Fix a issue (Swall0w#6)

Author: lyakaap

torchstat/compute_memory.py

@@ -18,7 +18,7 @@ def compute_memory(module, inp, out):
         return compute_Pool2d_memory(module, inp, out)
     else:
         print(f"[Memory]: {type(module).__name__} is not supported!")
-        return (0, 0)
+        return 0, 0
     pass
 
 
@@ -28,20 +28,21 @@ def num_params(module):
 
 def compute_ReLU_memory(module, inp, out):
     assert isinstance(module, (nn.ReLU, nn.ReLU6, nn.ELU, nn.LeakyReLU))
-    batch_size = inp.size()[0]
-    mread = batch_size * inp.size()[1:].numel()
-    mwrite = batch_size * inp.size()[1:].numel()
-
-    return (mread, mwrite)
+    
+    mread = inp.numel()
+    mwrite = out.numel()
+    
+    return mread, mwrite
 
 
 def compute_PReLU_memory(module, inp, out):
-    assert isinstance(module, (nn.PReLU))
+    assert isinstance(module, nn.PReLU)
+    
     batch_size = inp.size()[0]
-    mread = batch_size * (inp.size()[1:].numel() + num_params(module))
-    mwrite = batch_size * inp.size()[1:].numel()
+    mread = batch_size * (inp[0].numel() + num_params(module))
+    mwrite = out.numel()
 
-    return (mread, mwrite)
+    return mread, mwrite
 
 
 def compute_Conv2d_memory(module, inp, out):
@@ -50,39 +51,42 @@ def compute_Conv2d_memory(module, inp, out):
     assert len(inp.size()) == 4 and len(inp.size()) == len(out.size())
 
     batch_size = inp.size()[0]
-    in_c = inp.size()[1]
-    out_c, out_h, out_w = out.size()[1:]
 
-    # This includes weighs with bias if the module contains it.
-    mread = batch_size * (inp.size()[1:].numel() + num_params(module))
-    mwrite = batch_size * out_c * out_h * out_w
-    return (mread, mwrite)
+    # This includes weights with bias if the module contains it.
+    mread = batch_size * (inp[0].numel() + num_params(module))
+    mwrite = out.numel()
+    return mread, mwrite
 
 
 def compute_BatchNorm2d_memory(module, inp, out):
     assert isinstance(module, nn.BatchNorm2d)
     assert len(inp.size()) == 4 and len(inp.size()) == len(out.size())
+   
     batch_size, in_c, in_h, in_w = inp.size()
-
-    mread = batch_size * (inp.size()[1:].numel() + 2 * in_c)
-    mwrite = inp.size().numel()
-    return (mread, mwrite)
+    mread = batch_size * (inp[0].numel() + 2 * in_c)
+    mwrite = out.numel()
+    
+    return mread, mwrite
 
 
 def compute_Linear_memory(module, inp, out):
     assert isinstance(module, nn.Linear)
     assert len(inp.size()) == 2 and len(out.size()) == 2
+    
     batch_size = inp.size()[0]
-    mread = batch_size * (inp.size()[1:].numel() + num_params(module))
-    mwrite = out.size().numel()
 
-    return (mread, mwrite)
+    # This includes weights with bias if the module contains it.
+    mread = batch_size * (inp[0].numel() + num_params(module))
+    mwrite = out.numel()
+
+    return mread, mwrite
 
 
 def compute_Pool2d_memory(module, inp, out):
     assert isinstance(module, (nn.MaxPool2d, nn.AvgPool2d))
     assert len(inp.size()) == 4 and len(inp.size()) == len(out.size())
-    batch_size = inp.size()[0]
-    mread = batch_size * inp.size()[1:].numel()
-    mwrite = batch_size * out.size()[1:].numel()
-    return (mread, mwrite)
+    
+    mread = inp.numel()
+    mwrite = out.numel()
+    
+    return mread, mwrite