code stringlengths 3 6.57k |
|---|
asp_file.write("os_needed("+job+", ubuntu_DE) |
asp_file.write("os_needed("+job+", centOS_7_DE) |
asp_file.write("os_needed("+job+", centOS_7_NE) |
asp_file.write("os_needed("+job+", debian) |
asp_file.write("os_needed("+job+", red_hat) |
asp_file.write("-os_needed("+job+") |
asp_file.write("% Here the OS of each machine in the cluster is represented in the model.\n") |
range(len(all_macs) |
mac.replace(" ", "") |
mac.lower() |
asp_file.write("os_on("+mac+", ubuntu_DE) |
asp_file.write("os_on("+mac+", centOS_7_DE) |
asp_file.write("os_on("+mac+", centOS_7_NE) |
asp_file.write("os_on("+mac+", debian) |
asp_file.write("os_on("+mac+") |
asp_file.write("% The thread_cost() |
range(len(all_jobs) |
job.replace(" ", "") |
job.replace(".", "_") |
job.lower() |
str(all_jobs[i][4]) |
asp_file.write("thread_cost("+job+", "+thread+") |
asp_file.write("% The depends_on(X1, X2) |
range(len(all_jobs) |
job0.replace(" ", "") |
job0.replace(".", "_") |
job0.lower() |
range(len(all_jobs[i][2]) |
job1.replace(" ", "") |
job1.replace(".", "_") |
job1.lower() |
depended_on.append(job1) |
asp_file.write("depends_on("+job0+", "+job1+") |
range(len(all_tasks) |
range(len(depended_on) |
range(len(all_tasks) |
asp_file.write("nobody_depends_on("+all_tasks[k]+") |
asp_file.write("% The machine_threads() |
range(len(all_macs) |
mac.replace(" ", "") |
mac.lower() |
str(all_macs[i][6]) |
asp_file.write("machine_threads("+mac+", "+thread+") |
asp_file.write("% Initialization of the statuses of all tasks.\n") |
range(len(all_jobs) |
job.replace(" ", "") |
job.replace(".", "_") |
job.lower() |
asp_file.write("init(on("+job+", home) |
asp_file.write("init(at("+job+", -done) |
asp_file.write("% Declartion of the goals of the system.\n") |
range(len(all_jobs) |
job.replace(" ", "") |
job.replace(".", "_") |
job.lower() |
asp_file.write("goal(at("+job+", done) |
asp_file.close() |
Copyright (c) |
DataSeg(DLBase) |
os.path.expanduser('./data') |
super(DataSeg, self) |
__init__() |
self._init_palette(self.cfg.DATASET.NUM_CLASSES) |
os.path.join(self.root, self.split + ".txt") |
os.path.isfile(split_fn) |
add_sequence(name) |
len(self.images) |
self.sequence_ids.append(vlen) |
self.sequence_names.append(name) |
open(split_fn, "r") |
line.strip("\n") |
split(' ') |
self.flags.append(int(_flag) |
os.path.join(cfg.DATASET.ROOT, _image.lstrip('/') |
os.path.isfile(_image) |
_image.split("/") |
os.path.basename(_image) |
split("_") |
add_sequence(token) |
self.images.append(_image) |
self.masks.append(None) |
os.path.join(cfg.DATASET.ROOT, _mask.lstrip('/') |
os.path.isfile(_mask) |
self.masks.append(_mask) |
add_sequence(token) |
print("Loaded {} sequences".format(len(self.sequence_ids) |
print("Dataloader: {}".format(split) |
len(self.images) |
print("\t {}: no augmentation".format(split) |
tf.Compose([tf.ToTensor() |
tf.Normalize(mean=self.MEAN, std=self.STD) |
len(self.images) |
__len__(self) |
len(self.sequence_ids) |
_mask2tensor(self, mask, num_classes=6) |
torch.ones(1,h,w) |
torch.zeros(num_classes,h,w) |
mask.max() |
format(max_idx, num_classes) |
zeros.scatter(0, mask[None, ...], ones) |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.