From 53a9382e1cd587477b73c2700b29049a15888579 Mon Sep 17 00:00:00 2001 From: Hunor Laczko Date: Tue, 28 Feb 2023 20:25:18 +0000 Subject: [PATCH] skin_gnn --- aaa_helpers.txt | 2 ++ configs/iccv/config_abl_skin.py | 4 ++-- cvae.py | 5 ++--- models/gnn.py | 17 ++++++++--------- 4 files changed, 14 insertions(+), 14 deletions(-) diff --git a/aaa_helpers.txt b/aaa_helpers.txt index 7e377bf..f54800b 100644 --- a/aaa_helpers.txt +++ b/aaa_helpers.txt @@ -24,6 +24,8 @@ nohup python cvae.py --name="lhunor_abl_reg" > nohup/iccv/ablation/abl_reg.out 2 nohup python cvae.py --name="lhunor_abl_off" > nohup/iccv/ablation/abl_off.out 2>&1 & nohup python cvae.py --name="lhunor_abl_skin_curv" > nohup/iccv/ablation/abl_skin_curv.out 2>&1 & +nohup python cvae.py --name="lhunor_abl_skin_gnn" > nohup/iccv/ablation/abl_skin_gnn.out 2>&1 & + nohup python upscale_test.py --name="iccv_32_2" > nohup/iccv/upscale/iccv_32_2.out 2>&1 & nohup python upscale_test.py --name="iccv_64_2" > nohup/iccv/upscale/iccv_64_2.out 2>&1 & nohup python upscale_test.py --name="iccv_128_2" > nohup/iccv/upscale/iccv_128_2.out 2>&1 & diff --git a/configs/iccv/config_abl_skin.py b/configs/iccv/config_abl_skin.py index 0530659..3ff3f3a 100644 --- a/configs/iccv/config_abl_skin.py +++ b/configs/iccv/config_abl_skin.py @@ -18,8 +18,8 @@ config['use_norm_loss'] = True ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False) assert ablation_count == 1 or ablation_count == 0 -config['gpu'] = '2' -config['name'] = 'abl_skin' +config['gpu'] = '4' +config['name'] = 'abl_skin_gnn' config['notes'] = '' config['tags'] = ['iccv', 'abl_skin'] diff --git a/cvae.py b/cvae.py index caf3f9d..5315bbd 100644 --- a/cvae.py +++ b/cvae.py @@ -1,6 +1,6 @@ import os import sys -from configs.iccv.config_abl_skin_curv import config +from configs.iccv.config_abl_skin import config os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu'] import tensorflow as tf @@ -34,7 +34,6 @@ else: from losses import edge_loss - from losses import collision_ratio, kl_loss, normal_loss #, concept_loss # from losses import collision_penalty as collision_penalty from losses import collision_loss as collision_penalty @@ -552,7 +551,7 @@ if __name__ == '__main__': train_loss = train_step(batch) train_accumulator.update(train_loss) - if step % 50 == 0: + 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) diff --git a/models/gnn.py b/models/gnn.py index ad9d495..7dc49a4 100644 --- a/models/gnn.py +++ b/models/gnn.py @@ -16,21 +16,20 @@ class Smoother(tf.keras.Model): def __init__(self, ): super().__init__() self.a = sp_matrix_to_sp_tensor(sio.loadmat("custom_utils/ssmpl0.mat")['L'].tocoo()) - self.conv1 = GeneralConv(channels=32, batch_norm=True, dropout=0.1, aggregate='mean', activation='prelu', use_bias=True) - self.conv2 = GeneralConv(channels=128, batch_norm=True, dropout=0.1, aggregate='mean', activation='prelu', use_bias=True) - self.conv3 = GeneralConv(channels=64, batch_norm=True, dropout=0.0, aggregate='mean', activation='prelu', use_bias=True) - self.conv4 = GeneralConv(channels=16, batch_norm=True, dropout=0.0, aggregate='mean', activation='prelu', use_bias=True) - - self.conv5 = GCNConv(3, activation='tanh', use_bias=False) + self.conv1 = GCNConv(16, activation='tanh', use_bias=False) + self.conv2 = GCNConv(3, activation='tanh', use_bias=False) + # self.conv3 = GCNConv(3, activation='tanh', use_bias=False) + # self.conv4 = GCNConv(3, activation='tanh', use_bias=False) + # self.conv5 = GCNConv(3, activation='tanh', use_bias=False) self.conv6 = GCNConv(3, activation='tanh', use_bias=False) def call(self, inputs, training=None): x = inputs x = self.conv1([x, self.a], training=training) x = self.conv2([x, self.a], training=training) - x = self.conv3([x, self.a], training=training) - x = self.conv4([x, self.a], training=training) - x = self.conv5([x, self.a], training=training) + # x = self.conv3([x, self.a], training=training) + # x = self.conv4([x, self.a], training=training) + # x = self.conv5([x, self.a], training=training) x = self.conv6([x, self.a], training=training) return x