Dear Concern,
Recently I have been trying to build an inception model. But it gives this error. Can anyone give me a solution? I really appreciate any help you can provide.
training_data = []
def create_training_data():
for category in CATEGORIES_Train: # do dogs and cats
path = os.path.join(DATADIR_Train,category) # create path attack
class_num = CATEGORIES_Train.index(category) # get the classification (0, 1,.... ).
for img in tqdm(os.listdir(path)): # iterate over each image
try:
img_array = cv2.imread(os.path.join(path,img)) # convert to array
new_array = cv2.resize(img_array, (100, 100)) # resize to normalize data size
new_array = np.transpose(new_array, (2, 0, 1))
training_data.append([new_array, class_num]) # add this to our training_data
except Exception as e: # in the interest in keeping the output clean...
pass
#except OSError as e:
# print("OSErrroBad img most likely", e, os.path.join(path,img))
#except Exception as e:
# print("general exception", e, os.path.join(path,img))
create_training_data()
print(len(training_data))
#############################################################
TRAIN_BATCH_SIZE = 64
VALID_BATCH_SIZE = 32
NUM_EPOCHS = 10
LEARNING_RATE = 1e-3
NUM_WORKERS = 0
PIN_MEMORY = False
train_loader = torch.utils.data.DataLoader(training_data, batch_size=TRAIN_BATCH_SIZE, shuffle=True, num_workers=NUM_WORKERS, pin_memory=PIN_MEMORY)
valid_loader = torch.utils.data.DataLoader(testing_data, batch_size=VALID_BATCH_SIZE, shuffle=True, num_workers=NUM_WORKERS, pin_memory=PIN_MEMORY)
model = InceptionV3().to(device)
start = time.time()
fit(model, train_loader, valid_loader, learning_rate=LEARNING_RATE, num_epochs=NUM_EPOCHS)
print(f'Total training time: {time.time() - start}')
model.load_state_dict(torch.load('Inception_Adam_T_Tesla_1.pth'))