boniolp / dcam Goto Github PK

from CNN_models import *
from DCAM import *
from sklearn.model_selection import train_test_split

with open("FingerMovements.pickle",'rb') as f:
    X,y = pickle.load(f)
    
# Convert the UCR-UEA format into a list of list
def generate_list_instance(x):
    res = []
    for i in range(len(x)):
        res.append(list(x[i]))
    return np.array(res)

dict_label = {}
count = 0
for val in set(y.values):
    dict_label[val] = count
    count += 1

all_class_all = []
all_label = []
for i in range(len(X)):
    all_class_all.append(generate_list_instance(X.values[i]))
    all_label.append(dict_label[y.values[i]])

original_length = len(all_class_all[0][0])
num_classes = len(set(y.values)) 
original_dim = len(all_class_all[0])
nb_instance = len(all_class_all) 

all_class, all_class_test, label, label_test = train_test_split(all_class_all, all_label,stratify=all_label, test_size=1-0.8,random_state=11081994)

# Generate C-wised input for d-based models (i.e., dCNN, dResNet, and dInceptionTime)
def gen_cube(instance):
    result = []
    for i in range(len(instance)):
        result.append([instance[(i+j)%len(instance)] for j in range(len(instance))])
    return result 

x = np.array([gen_cube(acl) for acl in all_class])
dataset_mat = TSDataset(x,label)
dataloader_cl1 = data.DataLoader(dataset_mat, batch_size=32, shuffle=True)

x = np.array([gen_cube(acl) for acl in all_class_test])
dataset_mat_test = TSDataset(x,label_test)
dataloader_cl1_test = data.DataLoader(dataset_mat_test, batch_size=1, shuffle=True)

# This is dInceptionTime
modelarch = dInceptionModel(num_blocks=3, in_channels=original_dim, out_channels=64,
                           bottleneck_channels=64, kernel_sizes=[10,20,40],
                           use_residuals=True, num_pred_classes=num_classes).to('cuda')

# dResNet gives the same error
# modelarch = dResNetBaseline(original_dim,mid_channels=128,num_pred_classes=num_classes).to(device)

model = ModelCNN(modelarch,'cuda')

model.train(num_epochs=70,dataloader_cl1=dataloader_cl1,dataloader_cl1_test=dataloader_cl1_test)