only. When the job processing was started.
+ "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.
"predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
@@ -843,7 +846,6 @@
# 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.
"completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
# Only set for hyperparameter tuning jobs.
@@ -872,7 +874,6 @@
],
"consumedMLUnits": 3.14, # The amount of ML units consumed by the 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.
@@ -929,7 +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>
@@ -950,9 +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
@@ -962,9 +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.
@@ -998,6 +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
@@ -1020,6 +1022,8 @@
# 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`.
},
+ "startTime": "A String", # Output only. When the job processing was started.
+ "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.
"predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.