trained_model

Creates, updates, deletes, gets or lists a trained_model resource.

Overview

Name	trained_model
Type	Resource
Id	azure.ai_language.trained_model

Fields

The following fields are returned by SELECT queries:

get_evaluation_status

Name	Datatype	Description
createdDateTime	string (date-time)	The creation date time of the job. Required.
errors	array	The errors encountered while executing the job.
expirationDateTime	string (date-time)	The expiration date time of the job.
jobId	string	The job ID. Required.
lastUpdatedDateTime	string (date-time)	The last date time the job was updated. Required.
result	object	Represents evaluation task detailed result. Required.
status	string	The job status. Required. Known values are: "notStarted", "running", "succeeded", "failed", "cancelled", "cancelling", and "partiallyCompleted". (notStarted, running, succeeded, failed, cancelled, cancelling, partiallyCompleted)
warnings	array	The warnings that were encountered while executing the job.

get_model_evaluation_results

Name	Datatype	Description
entitiesResult	object	Represents the entities results for the utterance. Required.
intentsResult	object	Represents the intents results for the utterance. Required.
language	string	Represents the utterance language. This is BCP-47 representation of a language. For example, use "en" for English, "en-gb" for English (UK), "es" for Spanish etc. Required.
text	string	Represents the utterance text. Required.

get_trained_model

Name	Datatype	Description
hasSnapshot	boolean	The flag to indicate if the trained model has a snapshot ready. Required.
label	string	The trained model label. Required.
lastTrainedDateTime	string (date-time)	The last trained date time of the model. Required.
lastTrainingDurationInSeconds	integer	The duration of the model's last training request in seconds. Required.
modelExpirationDate	string (date)	The model expiration date. Required.
modelId	string	The model ID. Required.
modelTrainingConfigVersion	string	The model training config version. Required.

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
get_evaluation_status	select	trained_model_label, job_id, project_name, endpoint		Gets the status for an evaluation job.
get_model_evaluation_results	select	trained_model_label, project_name, stringIndexType, endpoint	top, skip, maxpagesize	Gets the detailed results of the evaluation for a trained model. This includes the raw inference results for the data included in the evaluation process.
get_trained_model	select	trained_model_label, project_name, endpoint		Gets the details of a trained model.
delete_trained_model	delete	trained_model_label, project_name, endpoint		Deletes an existing trained model.
get_model_evaluation_summary	exec	trained_model_label, project_name, endpoint		Gets the evaluation summary of a trained model. The summary includes high level performance measurements of the model e.g., F1, Precision, Recall, etc.
get_load_snapshot_status	exec	trained_model_label, job_id, project_name, endpoint		Gets the status for loading a snapshot.
evaluate_model	exec	trained_model_label, project_name, endpoint		Triggers evaluation operation on a trained model.
load_snapshot	exec	trained_model_label, project_name, endpoint		Restores the snapshot of this trained model to be the current working directory of the project.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
endpoint	string	The service endpoint host (no scheme), e.g. myaccount.table.cosmos.azure.com:443 - value of the client Endpoint parameter. (default: )
job_id	string	The job ID. Required.
project_name	string
stringIndexType	string	Specifies the method used to interpret string offsets. For additional information see https://aka.ms/text-analytics-offsets _. Known values are: "Utf16CodeUnit", "Utf8CodeUnit", and "Utf32CodeUnit". Required.
trained_model_label	string	The trained model label. Required.
maxpagesize	integer
skip	integer	The number of result items to skip. Default value is None.
top	integer	The number of result items to return. Default value is None.

SELECT examples

get_evaluation_status

Gets the status for an evaluation job.

SELECT
createdDateTime,
errors,
expirationDateTime,
jobId,
lastUpdatedDateTime,
result,
status,
warnings
FROM azure.ai_language.trained_model
WHERE trained_model_label = '{{ trained_model_label }}' -- required
AND job_id = '{{ job_id }}' -- required
AND project_name = '{{ project_name }}' -- required
AND endpoint = '{{ endpoint }}' -- required
;

get_model_evaluation_results

Gets the detailed results of the evaluation for a trained model. This includes the raw inference results for the data included in the evaluation process.

SELECT
entitiesResult,
intentsResult,
language,
text
FROM azure.ai_language.trained_model
WHERE trained_model_label = '{{ trained_model_label }}' -- required
AND project_name = '{{ project_name }}' -- required
AND stringIndexType = '{{ stringIndexType }}' -- required
AND endpoint = '{{ endpoint }}' -- required
AND top = '{{ top }}'
AND skip = '{{ skip }}'
AND maxpagesize = '{{ maxpagesize }}'
;

get_trained_model

Gets the details of a trained model.

SELECT
hasSnapshot,
label,
lastTrainedDateTime,
lastTrainingDurationInSeconds,
modelExpirationDate,
modelId,
modelTrainingConfigVersion
FROM azure.ai_language.trained_model
WHERE trained_model_label = '{{ trained_model_label }}' -- required
AND project_name = '{{ project_name }}' -- required
AND endpoint = '{{ endpoint }}' -- required
;

DELETE examples

delete_trained_model

Deletes an existing trained model.

DELETE FROM azure.ai_language.trained_model
WHERE trained_model_label = '{{ trained_model_label }}' --required
AND project_name = '{{ project_name }}' --required
AND endpoint = '{{ endpoint }}' --required
;

Lifecycle Methods

get_model_evaluation_summary

Gets the evaluation summary of a trained model. The summary includes high level performance measurements of the model e.g., F1, Precision, Recall, etc.

EXEC azure.ai_language.trained_model.get_model_evaluation_summary 
@trained_model_label='{{ trained_model_label }}' --required, 
@project_name='{{ project_name }}' --required, 
@endpoint='{{ endpoint }}' --required
;

get_load_snapshot_status

Gets the status for loading a snapshot.

EXEC azure.ai_language.trained_model.get_load_snapshot_status 
@trained_model_label='{{ trained_model_label }}' --required, 
@job_id='{{ job_id }}' --required, 
@project_name='{{ project_name }}' --required, 
@endpoint='{{ endpoint }}' --required
;

evaluate_model

Triggers evaluation operation on a trained model.

EXEC azure.ai_language.trained_model.evaluate_model 
@trained_model_label='{{ trained_model_label }}' --required, 
@project_name='{{ project_name }}' --required, 
@endpoint='{{ endpoint }}' --required 
@@json=
'{
"kind": "{{ kind }}", 
"trainingSplitPercentage": {{ trainingSplitPercentage }}, 
"testingSplitPercentage": {{ testingSplitPercentage }}
}'
;

load_snapshot

Restores the snapshot of this trained model to be the current working directory of the project.

EXEC azure.ai_language.trained_model.load_snapshot 
@trained_model_label='{{ trained_model_label }}' --required, 
@project_name='{{ project_name }}' --required, 
@endpoint='{{ endpoint }}' --required
;