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ConvReLU1d#

class torch.ao.nn.intrinsic.qat.modules.conv_fused.ConvReLU1d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros', qconfig=None)[source]#

A ConvReLU1d module is a fused module of Conv1d and ReLU, attached with FakeQuantize modules for weight for quantization aware training.

We combined the interface of Conv1d and BatchNorm1d.

Variables:

weight_fake_quant – fake quant module for weight

forward(input)[source]#

Performs forward pass through fused Conv1d and ReLU.

classmethod from_float(mod, use_precomputed_fake_quant=False)[source]#

Creates a QAT module from a floating point module.