def forward(self, x, out_channel=None):
if out_channel is None:
out_channel = self.active_out_channel
in_channel = x.size(1)
filters = self.conv.weight[:out_channel, :in_channel, :, :].contiguous()
padding = get_same_padding(self.kernel_size)
y = F.conv2d(x, filters, None, self.stride, padding, self.dilation, 1)
return y
def forward(self, x, kernel_size=None):
if kernel_size is None:
kernel_size = self.active_kernel_size
in_channel = x.size(1)
filters = self.get_active_filter(in_channel, kernel_size).contiguous()
padding = get_same_padding(kernel_size)
y = F.conv2d(x, filters, None, self.stride, padding, self.dilation,
in_channel)
return y
def forward(self, x, kernel_size=None):
if kernel_size is None:
kernel_size = self.active_kernel_size
in_channel = x.size(1)
filters = self.get_active_filter(in_channel, kernel_size).contiguous()
inputs, weight, bias = self._quantize(inputs=x, weight=filters, bias=None)
padding = get_same_padding(kernel_size)
y = F.conv2d(
inputs, weight, None, self.stride, padding, self.dilation, in_channel
)
return y
def forward(self, x, out_channel=None):
if out_channel is None:
out_channel = self.active_out_channel
in_channel = x.size(1)
filters = self.conv.weight[:out_channel, :in_channel, :, :].contiguous(
)
x_quant, w_quant = self.conv.get_quant_x_w(x, filters)
padding = get_same_padding(self.kernel_size)
#if hvd.rank()==0:
# print('point',x.size(),filters.size(),x_quant[0][0][0][0].detach()/self.conv.sa.detach(),w_quant[0][0][0][0].detach()/self.conv.sw.detach())
y = F.conv2d(x_quant, w_quant, None, self.stride, padding,
self.dilation, 1)
return y
def forward(self, x, kernel_size=None):
if kernel_size is None:
kernel_size = self.active_kernel_size
in_channel = x.size(1)
filters = self.get_active_filter(in_channel, kernel_size).contiguous()
padding = get_same_padding(kernel_size)
x_quant, w_quant = self.conv.get_quant_x_w(x, filters)
#if hvd.rank() == 0:
# print('depth',x.size(),filters.size(),x_quant[0][0][0][0].detach()/self.conv.sa.detach(),w_quant[0][0][0][0].detach()/self.conv.sw.detach())
y = F.conv2d(x_quant, w_quant, None, self.stride, padding,
self.dilation, in_channel)
return y