"git@developer.sourcefind.cn:OpenDAS/vision.git" did not exist on "dcfd26e834a4f20269598f0609ce636530ec3fb9"
Unverified Commit 15ace31a authored by Songqing Zhang's avatar Songqing Zhang Committed by GitHub
Browse files

[Misc] Using the aliases of builtin types like np.int is deprecated (#7300)

parent 2ff3006c
...@@ -60,7 +60,7 @@ def main(args): ...@@ -60,7 +60,7 @@ def main(args):
labels = labels.data.numpy().tolist() labels = labels.data.numpy().tolist()
dev_preds += preds dev_preds += preds
dev_labels += labels dev_labels += labels
acc = np.equal(dev_labels, dev_preds).astype(np.float).tolist() acc = np.equal(dev_labels, dev_preds).astype(float).tolist()
acc = sum(acc) / len(acc) acc = sum(acc) / len(acc)
print(f"Epoch {epoch}, Dev acc {acc}") print(f"Epoch {epoch}, Dev acc {acc}")
...@@ -80,7 +80,7 @@ def main(args): ...@@ -80,7 +80,7 @@ def main(args):
labels = labels.data.numpy().tolist() labels = labels.data.numpy().tolist()
test_preds += preds test_preds += preds
test_labels += labels test_labels += labels
acc = np.equal(test_labels, test_preds).astype(np.float).tolist() acc = np.equal(test_labels, test_preds).astype(float).tolist()
acc = sum(acc) / len(acc) acc = sum(acc) / len(acc)
test_acc_list.append(acc) test_acc_list.append(acc)
......
...@@ -40,7 +40,7 @@ def evaluate(gt_labels, pred_labels, metric="pairwise"): ...@@ -40,7 +40,7 @@ def evaluate(gt_labels, pred_labels, metric="pairwise"):
"evaluate with {}{}{}".format(TextColors.FATAL, metric, TextColors.ENDC) "evaluate with {}{}{}".format(TextColors.FATAL, metric, TextColors.ENDC)
): ):
result = metric_func(gt_labels, pred_labels) result = metric_func(gt_labels, pred_labels)
if isinstance(result, np.float): if isinstance(result, float):
print( print(
"{}{}: {:.4f}{}".format( "{}{}: {:.4f}{}".format(
TextColors.OKGREEN, metric, result, TextColors.ENDC TextColors.OKGREEN, metric, result, TextColors.ENDC
......
...@@ -68,7 +68,7 @@ def process(dataset): ...@@ -68,7 +68,7 @@ def process(dataset):
for attr in re.split("[,\s]+", line.strip("\s\n")) for attr in re.split("[,\s]+", line.strip("\s\n"))
if attr if attr
], ],
dtype=np.float, dtype=float,
) )
) )
else: else:
...@@ -130,7 +130,7 @@ def process(dataset): ...@@ -130,7 +130,7 @@ def process(dataset):
f[graph.degree[u[0]]] = 1.0 f[graph.degree[u[0]]] = 1.0
if "label" in u[1]: if "label" in u[1]:
f = np.concatenate( f = np.concatenate(
(np.array(u[1]["label"], dtype=np.float), f) (np.array(u[1]["label"], dtype=float), f)
) )
graph.nodes[u[0]]["feat"] = f graph.nodes[u[0]]["feat"] = f
return graphs, pprs return graphs, pprs
......
...@@ -213,13 +213,13 @@ class DeepwalkDataset: ...@@ -213,13 +213,13 @@ class DeepwalkDataset:
node_degree = self.G.out_degrees(self.valid_seeds).numpy() node_degree = self.G.out_degrees(self.valid_seeds).numpy()
node_degree = np.power(node_degree, 0.75) node_degree = np.power(node_degree, 0.75)
node_degree /= np.sum(node_degree) node_degree /= np.sum(node_degree)
node_degree = np.array(node_degree * 1e8, dtype=np.int) node_degree = np.array(node_degree * 1e8, dtype=int)
self.neg_table = [] self.neg_table = []
for idx, node in enumerate(self.valid_seeds): for idx, node in enumerate(self.valid_seeds):
self.neg_table += [node] * node_degree[idx] self.neg_table += [node] * node_degree[idx]
self.neg_table_size = len(self.neg_table) self.neg_table_size = len(self.neg_table)
self.neg_table = np.array(self.neg_table, dtype=np.long) self.neg_table = np.array(self.neg_table, dtype=int)
del node_degree del node_degree
def create_sampler(self, i): def create_sampler(self, i):
......
...@@ -209,13 +209,13 @@ class LineDataset: ...@@ -209,13 +209,13 @@ class LineDataset:
node_degree = self.G.out_degrees(self.valid_nodes).numpy() node_degree = self.G.out_degrees(self.valid_nodes).numpy()
node_degree = np.power(node_degree, 0.75) node_degree = np.power(node_degree, 0.75)
node_degree /= np.sum(node_degree) node_degree /= np.sum(node_degree)
node_degree = np.array(node_degree * 1e8, dtype=np.int) node_degree = np.array(node_degree * 1e8, dtype=int)
self.neg_table = [] self.neg_table = []
for idx, node in enumerate(self.valid_nodes): for idx, node in enumerate(self.valid_nodes):
self.neg_table += [node] * node_degree[idx] self.neg_table += [node] * node_degree[idx]
self.neg_table_size = len(self.neg_table) self.neg_table_size = len(self.neg_table)
self.neg_table = np.array(self.neg_table, dtype=np.long) self.neg_table = np.array(self.neg_table, dtype=int)
del node_degree del node_degree
def create_sampler(self, i): def create_sampler(self, i):
......
