logging

Author: sebffischer

paper/benchmark/linux-cpu.R

@@ -55,6 +55,7 @@ addExperiments(
 tbl = unwrap(getJobTable())
 
 for (id in sample(tbl$job.id)) {
+  print(tbl[job.id == id, ])
   submitJobs(id)
   Sys.sleep(0.1)
 }

paper/benchmark/linux-gpu-optimizer.R

@@ -52,6 +52,7 @@ addExperiments(
 tbl = unwrap(getJobTable())
 
 for (id in sample(tbl$job.id)) {
+  print(tbl[job.id == id, ])
   submitJobs(id)
   Sys.sleep(0.1)
 }

paper/benchmark/linux-gpu.R

@@ -59,6 +59,7 @@ addExperiments(
 tbl = unwrap(getJobTable())
 
 for (id in sample(tbl$job.id)) {
+  print(tbl[job.id == id, ])
   submitJobs(id)
   Sys.sleep(0.1)
 }

paper/benchmark/time_pytorch.py

@@ -6,17 +6,6 @@
 
 # 3. Define the timing function
 def time_pytorch(epochs, batch_size, n_layers, latent, n, p, device, seed, optimizer, jit):
-    print(f"epochs: {epochs}")
-    print(f"batch_size: {batch_size}")
-    print(f"n_layers: {n_layers}")
-    print(f"latent: {latent}")
-    print(f"n: {n}")
-    print(f"p: {p}")
-    print(f"device: {device}")
-    print(f"seed: {seed}")
-    print(f"optimizer: {optimizer}")
-    print(f"jit: {jit}")
-
     torch.manual_seed(seed)
     torch.set_num_threads(1)
     # convert latentn, n_layers to int

paper/benchmark/time_rtorch.R

@@ -4,18 +4,6 @@ time_rtorch = function(epochs, batch_size, n_layers, latent, n, p, device, jit,
   torch_set_num_threads(1)
   torch_manual_seed(seed)
 
-  cat("epochs: ", epochs, "\n")
-  cat("batch_size: ", batch_size, "\n")
-  cat("n_layers: ", n_layers, "\n")
-  cat("latent: ", latent, "\n")
-  cat("n: ", n, "\n")
-  cat("p: ", p, "\n")
-  cat("device: ", device, "\n")
-  cat("jit: ", jit, "\n")
-  cat("seed: ", seed, "\n")
-  cat("optimizer: ", optimizer, "\n")
-  cat("mlr3torch: ", mlr3torch, "\n")
-
   lr = 0.0001
 
   make_network = function(p, latent, n_layers) {