# coding: utf-8
# Python 2 and 3 compatibility
from __future__ import (
print_function,
absolute_import,
division,
unicode_literals,
with_statement,
)
# Make sure python version is compatible with fasttext
from cleanlab.util import VersionWarning
python_version = VersionWarning(
warning_str="fastText supports Python 3 versions (not python 2).",
list_of_compatible_versions=[3.4, 3.5, 3.6, 3.7],
)
# fasttext only exists for these versions that are also compatible with cleanlab
# if python_version.is_compatible(): # pragma: no cover
import time
import os
import copy
from sklearn.metrics import accuracy_score
import numpy as np
# You need to install fasttext using pip for this library to work
from fasttext import train_supervised, load_model
LABEL = '__label__'
NEWLINE = ' __newline__ '
#
# ## Note to use this model you'll need to have pytorch installed
# See: https://pytorch.org/get-started/locally/
# In[ ]:
# Python 2 and 3 compatibility
from __future__ import print_function, absolute_import, division, unicode_literals, with_statement
# In[ ]:
# Make sure python version is compatible with pyTorch
from cleanlab.util import VersionWarning
python_version = VersionWarning(
warning_str="pyTorch supports Python version 2.7, 3.5, 3.6, 3.7.",
list_of_compatible_versions=[2.7, 3.5, 3.6],
)
# In[ ]:
if python_version.is_compatible(): # pragma: no cover
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
from torch.autograd import Variable
from torch.utils.data.sampler import SubsetRandomSampler
import numpy as np
#!/usr/bin/env python
# coding: utf-8
# Python 2 and 3 compatibility
from __future__ import (
print_function, absolute_import, division,
unicode_literals, with_statement,
)
# Make sure python version is compatible with pyTorch
from cleanlab.util import VersionWarning
python_version = VersionWarning(
warning_str="pyTorch supports Python version 3.5, 3.6, 3.7, 3.8",
list_of_compatible_versions=[3.5, 3.6, 3.7, 3.8, ],
)
if python_version.is_compatible():
from cleanlab.models.mnist_pytorch import (
CNN, SKLEARN_DIGITS_TEST_SIZE,
SKLEARN_DIGITS_TRAIN_SIZE,
)
import cleanlab
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.datasets import load_digits
from torch import from_numpy
import pytest