import numpy as np
import re
-
import torch
import torch.nn as nn
import torchvision.datasets as dsets
for name in list_vars.keys():
data = list_vars[name].squeeze().numpy()
- print("Processing variable: " + name + " with shape: ", data.shape)
+ print("Processing variable: " + name + " with shape: ", data.shape)
n_dims = len(data.shape);
-
+
fout.write(struct.pack("i", n_dims))
-
+
data = data.astype(np.float32)
for i in range(n_dims):
fout.write(struct.pack("i", data.shape[n_dims - 1 - i]))