kevinzakka

"""
Create train, valid, test iterators for CIFAR-10 [1].
Easily extended to MNIST, CIFAR-100 and Imagenet.

[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
"""

import torch
import numpy as np

kevinzakka

import numpy as np

import torch
import torch.nn.functional as F

def rotz(theta):
    return np.array([
        [np.cos(theta), -np.sin(theta), 0],
        [np.sin(theta), np.cos(theta), 0],
        [0, 0, 1],

kevinzakka

import time
import numpy as np

from scipy.linalg import expm

def angvel2skewsym(w):
  """Converts an angular velocity to a skew-symmetric representation.
  """
  return np.array([
    [0, -w[2], w[1]],

kevinzakka

import torch
import torch.nn as nn
import torch.nn.functional as F


class SpatialSoftArgmax(nn.Module):
    """Spatial softmax as defined in [1].

    Concretely, the spatial softmax of each feature
    map is used to compute a weighted mean of the pixel