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test_hashed_scenarios.py
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import numpy as np
import pytest
import os
from continuum.datasets import CIFAR10, CIFAR100, TinyImageNet200, InMemoryDataset
from continuum.scenarios import HashedScenario
from continuum.tasks import TaskType
DATA_PATH = os.environ.get("CONTINUUM_DATA_PATH")
@pytest.mark.slow
@pytest.mark.parametrize("hash_name",
["Whash",
"DhashV",
"DhashH",
"PhashSimple",
"Phash",
"AverageHash",
"ColorHash"]) # , "CropResistantHash"]) # too long CropResistantHash
@pytest.mark.parametrize(("dataset", "shape", "split_task"),
[(CIFAR10, [32, 32, 3], "auto"),
(CIFAR100, [32, 32, 3], "auto"),
(TinyImageNet200, [64, 64, 3], "auto"),
(CIFAR10, [32, 32, 3], "balanced"),
(CIFAR100, [32, 32, 3], "balanced"),
(TinyImageNet200, [64, 64, 3], "balanced")])
def test_visualization_HashedScenario(hash_name, dataset, shape, split_task):
if split_task == "balanced":
num_tasks = 5
else:
num_tasks = None
dataset = dataset(data_path=DATA_PATH, download=False, train=True)
scenario = HashedScenario(cl_dataset=dataset,
hash_name=hash_name,
nb_tasks=num_tasks,
split_task=split_task)
assert scenario.nb_tasks > 1
folder = "tests/samples/hashed_scenario/"
if not os.path.exists(folder):
os.makedirs(folder)
# test default parameters
for task_id, taskset in enumerate(scenario):
taskset.plot(path=folder,
title="{}_HashedScenario_{}_{}_{}.jpg".format(split_task,
type(dataset).__name__,
hash_name,
task_id),
nb_samples=100,
shape=shape)
def numpy_data():
x_train = []
y_train = []
for i in range(10):
x_train.append(np.random.randn(5, 10, 10, 3))
y_train.append(np.ones(5) * i)
x_train = np.concatenate(x_train)
y_train = np.concatenate(y_train)
return (x_train, y_train.astype(int))
@pytest.mark.parametrize("hash_name",
["Whash",
"DhashV",
"DhashH",
"PhashSimple",
"Phash",
"AverageHash",
"ColorHash"]) # , "CropResistantHash"
def test_HashedScenario_save_indexes(tmpdir, hash_name):
num_tasks = 2
x, y = numpy_data()
dataset = InMemoryDataset(x, y, None, data_type=TaskType.IMAGE_ARRAY)
filename_indexes = os.path.join(tmpdir, f"{hash_name}.npy")
if os.path.exists(filename_indexes):
os.remove(filename_indexes)
if os.path.exists(filename_indexes):
AssertionError(f"{filename_indexes} should have been delete.")
# test save the indexes array
scenario = HashedScenario(cl_dataset=dataset,
hash_name=hash_name,
nb_tasks=num_tasks,
filename_hash_indexes=filename_indexes)
# test load the indexes array
scenario = HashedScenario(cl_dataset=dataset,
hash_name=hash_name,
nb_tasks=num_tasks,
filename_hash_indexes=filename_indexes)
# delete test indexes
os.remove(filename_indexes)
@pytest.mark.parametrize("hash_name",
["Whash",
"DhashV",
"DhashH",
"PhashSimple",
"Phash",
"AverageHash",
"ColorHash"]) # , "CropResistantHash"
def test_HashedScenario_automatic_task_number(hash_name):
x, y = numpy_data()
dataset = InMemoryDataset(x, y, None, data_type=TaskType.IMAGE_ARRAY)
# test when nb_tasks is set to None
scenario = HashedScenario(cl_dataset=dataset,
hash_name=hash_name,
nb_tasks=None,
split_task="auto")
if scenario.nb_tasks is None or scenario.nb_tasks < 2:
AssertionError("nb_tasks should have been set automatically to more than one")