Conv1d.patch

--- /opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py
+++ /opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py
@@ -65,7 +65,6 @@
         stride (int or tuple, optional): Stride of the convolution. Default: 1
         padding (int or tuple, optional): Zero-padding added to both sides of
             the input. Default: 0
-        padding_mode (string, optional). Accepted values `zeros` and `circular` Default: `zeros`
         dilation (int or tuple, optional): Spacing between kernel
             elements. Default: 1
         groups (int, optional): Number of blocked connections from input
@@ -105,23 +104,17 @@
     """
 
     def __init__(self, in_channels, out_channels, kernel_size, stride=1,
-                 padding=0, dilation=1, groups=1,
-                 bias=True, padding_mode='zeros'):
+                 padding=0, dilation=1, groups=1, bias=True):
         kernel_size = _single(kernel_size)
         stride = _single(stride)
         padding = _single(padding)
         dilation = _single(dilation)
         super(Conv1d, self).__init__(
             in_channels, out_channels, kernel_size, stride, padding, dilation,
-            False, _single(0), groups, bias, padding_mode)
+            False, _single(0), groups, bias)
 
     @weak_script_method
     def forward(self, input):
-        if self.padding_mode == 'circular':
-            expanded_padding = ((self.padding[0] + 1) // 2, self.padding[0] // 2)
-            return F.conv1d(F.pad(input, expanded_padding, mode='circular'),
-                            self.weight, self.bias, self.stride,
-                            _single(0), self.dilation, self.groups)
         return F.conv1d(input, self.weight, self.bias, self.stride,
                         self.padding, self.dilation, self.groups)