Update bytes to GB with bitshift (#6886)

utils/__init__.py

@@ -21,14 +21,13 @@ def notebook_init(verbose=True):
     if is_colab():
         shutil.rmtree('/content/sample_data', ignore_errors=True)  # remove colab /sample_data directory
 
+    # System info
     if verbose:
-        # System info
-        # gb = 1 / 1000 ** 3  # bytes to GB
-        gib = 1 / 1024 ** 3  # bytes to GiB
+        gb = 1 << 30  # bytes to GiB (1024 ** 3)
         ram = psutil.virtual_memory().total
         total, used, free = shutil.disk_usage("/")
         display.clear_output()
-        s = f'({os.cpu_count()} CPUs, {ram * gib:.1f} GB RAM, {(total - free) * gib:.1f}/{total * gib:.1f} GB disk)'
+        s = f'({os.cpu_count()} CPUs, {ram / gb:.1f} GB RAM, {(total - free) / gb:.1f}/{total / gb:.1f} GB disk)'
     else:
         s = ''
 

utils/autobatch.py

@@ -34,11 +34,12 @@ def autobatch(model, imgsz=640, fraction=0.9, batch_size=16):
         LOGGER.info(f'{prefix}CUDA not detected, using default CPU batch-size {batch_size}')
         return batch_size
 
+    gb = 1 << 30  # bytes to GiB (1024 ** 3)
     d = str(device).upper()  # 'CUDA:0'
     properties = torch.cuda.get_device_properties(device)  # device properties
-    t = properties.total_memory / 1024 ** 3  # (GiB)
-    r = torch.cuda.memory_reserved(device) / 1024 ** 3  # (GiB)
-    a = torch.cuda.memory_allocated(device) / 1024 ** 3  # (GiB)
+    t = properties.total_memory / gb  # (GiB)
+    r = torch.cuda.memory_reserved(device) / gb  # (GiB)
+    a = torch.cuda.memory_allocated(device) / gb  # (GiB)
     f = t - (r + a)  # free inside reserved
     LOGGER.info(f'{prefix}{d} ({properties.name}) {t:.2f}G total, {r:.2f}G reserved, {a:.2f}G allocated, {f:.2f}G free')
 

utils/general.py

@@ -223,11 +223,12 @@ def emojis(str=''):
 
 def file_size(path):
     # Return file/dir size (MB)
+    mb = 1 << 20  # bytes to MiB (1024 ** 2)
     path = Path(path)
     if path.is_file():
-        return path.stat().st_size / 1E6
+        return path.stat().st_size / mb
     elif path.is_dir():
-        return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / 1E6
+        return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / mb
     else:
         return 0.0
 

utils/torch_utils.py

@@ -86,7 +86,7 @@ def select_device(device='', batch_size=0, newline=True):
         space = ' ' * (len(s) + 1)
         for i, d in enumerate(devices):
             p = torch.cuda.get_device_properties(i)
-            s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / 1024 ** 2:.0f}MiB)\n"  # bytes to MB
+            s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / (1 << 20):.0f}MiB)\n"  # bytes to MB
     else:
         s += 'CPU\n'