Get Models

get_models(self) → List[netspresso.compressor.core.model.ModelCollection]

Get the list of uploaded & compressed models.

Raises: e – If an error occurs while getting the model list.
Returns: The list of uploaded & compressed models.
Return type: List[ModelCollection]

Details of Returns

class ModelCollection(model_id: str, model_name: str, task: str, framework: str, model_size: float, flops: float, trainable_parameters: float, non_trainable_parameters: float, number_of_layers: int, input_shapes: List[netspresso.compressor.core.model.InputShape] = <factory>, compressed_models: List[netspresso.compressor.core.model.CompressedModel] = <factory>)[source]

Bases: netspresso.compressor.core.model.Model

A collection of models that includes the uploaded model and its compressed models.

compressed_models

A list of compressed models compressed from this model.

Type: List[CompressedModel]

Example

from netspresso.compressor import ModelCompressor


compressor = ModelCompressor(email="YOUR_EMAIL", password="YOUR_PASSWORD")
models = compressor.get_models()

Output

>>> models
[ModelCollection(
    model_id="f482a0d3-0321-49a4-a8d2-bd88ac124230",
    model_name="YOUR_MODEL_NAME",
    task="image_classification",
    framework="tensorflow_keras",
    input_shapes=[InputShape(batch=1, channel=3, dimension=[32, 32])],
    model_size=12.9641,
    flops=92.8979,
    trainable_parameters=3.3095,
    non_trainable_parameters=0.0219,
    number_of_layers=0,
    compressed_models=[CompressedModel(
        model_id="8cbd8b0c-68ca-42ae-b84b-921e7462ba88",
        model_name="YOUR_COMPRESSED_MODEL_NAME",
        task="image_classification",
        framework="tensorflow_keras",
        input_shapes=[InputShape(batch=1, channel=3, dimension=[32, 32])],
        model_size=2.9439,
        flops=24.1811,
        trainable_parameters=0.6933,
        non_trainable_parameters=0.01,
        number_of_layers=0,
        compression_id="ce584e7f-b76e-43cc-83fe-d140fe476a58",
        original_model_id="f482a0d3-0321-49a4-a8d2-bd88ac124230"
    )]
)]