jesuscast · October 16, 2017 05:08 · Oct 16, 2017 · Oct 16, 2017 · Oct 16, 2017 · Oct 16, 2017
diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -34,4 +34,5 @@ def exp():
     p.start()
     p.join()
     assert p.exitcode != 0, "Child process call to qr did not fail"
+    assert p.exitcode == -11, "The error is not a segmentation fault %s" % p.exitcode
     print("Child process call to QR failed as expected")
diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -23,11 +23,12 @@ def exp():
     flattened = get_flattened(tensor)
     # It should fail if being called
     # in a child process.
-    torch.qr(flattened)
+    return torch.qr(flattened)
 
 if __name__=="__main__":
     # First call
-    exp()
+    result = exp()
+    assert result is not None, "Oops, it should have not failed here"
     # Now create child process.
     p = mp.Process(target=exp)
     p.start()

diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -12,7 +12,7 @@ def get_flattened(tensor):
     return flattened
 
 def get_mat():
-    """ This is what we send when doing the initialization """
+    """ This is what we send when during the initialization """
     wc_dim = 200
     mat = nn.utils.weight_norm(nn.Linear(wc_dim, wc_dim, bias=False), name="weight")
     tensor = mat.weight.data

diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -2,7 +2,7 @@
 import torch.nn as nn
 import multiprocessing as mp
 
-def get_flattened():
+def get_flattened(tensor):
     """ This is just the first part of orthogonal initialization.
     Taken directly from https://github.com/pytorch/pytorch/blob/master/torch/nn/init.py
     """

diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -6,19 +6,24 @@ def get_flattened():
     """ This is just the first part of orthogonal initialization.
     Taken directly from https://github.com/pytorch/pytorch/blob/master/torch/nn/init.py
     """
-    wc_dim = 200
-    mat = nn.utils.weight_norm(nn.Linear(wc_dim, wc_dim, bias=False), name="weight")
-    tensor = mat.weight.data
-
     rows = tensor.size(0)
     cols = tensor[0].numel()
     flattened = torch.Tensor(rows, cols).normal_(0, 1)
     return flattened
 
+def get_mat():
+    """ This is what we send when doing the initialization """
+    wc_dim = 200
+    mat = nn.utils.weight_norm(nn.Linear(wc_dim, wc_dim, bias=False), name="weight")
+    tensor = mat.weight.data
+    return tensor
+
 def exp():
+    tensor = get_mat()
+    flattened = get_flattened(tensor)
     # It should fail if being called
     # in a child process.
-    torch.qr(get_flattened())
+    torch.qr(flattened)
 
 if __name__=="__main__":
     # First call

diff --git a/torch_qr_fail.py b/torch_qr_fail.py
@@ -3,6 +3,9 @@
 import multiprocessing as mp
 
 def get_flattened():
+    """ This is just the first part of orthogonal initialization.
+    Taken directly from https://github.com/pytorch/pytorch/blob/master/torch/nn/init.py
+    """
     wc_dim = 200
     mat = nn.utils.weight_norm(nn.Linear(wc_dim, wc_dim, bias=False), name="weight")
     tensor = mat.weight.data

diff --git a/gistfile1.txt → torch_qr_fail.py b/gistfile1.txt → torch_qr_fail.py
diff --git a/gistfile1.txt b/gistfile1.txt
@@ -0,0 +1,28 @@
+import torch
+import torch.nn as nn
+import multiprocessing as mp
+
+def get_flattened():
+    wc_dim = 200
+    mat = nn.utils.weight_norm(nn.Linear(wc_dim, wc_dim, bias=False), name="weight")
+    tensor = mat.weight.data
+
+    rows = tensor.size(0)
+    cols = tensor[0].numel()
+    flattened = torch.Tensor(rows, cols).normal_(0, 1)
+    return flattened
+
+def exp():
+    # It should fail if being called
+    # in a child process.
+    torch.qr(get_flattened())
+
+if __name__=="__main__":
+    # First call
+    exp()
+    # Now create child process.
+    p = mp.Process(target=exp)
+    p.start()
+    p.join()
+    assert p.exitcode != 0, "Child process call to qr did not fail"
+    print("Child process call to QR failed as expected")