From 8cb107e78c93575b8a263dcfc690717bfc6dda44 Mon Sep 17 00:00:00 2001 From: nihuini Date: Thu, 30 May 2019 11:28:48 +0800 Subject: [PATCH] apply model optimize --- benchmark/mnasnet.param | 5 ++--- benchmark/mobilenet.param | 2 +- benchmark/mobilenet_v2.param | 2 +- benchmark/proxylessnasnet.param | 5 ++--- benchmark/shufflenet.param | 2 +- 5 files changed, 7 insertions(+), 9 deletions(-) diff --git a/benchmark/mnasnet.param b/benchmark/mnasnet.param index feff8d318..56e2d1725 100644 --- a/benchmark/mnasnet.param +++ b/benchmark/mnasnet.param @@ -1,5 +1,5 @@ 7767517 -77 87 +76 86 Input data 0 1 data Convolution first-3x3-conv 1 1 data first-3x3-conv_relu 0=32 1=3 3=2 4=1 5=1 6=864 9=1 ConvolutionDepthWise A0_dw 1 1 first-3x3-conv_relu A0_dw_relu 0=32 1=3 4=1 5=1 6=288 7=32 9=1 @@ -73,7 +73,6 @@ Convolution G0_expand 1 1 unknownncnn_9 G0_expand_re ConvolutionDepthWise G0_dw 1 1 G0_expand_relu G0_dw_relu 0=1152 1=3 4=1 5=1 6=10368 7=1152 9=1 Convolution G0_linear 1 1 G0_dw_relu G0_linear_bn 0=320 1=1 5=1 6=368640 Convolution last-1x1-conv 1 1 G0_linear_bn last-1x1-conv_relu 0=1280 1=1 5=1 6=409600 9=1 -Pooling avgpool 1 1 last-1x1-conv_relu avgpool 0=1 1=7 4=1 5=1 -Flatten flatten 1 1 avgpool flatten +Pooling avgpool 1 1 last-1x1-conv_relu flatten 0=1 1=7 4=1 5=1 InnerProduct fc 1 1 flatten fc 0=1000 1=1 2=1280000 Softmax prob 1 1 fc prob diff --git a/benchmark/mobilenet.param b/benchmark/mobilenet.param index 8818b3564..8c7b9298c 100644 --- a/benchmark/mobilenet.param +++ b/benchmark/mobilenet.param @@ -29,5 +29,5 @@ Convolution conv5_6/sep 1 1 conv5_6/dw_relu5_6/dw conv ConvolutionDepthWise conv6/dw 1 1 conv5_6/sep_relu5_6/sep conv6/dw_relu6/dw 0=1024 1=3 4=1 5=1 6=9216 7=1024 9=1 Convolution conv6/sep 1 1 conv6/dw_relu6/dw conv6/sep_relu6/sep 0=1024 1=1 5=1 6=1048576 9=1 Pooling pool6 1 1 conv6/sep_relu6/sep pool6 0=1 4=1 -Convolution fc7 1 1 pool6 fc7 0=1000 1=1 5=1 6=1024000 +InnerProduct fc7 1 1 pool6 fc7 0=1000 1=1 2=1024000 Softmax prob 1 1 fc7 prob diff --git a/benchmark/mobilenet_v2.param b/benchmark/mobilenet_v2.param index fa3b62b83..dd0ebc62a 100644 --- a/benchmark/mobilenet_v2.param +++ b/benchmark/mobilenet_v2.param @@ -75,5 +75,5 @@ ConvolutionDepthWise conv6_3/dwise 1 1 conv6_3/expand/bn_relu6_3/ Convolution conv6_3/linear 1 1 conv6_3/dwise/bn_relu6_3/dwise conv6_3/linear/bn_conv6_3/linear/scale 0=320 1=1 5=1 6=307200 Convolution conv6_4 1 1 conv6_3/linear/bn_conv6_3/linear/scale conv6_4/bn_relu6_4 0=1280 1=1 5=1 6=409600 9=1 Pooling pool6 1 1 conv6_4/bn_relu6_4 pool6 0=1 4=1 -Convolution fc7 1 1 pool6 fc7 0=1000 1=1 5=1 6=1280000 +InnerProduct fc7 1 1 pool6 fc7 0=1000 1=1 2=1280000 Softmax prob 1 1 fc7 prob diff --git a/benchmark/proxylessnasnet.param b/benchmark/proxylessnasnet.param index 476b1308d..93ae55c06 100644 --- a/benchmark/proxylessnasnet.param +++ b/benchmark/proxylessnasnet.param @@ -1,5 +1,5 @@ 7767517 -92 105 +91 104 Input data 0 1 data Convolution first-3x3-conv 1 1 data first-3x3-conv_relu 0=32 1=3 3=2 4=1 5=1 6=864 9=1 ConvolutionDepthWise A0_dw 1 1 first-3x3-conv_relu A0_dw_relu 0=32 1=3 4=1 5=1 6=288 7=32 9=1 @@ -88,7 +88,6 @@ Convolution G0_expand 1 1 unknownncnn_12 G0_expand_r ConvolutionDepthWise G0_dw 1 1 G0_expand_relu G0_dw_relu 0=1152 1=7 4=3 5=1 6=56448 7=1152 9=1 Convolution G0_linear 1 1 G0_dw_relu G0_linear_bn 0=320 1=1 5=1 6=368640 Convolution last-1x1-conv 1 1 G0_linear_bn last-1x1-conv_relu 0=1280 1=1 5=1 6=409600 9=1 -Pooling avgpool 1 1 last-1x1-conv_relu avgpool 0=1 1=7 4=1 5=1 -Flatten flatten 1 1 avgpool flatten +Pooling avgpool 1 1 last-1x1-conv_relu flatten 0=1 1=7 4=1 5=1 InnerProduct fc 1 1 flatten fc 0=1000 1=1 2=1280000 Softmax prob 1 1 fc prob diff --git a/benchmark/shufflenet.param b/benchmark/shufflenet.param index aa250cd4e..44d242b5d 100644 --- a/benchmark/shufflenet.param +++ b/benchmark/shufflenet.param @@ -118,4 +118,4 @@ ConvolutionDepthWise resx16_conv3 1 1 resx16_conv2_resx16_conv2_ Eltwise resx16_elewise 2 1 resx15_elewise_resx15_elewise_relu_splitncnn_0 resx16_conv3_resx16_conv3_scale resx16_elewise 0=1 ReLU resx16_elewise_relu 1 1 resx16_elewise resx16_elewise_resx16_elewise_relu Pooling pool_ave 1 1 resx16_elewise_resx16_elewise_relu pool_ave 0=1 4=1 -Convolution fc1000 1 1 pool_ave fc1000 0=1000 1=1 5=1 6=960000 +InnerProduct fc1000 1 1 pool_ave fc1000 0=1000 1=1 2=960000