...@@ -132,7 +132,7 @@ class ShapeNetDataset(Dataset): ...@@ -132,7 +132,7 @@ class ShapeNetDataset(Dataset):
[t.split("\n")[0].split(" ") for t in f.readlines()] [t.split("\n")[0].split(" ") for t in f.readlines()]
).astype(np.float) ).astype(np.float)
data_list.append(data[:, 0 : self.dim]) data_list.append(data[:, 0 : self.dim])
label_list.append(data[:, 6].astype(np.int)) label_list.append(data[:, 6].astype(int))
category_list.append(shapenet.synset_dict[fn.split("/")[-2]]) category_list.append(shapenet.synset_dict[fn.split("/")[-2]])
self.data = data_list self.data = data_list
self.label = label_list self.label = label_list
...@@ -157,5 +157,5 @@ class ShapeNetDataset(Dataset): ...@@ -157,5 +157,5 @@ class ShapeNetDataset(Dataset):
if self.mode == "train": if self.mode == "train":
x = self.translate(x, size=self.dim) x = self.translate(x, size=self.dim)
x = x.astype(np.float) x = x.astype(np.float)
y = y.astype(np.int) y = y.astype(int)
return x, y, cat return x, y, cat
...@@ -130,9 +130,9 @@ class ShapeNetDataset(Dataset): ...@@ -130,9 +130,9 @@ class ShapeNetDataset(Dataset):
with open(fn) as f: with open(fn) as f:
data = np.array( data = np.array(
[t.split("\n")[0].split(" ") for t in f.readlines()] [t.split("\n")[0].split(" ") for t in f.readlines()]
).astype(np.float) ).astype(float)
data_list.append(data[:, 0 : self.dim]) data_list.append(data[:, 0 : self.dim])
label_list.append(data[:, 6].astype(np.int)) label_list.append(data[:, 6].astype(int))
category_list.append(shapenet.synset_dict[fn.split("/")[-2]]) category_list.append(shapenet.synset_dict[fn.split("/")[-2]])
self.data = data_list self.data = data_list
self.label = label_list self.label = label_list
...@@ -156,6 +156,6 @@ class ShapeNetDataset(Dataset): ...@@ -156,6 +156,6 @@ class ShapeNetDataset(Dataset):
cat = self.category[i] cat = self.category[i]
if self.mode == "train": if self.mode == "train":
x = self.translate(x, size=self.dim) x = self.translate(x, size=self.dim)
x = x.astype(np.float) x = x.astype(float)
y = y.astype(np.int) y = y.astype(int)
return x, y, cat return x, y, cat
...@@ -130,9 +130,9 @@ class ShapeNetDataset(Dataset): ...@@ -130,9 +130,9 @@ class ShapeNetDataset(Dataset):
with open(fn) as f: with open(fn) as f:
data = np.array( data = np.array(
[t.split("\n")[0].split(" ") for t in f.readlines()] [t.split("\n")[0].split(" ") for t in f.readlines()]
).astype(np.float) ).astype(float)
data_list.append(data[:, 0 : self.dim]) data_list.append(data[:, 0 : self.dim])
label_list.append(data[:, 6].astype(np.int)) label_list.append(data[:, 6].astype(int))
category_list.append(shapenet.synset_dict[fn.split("/")[-2]]) category_list.append(shapenet.synset_dict[fn.split("/")[-2]])
self.data = data_list self.data = data_list
self.label = label_list self.label = label_list
...@@ -156,6 +156,6 @@ class ShapeNetDataset(Dataset): ...@@ -156,6 +156,6 @@ class ShapeNetDataset(Dataset):
cat = self.category[i] cat = self.category[i]
if self.mode == "train": if self.mode == "train":
x = self.translate(x, size=self.dim) x = self.translate(x, size=self.dim)
x = x.astype(np.float) x = x.astype(float)
y = y.astype(np.int) y = y.astype(int)
return x, y, cat return x, y, cat
...@@ -13,7 +13,7 @@ def solve_sudoku(puzzle): ...@@ -13,7 +13,7 @@ def solve_sudoku(puzzle):
:param puzzle: an array-like data with shape [9, 9], blank positions are filled with 0 :param puzzle: an array-like data with shape [9, 9], blank positions are filled with 0
:return: a [9, 9] shaped numpy array :return: a [9, 9] shaped numpy array
""" """
puzzle = np.array(puzzle, dtype=np.long).reshape([-1]) puzzle = np.array(puzzle, dtype=int).reshape([-1])
model_path = "ckpt" model_path = "ckpt"
if not os.path.exists(model_path): if not os.path.exists(model_path):
os.mkdir(model_path) os.mkdir(model_path)
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment