import os
def make_tsv(metadata, save_path, metadata_header=None):
if not metadata_header:
metadata = [str(x) for x in metadata]
else:
assert len(metadata_header) == len(metadata[0]), \
'len of header must be equal to the number of columns in metadata'
metadata = ['\t'.join(str(e) for e in l)
for l in [metadata_header] + metadata]
with open(os.path.join(save_path, 'metadata.tsv'), 'w') as f:
for x in metadata:
f.write(x + '\n')
# https://github.com/tensorflow/tensorboard/issues/44 image label will be squared
def make_sprite(label_img, save_path):
import math
import torch
import torchvision
from .x2num import make_np
# this ensures the sprite image has correct dimension as described in
# https://www.tensorflow.org/get_started/embedding_viz
nrow = int(math.ceil((label_img.size(0)) ** 0.5))
label_img = torch.from_numpy(make_np(label_img)) # for other framework
# augment images so that #images equals nrow*nrow
label_img = torch.cat((label_img, torch.randn(
nrow ** 2 - label_img.size(0), *label_img.size()[1:]) * 255), 0)
torchvision.utils.save_image(label_img, os.path.join(
save_path, 'sprite.png'), nrow=nrow, padding=0)
def append_pbtxt(metadata, label_img, save_path, subdir, global_step, tag):
from posixpath import join
with open(os.path.join(save_path, 'projector_config.pbtxt'), 'a') as f:
# step = os.path.split(save_path)[-1]
f.write('embeddings {\n')
f.write('tensor_name: "{}:{}"\n'.format(
tag, str(global_step).zfill(5)))
f.write('tensor_path: "{}"\n'.format(join(subdir, 'tensors.tsv')))
if metadata is not None:
f.write('metadata_path: "{}"\n'.format(
join(subdir, 'metadata.tsv')))
if label_img is not None:
f.write('sprite {\n')
f.write('image_path: "{}"\n'.format(join(subdir, 'sprite.png')))
f.write('single_image_dim: {}\n'.format(label_img.size(3)))
f.write('single_image_dim: {}\n'.format(label_img.size(2)))
f.write('}\n')
f.write('}\n')
def make_mat(matlist, save_path):
with open(os.path.join(save_path, 'tensors.tsv'), 'w') as f:
for x in matlist:
x = [str(i.item()) for i in x]
f.write('\t'.join(x) + '\n')