Write tensorboard events with simple command.
including scalar, image, histogram, audio, text, graph and embedding.
see demo (result of demo.py and some images generated by BEGAN)
#tested on anaconda2/anaconda3, pytorch 0.2, torchvision 0.1.9
pip install tensorboard-pytorch
pip install tensorflow-tensorboard (for tensorboard web server)
or build from source:
pip install git+https://github.com/lanpa/tensorboard-pytorch
http://tensorboard-pytorch.readthedocs.io/en/latest/tensorboard.html
import torch
import torchvision.utils as vutils
import numpy as np
import torchvision.models as models
from torchvision import datasets
from tensorboard import SummaryWriter
# if error, uninstall tensorboard-pytorch and install tensorboardX
# then use: from tensorboardX import SummaryWriter see:#20
resnet18 = models.resnet18(False)
writer = SummaryWriter()
sample_rate = 44100
freqs = [262, 294, 330, 349, 392, 440, 440, 440, 440, 440, 440]
for n_iter in range(100):
s1 = torch.rand(1) # value to keep
s2 = torch.rand(1)
writer.add_scalar('data/scalar1', s1[0], n_iter) #data grouping by `slash`
writer.add_scalar('data/scalar2', s2[0], n_iter)
x = torch.rand(32, 3, 64, 64) # output from network
if n_iter%10==0:
x = vutils.make_grid(x, normalize=True, scale_each=True)
writer.add_image('Image', x, n_iter)
x = torch.zeros(sample_rate*2)
for i in range(x.size(0)):
x[i] = np.cos(freqs[n_iter//10]*np.pi*float(i)/float(sample_rate)) # sound amplitude should in [-1, 1]
writer.add_audio('myAudio', x, n_iter)
writer.add_text('Text', 'text logged at step:'+str(n_iter), n_iter)
for name, param in resnet18.named_parameters():
writer.add_histogram(name, param.clone().cpu().data.numpy(), n_iter)
dataset = datasets.MNIST('mnist', train=False, download=True)
images = dataset.test_data[:100].float()
label = dataset.test_labels[:100]
features = images.view(100, 784)
writer.add_embedding(features, metadata=label, label_img=images.unsqueeze(1))
writer.close()python demo.py
tensorboard --logdir runs
To show more images in tensorboard's image tab, just
modify the hardcoded event_accumulator in
~/anaconda3/lib/python3.6/site-packages/tensorflow/tensorboard/backend/application.py
as you wish.
audio sample rate