Conv3d¶
- class torch.ao.nn.quantized.Conv3d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros', device=None, dtype=None)[source]¶
在由多个量化输入平面组成的量化输入信号上应用 3D 卷积。
有关输入参数、参数和实现的详细信息,请参阅
Conv3d
.注意
仅支持 zeros 用于
padding_mode
参数。注意
仅支持 torch.quint8 用于输入数据类型。
有关其他属性,请参阅
Conv3d
.示例
>>> # With square kernels and equal stride >>> m = nn.quantized.Conv3d(16, 33, 3, stride=2) >>> # non-square kernels and unequal stride and with padding >>> m = nn.quantized.Conv3d(16, 33, (3, 5, 5), stride=(1, 2, 2), padding=(1, 2, 2)) >>> # non-square kernels and unequal stride and with padding and dilation >>> m = nn.quantized.Conv3d(16, 33, (3, 5, 5), stride=(1, 2, 2), padding=(1, 2, 2), dilation=(1, 2, 2)) >>> input = torch.randn(20, 16, 56, 56, 56) >>> # quantize input to quint8 >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, dtype=torch.quint8) >>> output = m(q_input)