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Create/list model docstrings (googleapis#10)
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@lwander
lwander authored Jul 2, 2019
1 parent 89510df commit ff4755c
Showing 1 changed file with 95 additions and 7 deletions.
102 changes: 95 additions & 7 deletions automl/google/cloud/automl_v1beta1/helper/tables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -591,10 +591,10 @@ def update_column_spec(self, dataset=None, dataset_display_name=None,
If you have initialized the client with a value for `region` it
will be used if this parameter is not supplied.
column_spec_name (Optional[string]):
The name AutoML-assigned name for the column you want to
The name AutoML-assigned name for the column you want to
update.
column_spec_display_name (Optional[string]):
The human-readable name of the column you want to update. If
The human-readable name of the column you want to update. If
this is supplied in place of `column_spec_name`, you also
need to provide either a way to lookup the source dataset
(using one of the `dataset*` kwargs), or the `table_spec_name`
Expand All @@ -607,19 +607,19 @@ def update_column_spec(self, dataset=None, dataset_display_name=None,
If no `table_spec_name` was provided, we use this index to
determine which table to update column specs on.
dataset_display_name (Optional[string]):
The human-readable name given to the dataset you want to update
The human-readable name given to the dataset you want to update
specs on. If no `table_spec_name` is supplied, this will
be used together with `table_spec_index` to infer the name of
table to update specs on. This must be supplied if `table_spec_name`,
`dataset` or `dataset_name` are not supplied.
dataset_name (Optional[string]):
The AutoML-assigned name given to the dataset you want to update
The AutoML-assigned name given to the dataset you want to update
specs one. If no `table_spec_name` is supplied, this will
be used together with `table_spec_index` to infer the name of
table to update specs on. This must be supplied if `table_spec_name`,
`dataset` or `dataset_display_name` are not supplied.
dataset (Optional[Dataset]):
The `Dataset` instance you want to update
The `Dataset` instance you want to update
specs on. If no `table_spec_name` is supplied, this will
be used together with `table_spec_index` to infer the name of
table to update specs on. This must be supplied if `table_spec_name`,
Expand Down Expand Up @@ -699,7 +699,7 @@ def set_target_column(self, dataset=None, dataset_display_name=None,
If you have initialized the client with a value for `region` it
will be used if this parameter is not supplied.
column_spec_name (Optional[string]):
The name AutoML-assigned name for the column you want to
The name AutoML-assigned name for the column you want to
set as the target column.
column_spec_display_name (Optional[string]):
The human-readable name of the column you want to set as the
Expand Down Expand Up @@ -802,7 +802,7 @@ def set_weight_column(self, dataset=None, dataset_display_name=None,
If you have initialized the client with a value for `region` it
will be used if this parameter is not supplied.
column_spec_name (Optional[string]):
The name AutoML-assigned name for the column you want to
The name AutoML-assigned name for the column you want to
set as the weight column.
column_spec_display_name (Optional[string]):
The human-readable name of the column you want to set as the
Expand Down Expand Up @@ -879,6 +879,44 @@ def set_weight_column(self, dataset=None, dataset_display_name=None,
return self.client.update_dataset(request)

def list_models(self, project=None, region=None):
"""List all models in a particular project and region.
Example:
>>> from google.cloud import automl_v1beta1
>>>
>>> client = automl_v1beta1.tables.ClientHelper(
... client=automl_v1beta1.AutoMlClient(),
... project='my-project', region='us-central1')
>>>
>>> ms = client.list_models()
>>>
>>> for m in ms:
... # do something
... pass
Args:
project (Optional[string]):
If you have initialized the client with a value for `project`
it will be used if this parameter is not supplied. Keep in
mind, the service account this client was initialized with must
have access to this project.
region (Optional[string]):
If you have initialized the client with a value for `region` it
will be used if this parameter is not supplied.
Returns:
A :class:`~google.api_core.page_iterator.PageIterator` instance.
An iterable of :class:`~google.cloud.automl_v1beta1.types.Model`
instances. You can also iterate over the pages of the response
using its `pages` property.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If required parameters are missing.
"""
return self.client.list_models(
self.__location_path(project=project, region=region)
)
Expand All @@ -887,6 +925,55 @@ def create_model(self, model_display_name, dataset=None,
dataset_display_name=None, dataset_name=None,
train_budget_milli_node_hours=None, project=None,
region=None):
"""Create a model. This will train your model on the given dataset.
Example:
>>> from google.cloud import automl_v1beta1
>>>
>>> client = automl_v1beta1.tables.ClientHelper(
... client=automl_v1beta1.AutoMlClient(),
... project='my-project', region='us-central1')
>>>
>>> d = client.create_model('my_model', dataset_display_name='my_dataset')
Args:
project (Optional[string]):
If you have initialized the client with a value for `project`
it will be used if this parameter is not supplied. Keep in
mind, the service account this client was initialized with must
have access to this project.
region (Optional[string]):
If you have initialized the client with a value for `region` it
will be used if this parameter is not supplied.
model_display_name (string):
a human-readable name to refer to this model by.
train_budget_milli_node_hours (int):
The amount of time (in thousandths of an hour) to spend
training. This value must be between 1,000 and 72,000 inclusive
(between 1 and 72 hours).
dataset_display_name (Optional[string]):
The human-readable name given to the dataset you want to train
your model on. This must be supplied if `dataset` or
`dataset_name` are not supplied.
dataset_name (Optional[string]):
The AutoML-assigned name given to the dataset you want to train
your model on. This must be supplied if `dataset_display_name`
or `dataset` are not supplied.
dataset (Optional[Dataset]):
The `Dataset` instance you want to train your model on. This
must be supplied if `dataset_display_name` or `dataset_name`
are not supplied.
Returns:
A :class:`~google.cloud.automl_v1beta1.types.Dataset` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If required parameters are missing.
"""
if train_budget_milli_node_hours is None:
raise ValueError('\'train_budget_milli_node_hours\' must be a '
'value between 1,000 and 72,000 inclusive')
Expand Down Expand Up @@ -930,6 +1017,7 @@ def get_model(self, project=None, region=None,
return next(m for m in self.list_models(project, region)
if m.name == model_name
or m.display_name == model_display_name)

#TODO(jonathanskim): allow deployment from just model ID
def deploy_model(self, model=None, model_name=None,
model_display_name=None, project=None, region=None):
Expand Down

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