0817-012224

context_unet.py

@@ -334,7 +334,7 @@ class ContextUnet(nn.Module):
             elif image_size == 128:
                 channel_mult = (1, 1, 2, 3, 4)
             elif image_size == 64:
-                channel_mult = (0.5,1,1,2,2)#(1,1,2)#(1,2)#(1,1,2,2)#(1,1,2,2,4)#(2,2,4,4,4)#(1, 2, 4)#(2,4,4,4,8)#(1, 2, 2, 4, 4)#(1, 2, 2, 4, 8)#(1, 1, 2, 2, 4, 4)#(1, 2, 4, 8, 16)#(1, 2, 3, 4)#(1, 2, 4, 6, 8)#(1, 2, 2, 4)#(1, 2, 8, 8, 8)#(1, 2, 4)#(1, 2, 2, 4)#(0.5,1,2,2,4,4)#(1, 1, 2, 2, 4, 4)#
+                channel_mult = (1,2,2,4,4)#(1,1,2,2,4)#(1,1,1,2,2)#(0.5,1,1,2,2)#(1,1,2)#(1,2)#(1,1,2,2)#(1,1,2,2,4)#(2,2,4,4,4)#(1, 2, 4)#(2,4,4,4,8)#(1, 2, 2, 4, 4)#(1, 2, 2, 4, 8)#(1, 1, 2, 2, 4, 4)#(1, 2, 4, 8, 16)#(1, 2, 3, 4)#(1, 2, 4, 6, 8)#(1, 2, 2, 4)#(1, 2, 8, 8, 8)#(1, 2, 4)#(1, 2, 2, 4)#(0.5,1,2,2,4,4)#(1, 1, 2, 2, 4, 4)#
             elif image_size == 32:
                 channel_mult = (1, 2, 2, 4)
             elif image_size == 28:

diffusion.py

@@ -269,9 +269,9 @@ class TrainConfig:
     # dim = 2
     dim = 3#2
     stride = (2,4) if dim == 2 else (2,2,2)
-    num_image = 3000#480#1200#120#3000#300#3000#6000#30#60#6000#1000#2000#20000#15000#7000#25600#3000#10000#1000#10000#5000#2560#800#2560
-    batch_size = 2#1#10#50#10#50#20#50#1#2#50#20#2#100 # 10
-    n_epoch = 40#1#50#10#1#50#1#50#5#50#5#50#100#50#100#30#120#5#4# 10#50#20#20#2#5#25 # 120
+    num_image = 2000#480#1200#120#3000#300#3000#6000#30#60#6000#1000#2000#20000#15000#7000#25600#3000#10000#1000#10000#5000#2560#800#2560
+    batch_size = 1#1#10#50#10#50#20#50#1#2#50#20#2#100 # 10
+    n_epoch = 15#1#50#10#1#50#1#50#5#50#5#50#100#50#100#30#120#5#4# 10#50#20#20#2#5#25 # 120
     HII_DIM = 64
     num_redshift = 64#256#512#256#512#256#512#256#512#64#512#64#512#64#256CUDAoom#128#64#512#128#64#512#256#256#64#512#128
     channel = 1

phoenix_diffusion.sbatch

@@ -2,7 +2,7 @@
 #SBATCH -J diffusion # Job name
 #SBATCH -A gts-jw254-coda20 
 #SBATCH -qembers
-#SBATCH -N4 --gpus-per-node=V100:1 -C V100-16GB              # Number of nodes and cores per node required
+#SBATCH -N8 --gpus-per-node=V100:1 -C V100-16GB              # Number of nodes and cores per node required
 #SBATCH --ntasks-per-node=1
 #SBATCH --mem-per-gpu=16G                        # Memory per core
 #SBATCH -t 08:00:00                                    # Duration of the job (Ex: 15 mins)
@@ -31,9 +31,9 @@ export MASTER_PORT=$MASTER_PORT
 
 srun python diffusion.py \
     --train 1 \
-    --resume outputs/model_state-N3000-device_count1-node2-epoch49-172.27.149.67 \
+    --resume outputs/model_state-N3000-device_count1-node3-epoch39-172.27.144.175 \
     --num_new_img_per_gpu 50 \
-    --max_num_img_per_gpu 5 \
+    --max_num_img_per_gpu 2 \
     --gradient_accumulation_steps 1 \
 ######################################################################################
 

quantify_results.ipynb

@@ -20,9 +20,11 @@
       "\u001b[1;31m  File \"/usr/local/pace-apps/manual/packages/anaconda3/2022.05/lib/python3.9/site-packages/notebook/notebookapp.py\", line 44, in <module>\n",
       "\u001b[1;31m\n",
       "\u001b[1;31m    from jinja2 import Environment, FileSystemLoader\n",
+      "\u001b[1;31m\n",
       "\u001b[1;31m  File \"/usr/local/pace-apps/manual/packages/anaconda3/2022.05/lib/python3.9/site-packages/jinja2/__init__.py\", line 12, in <module>\n",
       "\u001b[1;31m\n",
       "\u001b[1;31m    from .environment import Environment\n",
+      "\u001b[1;31m\n",
       "\u001b[1;31m  File \"/usr/local/pace-apps/manual/packages/anaconda3/2022.05/lib/python3.9/site-packages/jinja2/environment.py\", line 25, in <module>\n",
       "\u001b[1;31m\n",
       "\u001b[1;31m    from .defaults import BLOCK_END_STRING\n",
@@ -70,12 +72,10 @@
       "\u001b[1;31m\n",
       "\u001b[1;31m    from .defaults import BLOCK_END_STRING\n",
       "\u001b[1;31m  File \"/usr/local/pace-apps/manual/packages/anaconda3/2022.05/lib/python3.9/site-packages/jinja2/defaults.py\", line 3, in <module>\n",
-      "\u001b[1;31m\n",
       "\u001b[1;31m    from .filters import FILTERS as DEFAULT_FILTERS  # noqa: F401\n",
       "\u001b[1;31m  File \"/usr/local/pace-apps/manual/packages/anaconda3/2022.05/lib/python3.9/site-packages/jinja2/filters.py\", line 13, in <module>\n",
       "\u001b[1;31m\n",
       "\u001b[1;31m    from markupsafe import soft_unicode\n",
-      "\u001b[1;31m\n",
       "\u001b[1;31mImportError: cannot import name 'soft_unicode' from 'markupsafe' (/storage/home/hcoda1/3/bxia34/.local/lib/python3.9/site-packages/markupsafe/__init__.py). \n",
       "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
      ]
@@ -2321,7 +2321,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.12"
   }
  },
  "nbformat": 4,