def test_which_processor():
# Naive test: Just run the function to see whether it works or does not work
which_processor()
ClassificationInterpretation,
to_np,
)
from fastai.metrics import accuracy
import fastai
from pathlib import Path
import numpy as np
import sys
# fastai and torch
# local modules
print(f"Fast.ai version = {fastai.__version__}")
which_processor()
EPOCHS = 10
LEARNING_RATE = 1e-4
IM_SIZE = 300
BATCH_SIZE = 16
ARCHITECTURE = models.resnet18
path = Path('/app/classifier_data/')
data = (ImageList.from_folder(path).split_by_rand_pct(
valid_pct=0.2,
seed=10).label_from_folder().transform(size=IM_SIZE).databunch(
bs=BATCH_SIZE, num_workers=db_num_workers()).normalize(imagenet_stats))
print(f'number of classes: {data.c}')