13133235

diffusion.py

@@ -431,7 +431,7 @@ class DDPM21CM:
             raise ValueError(f"len(self.dataloader) % self.config.gradient_accumulation_steps = {len(self.dataloader) % self.config.gradient_accumulation_steps} instead of 0. Make sure len(dataloader)={len(self.dataloader)} is dividable by gradient_accumulation_steps={self.config.gradient_accumulation_steps}.")
 
         dataloader_end = time()
-        print(f"cuda:{torch.cuda.current_device()}/{self.config.global_rank} dataloader costs {dataloader_end-dataloader_start:.3f}s")
+        #print(f"cuda:{torch.cuda.current_device()}/{self.config.global_rank} dataloader costs {dataloader_end-dataloader_start:.3f}s")
 
         del dataset
 
@@ -489,7 +489,7 @@ class DDPM21CM:
         global_step = 0
         for ep in range(self.config.n_epoch):
             self.ddpm.train()
-            pbar_train = tqdm(total=len(self.dataloader), file=sys.stderr)#, disable=True)#, mininterval=self.config.pbar_update_step)#, disable=True)#not self.accelerator.is_local_main_process)
+            pbar_train = tqdm(total=len(self.dataloader), file=sys.stderr, disable=True)#, mininterval=self.config.pbar_update_step)#, disable=True)#not self.accelerator.is_local_main_process)
             pbar_train.set_description(f"{socket.gethostbyname(socket.gethostname())} cuda:{torch.cuda.current_device()}/{self.config.global_rank} Epoch {ep}")
             epoch_start = time()
             for i, (x, c) in enumerate(self.dataloader):

quantify_results.ipynb

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2f5c609710980f1c8798c5f4732afe3f28bce2a24799b0ef5028f1c9fef85a5d
-size 15711677
+oid sha256:4feb0d9bf444b9783c9d63200ff956c00b720a75e82a3b25597432ea88122b2a
+size 16041018

tensorboard.ipynb

@@ -23,13 +23,13 @@
      "data": {
       "text/html": [
        "\n",
-       "      <iframe id=\"tensorboard-frame-f840e130425733a4\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
+       "      <iframe id=\"tensorboard-frame-8bbb5cb424abc4b5\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
        "      </iframe>\n",
        "      <script>\n",
        "        (function() {\n",
-       "          const frame = document.getElementById(\"tensorboard-frame-f840e130425733a4\");\n",
+       "          const frame = document.getElementById(\"tensorboard-frame-8bbb5cb424abc4b5\");\n",
        "          const url = new URL(\"/\", window.location);\n",
-       "          const port = 33313;\n",
+       "          const port = 34693;\n",
        "          if (port) {\n",
        "            url.port = port;\n",
        "          }\n",
@@ -59,7 +59,7 @@
     {
      "data": {
       "text/html": [
-       "<a href=\"https://jupyter.nersc.gov/user/binxia/perlmutter-login-node-base/proxy/33313/\">https://jupyter.nersc.gov/user/binxia/perlmutter-login-node-base/proxy/33313/</a>"
+       "<a href=\"https://jupyter.nersc.gov/user/binxia/perlmutter-login-node-base/proxy/34693/\">https://jupyter.nersc.gov/user/binxia/perlmutter-login-node-base/proxy/34693/</a>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"