ptrblck

Deep Learning Frameworks @NVIDIA

ptrblck / weigthed_bceloss.py

Last active February 9, 2018 15:34

	import torch
	import torch.nn as nn
	from torch.autograd import Variable
	import torch.nn.functional as F
	from torch._C import _infer_size

	# Setup
	x = Variable(torch.randn(4, 2, 2))
	y = Variable(torch.Tensor(4, 2, 2).random_(2))
	output = F.sigmoid(x)

ptrblck / numpy split vs PyTorch split

Created February 19, 2018 13:45

	import torch
	import numpy as np

	# numpy
	a = np.random.rand(10, 20)
	tmp0 = np.split(a, indices_or_sections=5, axis=0) # split into 5 sections
	for t in tmp0:
	print(t.shape)

	np.split(a, indices_or_sections=7, axis=0) # error, since no equal division

ptrblck / accumulated_gradient

Last active March 28, 2018 21:20


	import torch
	import torch.nn as nn
	from torch.autograd import Variable

	# batch_size = 2
	x1 = Variable(torch.ones(2, 1))
	w1 = Variable(torch.ones(1, 1), requires_grad=True)
	y1 = Variable(torch.ones(2, 1) * 2)

ptrblck / pytorch_mnist_lbfgs

Created April 11, 2018 08:32


	#Load packages
	import torch
	import torch.nn as nn
	import torchvision.transforms as transforms
	import torchvision.datasets as dsets
	from torch.autograd import Variable
	import torch.nn.functional as F

	torch.manual_seed(2809)

ptrblck / pytorch_resume_training

Created April 12, 2018 13:40


	import torch
	import torch.nn as nn
	import torch.optim as optim
	from torch.autograd import Variable
	import torch.nn.functional as F

	import matplotlib.pyplot as plt

	import numpy as np

ptrblck / pytorch_scaling_importance

Created May 16, 2018 20:51


	import torch
	import torch.nn as nn
	import torch.optim as optim
	from torch.utils.data import Dataset, DataLoader

	class MyDataset(Dataset):
	def __init__(self, data, target):
	self.data = data
	self.target = target

ptrblck / pytorch_unet_example

Created June 6, 2018 09:31

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

	from torchvision.utils import make_grid

	import matplotlib.pyplot as plt

ptrblck / pytorch_param_update_nograd

Last active September 22, 2021 14:53

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


	use_adam = False

	class MyModel(nn.Module):
	def __init__(self):

ptrblck / pytorch_edge_weighting_segmentation

Last active February 21, 2022 12:14

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

	import matplotlib.pyplot as plt


	output = F.log_softmax(torch.randn(1, 3, 24, 24), 1)
	target = torch.zeros(1, 24, 24, dtype=torch.long)
	target[0, 4:12, 4:12] = 1

ptrblck / pytorch_conv_vs_linear

Last active January 25, 2019 14:08