Solved by ptrblck in post #2 
              
              
                Yes, should be the case: 
# Setup
conv = torch.nn.Conv1d(in_channels=512, out_channels=512, kernel_size=1).double()
lin = torch.nn.Linear(512, 512).double()

# use same param values
with torch.no_grad():
    lin.weight = nn.Parameter(conv.weight.squeeze(2))
    lin.bias = nn.Parameter(conv.bias)

# …