import torch
from dnn_cool.synthetic_dataset import synthenic_dataset_preparation
from dnn_cool.task_flow import BinaryClassificationTask
from torch import nn


def test_repr_binary_task():
    task = BinaryClassificationTask(name='is_car', labels=torch.ones(24),
        module=nn.Linear(256, 1))
    print(task)


def test_repr_flow():
    model, nested_loaders, datasets, project = synthenic_dataset_preparation()
    flow = project.get_full_flow()
    print(flow)

437b4ff95d966057673b325de332c1bd4c8a60dd
<mask token>

<mask token>


def test_repr_flow():
    model, nested_loaders, datasets, project = synthenic_dataset_preparation()
    flow = project.get_full_flow()
    print(flow)

<mask token>


def test_repr_binary_task():
    task = BinaryClassificationTask(name='is_car', labels=torch.ones(24),
        module=nn.Linear(256, 1))
    print(task)


def test_repr_flow():
    model, nested_loaders, datasets, project = synthenic_dataset_preparation()
    flow = project.get_full_flow()
    print(flow)

import torch
from dnn_cool.synthetic_dataset import synthenic_dataset_preparation
from dnn_cool.task_flow import BinaryClassificationTask
from torch import nn


def test_repr_binary_task():
    task = BinaryClassificationTask(name='is_car', labels=torch.ones(24),
        module=nn.Linear(256, 1))
    print(task)


def test_repr_flow():
    model, nested_loaders, datasets, project = synthenic_dataset_preparation()
    flow = project.get_full_flow()
    print(flow)
