The CREATE MODEL statement for importing TensorFlow Lite models

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CREATE MODEL statement for TensorFlow Lite

To import an existing TensorFlow Lite model into BigQuery from Cloud Storage, use the BigQuery ML CREATE MODEL statement with the TensorFlow Lite model type.

For information about supported model types of each SQL statement and function, and all supported SQL statements and functions for each model type, read End-to-end user journey for each model.

CREATE MODEL syntax

{CREATE MODEL | CREATE MODEL IF NOT EXISTS | CREATE OR REPLACE MODEL}
model_name
[OPTIONS(MODEL_TYPE = 'TENSORFLOW_LITE', MODEL_PATH = string_value)];

CREATE MODEL

Creates a new BigQuery model in the specified dataset. For TensorFlow Lite models, BigQuery imports the existing TensorFlow Lite model and converts it to a BigQuery model. If the model name exists, CREATE MODEL returns an error.

CREATE MODEL IF NOT EXISTS

Creates a new imported model only if the model does not currently exist in the specified dataset.

CREATE OR REPLACE MODEL

Creates a new imported model and replaces any existing model with the same name in the specified dataset.

model_name

model_name is the name of the BigQuery model you're creating or replacing. The model name must be unique per dataset: no other model or table can have the same name. The model name must follow the same naming rules as a BigQuery table. A model name can contain the following:

• Up to 1,024 characters
• Letters of either case, numbers, and underscores

model_name is not case-sensitive.

If you do not have a default project configured, prepend the project ID to the model name in following format, including backticks:

`[PROJECT_ID].[DATASET].[MODEL]`

For example:

`myproject.mydataset.mymodel`

CREATE MODEL supports the following options:

MODEL_TYPE

Syntax

MODEL_TYPE = 'TENSORFLOW_LITE'

Description

Specifies the model type. This option is required.

MODEL_PATH

Syntax

MODEL_PATH = string_value

Description

Specifies the Cloud Storage URI of the TensorFlow Lite model to import. This option is required for TensorFlow Lite models.

string_value is the URI of a Cloud Storage bucket that contains the model to import.

BigQuery imports the model from Cloud Storage using the credentials of the user who sent the CREATE MODEL statement.

Example

MODEL_PATH = 'gs://bucket/path/to/tflite_model/*'

Supported inputs

The CREATE MODEL statement supports the following data types for input label and data split columns.

Supported data types for TensorFlow Lite model inputs and outputs

BigQuery converts certain TensorFlow Lite model inputs and outputs to BigQuery types. Some TensorFlow Lite model input and output types are not supported. Supported data types for the inputs and outputs of the imported TensorFlow Lite model include:

TensorFlow Lite types	Supported	BigQuery type
UINT8, UINT16, UINT32, UINT64, INT8, INT16, INT32, INT64	Supported	INT64
FLOAT16, FLOAT32, FLOAT64	Supported	FLOAT64
COMPLEX64, COMPLEX128	Unsupported	N/a
BOOL	Supported	BOOL
STRING	Supported	STRING
RESOURCE	Unsupported	N/a
VARIANT	Unsupported	N/a

Limitations

CREATE MODEL statements for TensorFlow Lite models must comply with the following rules:

• The TensorFlow Lite model must exist before it can be imported into BigQuery.
• Models must be stored in Cloud Storage.
• TensorFlow Lite models must be in .tflite format.
• Only ML.PREDICT is supported for TensorFlow Lite models.
• Models are limited to 450 MB in size.
• Only Tensorflow core operations and TensorFlow Text operations are supported in BigQuery.
• SentencePiece operators are not supported.
• Sparse tensors are not supported.

CREATE MODEL examples

The following example creates models named mymodel in mydataset in your default project.

Importing a TensorFlow Lite model

The following example imports a TensorFlow Lite model into BigQuery as a BigQuery model. The example assumes that there is an existing TensorFlow Lite model located at gs://bucket/path/to/tflite_model/*.

CREATE MODEL project_id.mydataset.mymodel
 OPTIONS(MODEL_TYPE='TENSORFLOW_LITE',
         MODEL_PATH="gs://bucket/path/to/tflite_model/*")