def get_flops(self, x): flop1 = utils.count_conv_flop(self.inverted_bottleneck.conv, x) x = self.inverted_bottleneck(x) flop2 = utils.count_conv_flop(self.depth_wise.conv, x) x = self.depth_wise(x) flop3 = utils.count_conv_flop(self.point_wise.conv, x) x = self.point_wise(x) return flop1 + flop2 + flop3, x
def get_flops(self, input_size):
flop_1 = count_conv_flop(self.conv_1, input_size)
if self.stride > 1:
input_size = (input_size[0] // self.stride,
input_size[1] // self.stride)
flop_2 = count_conv_flop(self.conv_2, input_size)
print(
'DilConv: Flops: {:.2e}, input_size: {} ,in_c : {} , out_c: {} , kernel: {} , stride: {} '
.format(flop_1 + flop_2, input_size, self.in_channels,
self.out_channels, self.kernel_size, self.stride))
return flop_1 + flop_2
def get_flops(self, x):
if self.inverted_bottleneck:
flop1 = count_conv_flop(self.inverted_bottleneck.conv, x)
x = self.inverted_bottleneck(x)
else:
flop1 = 0
flop2 = count_conv_flop(self.depth_conv.conv, x)
x = self.depth_conv(x)
flop3 = count_conv_flop(self.point_linear.conv, x)
x = self.point_linear(x)
return flop1 + flop2 + flop3, x
def get_flops(self, input_size):
f_depth_1 = count_conv_flop(self.conv_1_1, input_size)
if self.stride > 1:
input_size = (input_size[0] // self.stride,
input_size[1] // self.stride)
f_point_1 = count_conv_flop(self.conv_1_2, input_size)
f_depth_2 = count_conv_flop(self.conv_2_1, input_size)
f_point_2 = count_conv_flop(self.conv_2_2, input_size)
f_sum = f_depth_1 + f_depth_2 + f_point_1 + f_point_2
print(
'SepConv: Flops: {:.2e}, input_size: {} ,in_c : {} , out_c: {} , kernel: {} , stride: {} '
.format(f_sum, input_size, self.in_channels, self.out_channels,
self.kernel_size, self.stride))
return f_sum
def get_flops(self, input_size):
flop = count_conv_flop(self.conv, input_size)
print(
'ReLBN: Flops: {:.2e}, input_size: {} ,in_c : {} , out_c: {} , kernel: {} , stride: {} '
.format(flop, input_size, self.in_channels, self.out_channels,
self.kernel_size, self.stride))
return flop
def get_flops(self, x):
flop = utils.count_conv_flop(self.first_conv, x)
x = self.first_conv(x)
x = self.stem(x)
mb_flop, x = self.mbconv3.get_flops(x)
flop += mb_flop
for model in self.layers:
layer = model.MixedOp
layer_flop, x = layer.active_op.get_flops(x)
flop += layer_flop
post_flop, x = self.post.get_flops(x)
flop += post_flop
x = self.global_pooling(x)
flop += self.classifier.weight.numel()
x = self.classifier(x.view(x.size(0), -1))
return flop
def get_flops(self, input_size):
f_1 = count_conv_flop(self.conv_1, input_size)
f_2 = count_conv_flop(self.conv_2, input_size)
return f_1 + f_2
def get_flops(self, x):
depth_flop = count_conv_flop(self.depth_conv, x)
point_flop = count_conv_flop(self.point_conv, self.depth_conv(x))
return depth_flop + point_flop, self.forward(x)
def get_flops(self, x):
return count_conv_flop(self.conv, x), self.forward(x)