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more training

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luni
2023-02-28 22:03:08 +00:00
parent 4c6497f726
commit 35ba014ba5
13 changed files with 347 additions and 24 deletions
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auto_encoder_curv.py
+7 -6
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@@ -1,6 +1,6 @@
import os
import sys
from configs.iccv.config_ae_curv_cape_m import config
from configs.iccv.config_ae_curv_25p import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
@@ -169,12 +169,13 @@ def train():
train_loss = train_step(batch)
train_accumulator.update(train_loss)
data_valid = valid_iterator.get_next()
data_valid = static_dataset_valid.expand_batch(batch_to_dict(data_valid, config['signature_dynamic']))
valid_loss = valid_step(data_valid)
valid_accumulator.update(valid_loss)
if step % 25 == 0:
data_valid = valid_iterator.get_next()
data_valid = static_dataset_valid.expand_batch(batch_to_dict(data_valid, config['signature_dynamic']))
valid_loss = valid_step(data_valid)
valid_accumulator.update(valid_loss)
if step % 1000 == 0 or (step < 1000 and step % 10 == 0):
if step % 1000 == 0 or (step < 1000 and step % 100 == 0):
to_log = dict({ **train_loss, **valid_loss, **{ 'current_step': step } })
if step % 5000 == 0 or (step < 5000 and step % 1000 == 0):
train_figs = plot_everything(batch, 'train')