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fix the input/output type mismatch (#20829)

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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20829

as title

Reviewed By: jamesr66a

Differential Revision: D15461937

fbshipit-source-id: 02c7150c0e8d020030ae8898008f718c74850dca
This commit is contained in:
Lingyi Liu
2019-05-23 10:47:18 -07:00
committed by Facebook Github Bot
parent 9c57d8df42
commit 2c556a9489
1 changed files with 2 additions and 2 deletions
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4
torch/jit/quantized.py
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@ -20,7 +20,7 @@ class QuantizedLinear(torch.jit.ScriptModule):
self.weight = torch.nn.Parameter(self.weight, requires_grad=False)
self.col_offsets = torch.nn.Parameter(self.col_offsets, requires_grad=False)
assert other.bias is not None, 'QuantizedLinear requires a bias'
self.bias = torch.nn.Parameter(other.bias.clone().float())
self.bias = torch.nn.Parameter(other.bias.clone().float(), requires_grad=False)
self.register_buffer(
'packed_tensor_ptr',
@ -42,7 +42,7 @@ class QuantizedLinear(torch.jit.ScriptModule):
out = torch.fbgemm_linear_int8_weight(
input.float(), self.weight, self.packed_tensor_ptr, self.col_offsets,
self.scale, self.zero_point, self.bias)
return out.type_as(input)
return out.to(input.dtype)
def extra_repr(self):
repr = 'in_features={in_features}, out_features={out_features}, ' \