Get Uploaded Models

get_uploaded_models(self) → List[netspresso.compressor.core.model.Model]

Get the list of uploaded models.

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

Details of Returns

class Model(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>)[source]

Represents a uploaded model.

model_id

The ID of the model.

Type: str

model_name

The name of the model.

Type: str

task

The task of the model.

Type: Task

framework

The framework of the model.

Type: Framework

input_shapes

The input shapes of the model.

InputShape Attributes:

batch (int): The batch size of the input tensor.
channel (int): The number of channels in the input tensor.
dimension (List[int]): The dimensions of the input tensor.

Type: List[InputShape]

model_size

The size of the model.

Type: float

flops

The FLOPs (floating point operations) of the model.

Type: float

trainable_parameters

The number of trainable parameters in the model.

Type: float

non_trainable_parameters

The number of non-trainable parameters in the model.

Type: float

number_of_layers

The number of layers in the model.

Type: float

Example

from netspresso.compressor import ModelCompressor


compressor = ModelCompressor(email="YOUR_EMAIL", password="YOUR_PASSWORD")
uploaded_models = compressor.get_uploaded_models()

Output

>>> uploaded_models
[Model(
    model_id="5eeb0edb-57d2-4a20-adf4-a6c05516015d",
    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,
)]