MMdnn
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microsoft
tensorflow openpose convert to caffe failed
Platform (like ubuntu 16.04/win10):ubuntu 16.04
Python version:2.7
Source framework with version (like Tensorflow 1.4.1 with GPU):Tensorflow 1.8
Destination framework with version (like CNTK 2.3 with GPU):
Pre-trained model path (webpath or webdisk path): http://www.mediafire.com/file/1pyjsjl0p93x27c/graph_freeze.pb
###this is net ###
Running scripts: mmconvert -sf tensorflow -iw graph_freeze.pb --inNodeName image --inputShape 368,432,3 --dstNodeName Openpose/concat_stage7 -df caffe -om tf_openpose
Check failed: top_shape[j] == bottom[i]->shape(j) (46 vs. 45) All inputs must have the same shape, except at concat_axis. But ,I can use this graph_freeze.pb in tensorflow infference right result.
log as follow: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA IR network structure is saved as [8c581b98527a41608f660bc97248d906.json]. IR network structure is saved as [8c581b98527a41608f660bc97248d906.pb]. IR weights are saved as [8c581b98527a41608f660bc97248d906.npy]. Parse file [8c581b98527a41608f660bc97248d906.pb] with binary format successfully. Target network code snippet is saved as [8c581b98527a41608f660bc97248d906.py]. Target weights are saved as [8c581b98527a41608f660bc97248d906.npy]. WARNING: Logging before InitGoogleLogging() is written to STDERR I0726 16:15:38.266441 10279 net.cpp:58] Initializing net from parameters: state { phase: TRAIN level: 0 } layer { name: "Placeholder" type: "Input" top: "Placeholder" input_param { shape { dim: 1 dim: 3 dim: 368 dim: 432 } } } layer { name: "MobilenetV1_Conv2d_0_Conv2D" type: "Convolution" bottom: "Placeholder" top: "MobilenetV1_Conv2d_0_Conv2D" convolution_param { num_output: 24 bias_term: false group: 1 stride: 2 pad_h: 0 pad_w: 0 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_0_Conv2D" top: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_0_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_1_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_1_depthwise_depthwise" convolution_param { num_output: 24 bias_term: false group: 24 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_1_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_1_depthwise_depthwise" top: "MobilenetV1_Conv2d_1_pointwise_Conv2D" convolution_param { num_output: 48 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_1_pointwise_Conv2D" top: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_1_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_2_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_2_depthwise_depthwise" convolution_param { num_output: 48 bias_term: false group: 48 stride: 2 pad_h: 0 pad_w: 0 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_2_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_2_depthwise_depthwise" top: "MobilenetV1_Conv2d_2_pointwise_Conv2D" convolution_param { num_output: 96 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_2_pointwise_Conv2D" top: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_2_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_3_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_3_depthwise_depthwise" convolution_param { num_output: 96 bias_term: false group: 96 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_3_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_3_depthwise_depthwise" top: "MobilenetV1_Conv2d_3_pointwise_Conv2D" convolution_param { num_output: 96 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_3_pointwise_Conv2D" top: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_3_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Conv2d_3_pool" type: "Pooling" bottom: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" top: "Conv2d_3_pool" pooling_param { pool: MAX kernel_size: 2 stride: 2 pad_h: 0 pad_w: 0 } } layer { name: "MobilenetV1_Conv2d_4_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_4_depthwise_depthwise" convolution_param { num_output: 96 bias_term: false group: 96 stride: 2 pad_h: 0 pad_w: 0 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_4_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_4_depthwise_depthwise" top: "MobilenetV1_Conv2d_4_pointwise_Conv2D" convolution_param { num_output: 192 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_4_pointwise_Conv2D" top: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_4_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_5_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_5_depthwise_depthwise" convolution_param { num_output: 192 bias_term: false group: 192 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_5_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_5_depthwise_depthwise" top: "MobilenetV1_Conv2d_5_pointwise_Conv2D" convolution_param { num_output: 192 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_5_pointwise_Conv2D" top: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_5_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_6_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_6_depthwise_depthwise" convolution_param { num_output: 192 bias_term: false group: 192 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_6_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_6_depthwise_depthwise" top: "MobilenetV1_Conv2d_6_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_6_pointwise_Conv2D" top: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_6_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_7_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_7_depthwise_depthwise" convolution_param { num_output: 384 bias_term: false group: 384 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_7_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_7_depthwise_depthwise" top: "MobilenetV1_Conv2d_7_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_7_pointwise_Conv2D" top: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_7_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_8_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_8_depthwise_depthwise" convolution_param { num_output: 384 bias_term: false group: 384 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_8_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_8_depthwise_depthwise" top: "MobilenetV1_Conv2d_8_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_8_pointwise_Conv2D" top: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_8_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_9_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_9_depthwise_depthwise" convolution_param { num_output: 384 bias_term: false group: 384 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_9_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_9_depthwise_depthwise" top: "MobilenetV1_Conv2d_9_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_9_pointwise_Conv2D" top: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_9_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_10_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_10_depthwise_depthwise" convolution_param { num_output: 384 bias_term: false group: 384 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_10_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_10_depthwise_depthwise" top: "MobilenetV1_Conv2d_10_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_10_pointwise_Conv2D" top: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_10_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "MobilenetV1_Conv2d_11_depthwise_depthwise" type: "Convolution" bottom: "MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_11_depthwise_depthwise" convolution_param { num_output: 384 bias_term: false group: 384 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "MobilenetV1_Conv2d_11_pointwise_Conv2D" type: "Convolution" bottom: "MobilenetV1_Conv2d_11_depthwise_depthwise" top: "MobilenetV1_Conv2d_11_pointwise_Conv2D" convolution_param { num_output: 384 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "MobilenetV1_Conv2d_11_pointwise_Conv2D" top: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "MobilenetV1_Conv2d_11_pointwise_Relu" type: "ReLU" bottom: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" top: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "feat_concat" type: "Concat" bottom: "Conv2d_3_pool" bottom: "MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm" bottom: "MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm" top: "feat_concat" concat_param { axis: 1 } } layer { name: "Openpose_MConv_Stage1_L2_1_depthwise_depthwise" type: "Convolution" bottom: "feat_concat" top: "Openpose_MConv_Stage1_L2_1_depthwise_depthwise" convolution_param { num_output: 864 bias_term: false group: 864 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L1_1_depthwise_depthwise" type: "Convolution" bottom: "feat_concat" top: "Openpose_MConv_Stage1_L1_1_depthwise_depthwise" convolution_param { num_output: 864 bias_term: false group: 864 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L2_1_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_1_depthwise_depthwise" top: "Openpose_MConv_Stage1_L2_1_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L1_1_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_1_depthwise_depthwise" top: "Openpose_MConv_Stage1_L1_1_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L2_1_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L1_1_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L2_1_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L1_1_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L2_2_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_2_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L1_2_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_1_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_2_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L2_2_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_2_depthwise_depthwise" top: "Openpose_MConv_Stage1_L2_2_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L1_2_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_2_depthwise_depthwise" top: "Openpose_MConv_Stage1_L1_2_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L2_2_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L1_2_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L2_2_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L1_2_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L2_3_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_3_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L1_3_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_2_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_3_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 1 pad_w: 1 kernel_h: 3 kernel_w: 3 } } layer { name: "Openpose_MConv_Stage1_L2_3_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_3_depthwise_depthwise" top: "Openpose_MConv_Stage1_L2_3_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L1_3_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_3_depthwise_depthwise" top: "Openpose_MConv_Stage1_L1_3_pointwise_Conv2D" convolution_param { num_output: 64 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L2_3_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L1_3_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L2_3_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L1_3_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L2_4_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_4_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L1_4_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_3_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_4_depthwise_depthwise" convolution_param { num_output: 64 bias_term: false group: 64 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L2_4_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_4_depthwise_depthwise" top: "Openpose_MConv_Stage1_L2_4_pointwise_Conv2D" convolution_param { num_output: 256 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L1_4_pointwise_Conv2D" type: "Convolution" bottom: "Openpose_MConv_Stage1_L1_4_depthwise_depthwise" top: "Openpose_MConv_Stage1_L1_4_pointwise_Conv2D" convolution_param { num_output: 256 bias_term: false group: 1 stride: 1 pad_h: 0 pad_w: 0 kernel_h: 1 kernel_w: 1 } } layer { name: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L2_4_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" type: "BatchNorm" bottom: "Openpose_MConv_Stage1_L1_4_pointwise_Conv2D" top: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" batch_norm_param { use_global_stats: true eps: 0.001 } } layer { name: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm_scale" type: "Scale" bottom: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" scale_param { bias_term: true } } layer { name: "Openpose_MConv_Stage1_L2_4_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L1_4_pointwise_Relu" type: "ReLU" bottom: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L1_4_pointwise_BatchNorm_FusedBatchNorm" } layer { name: "Openpose_MConv_Stage1_L2_5_depthwise_depthwise" type: "Convolution" bottom: "Openpose_MConv_Stage1_L2_4_pointwise_BatchNorm_FusedBatchNorm" top: "Openpose_MConv_Stage1_L2_5_depthwise_depthwise" convolution_param { num_output: 256 bias_term: false group: 256 stride I0726 16:15:38.268064 10279 layer_factory.hpp:77] Creating layer Placeholder I0726 16:15:38.268103 10279 net.cpp:100] Creating Layer Placeholder I0726 16:15:38.268113 10279 net.cpp:408] Placeholder -> Placeholder I0726 16:15:38.268151 10279 net.cpp:150] Setting up Placeholder I0726 16:15:38.268162 10279 net.cpp:157] Top shape: 1 3 368 432 (476928) I0726 16:15:38.268167 10279 net.cpp:165] Memory required for data: 1907712 I0726 16:15:38.268172 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_0_Conv2D I0726 16:15:38.268182 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_0_Conv2D I0726 16:15:38.268187 10279 net.cpp:434] MobilenetV1_Conv2d_0_Conv2D <- Placeholder I0726 16:15:38.268194 10279 net.cpp:408] MobilenetV1_Conv2d_0_Conv2D -> MobilenetV1_Conv2d_0_Conv2D I0726 16:15:38.268225 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_0_Conv2D I0726 16:15:38.268234 10279 net.cpp:157] Top shape: 1 24 183 215 (944280) I0726 16:15:38.268239 10279 net.cpp:165] Memory required for data: 5684832 I0726 16:15:38.268247 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268257 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268262 10279 net.cpp:434] MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_0_Conv2D I0726 16:15:38.268268 10279 net.cpp:408] MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268313 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268324 10279 net.cpp:157] Top shape: 1 24 183 215 (944280) I0726 16:15:38.268328 10279 net.cpp:165] Memory required for data: 9461952 I0726 16:15:38.268339 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268348 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268353 10279 net.cpp:434] MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268360 10279 net.cpp:395] MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.268373 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268448 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268460 10279 net.cpp:157] Top shape: 1 24 183 215 (944280) I0726 16:15:38.268465 10279 net.cpp:165] Memory required for data: 13239072 I0726 16:15:38.268473 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_0_Relu I0726 16:15:38.268482 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_0_Relu I0726 16:15:38.268487 10279 net.cpp:434] MobilenetV1_Conv2d_0_Relu <- MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268493 10279 net.cpp:395] MobilenetV1_Conv2d_0_Relu -> MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.268501 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_0_Relu I0726 16:15:38.268507 10279 net.cpp:157] Top shape: 1 24 183 215 (944280) I0726 16:15:38.268512 10279 net.cpp:165] Memory required for data: 17016192 I0726 16:15:38.268517 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_depthwise_depthwise I0726 16:15:38.268525 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_1_depthwise_depthwise I0726 16:15:38.268530 10279 net.cpp:434] MobilenetV1_Conv2d_1_depthwise_depthwise <- MobilenetV1_Conv2d_0_BatchNorm_FusedBatchNorm I0726 16:15:38.268537 10279 net.cpp:408] MobilenetV1_Conv2d_1_depthwise_depthwise -> MobilenetV1_Conv2d_1_depthwise_depthwise I0726 16:15:38.268553 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_1_depthwise_depthwise I0726 16:15:38.268559 10279 net.cpp:157] Top shape: 1 24 183 215 (944280) I0726 16:15:38.268564 10279 net.cpp:165] Memory required for data: 20793312 I0726 16:15:38.268570 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_pointwise_Conv2D I0726 16:15:38.268577 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_1_pointwise_Conv2D I0726 16:15:38.268582 10279 net.cpp:434] MobilenetV1_Conv2d_1_pointwise_Conv2D <- MobilenetV1_Conv2d_1_depthwise_depthwise I0726 16:15:38.268587 10279 net.cpp:408] MobilenetV1_Conv2d_1_pointwise_Conv2D -> MobilenetV1_Conv2d_1_pointwise_Conv2D I0726 16:15:38.268602 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_1_pointwise_Conv2D I0726 16:15:38.268609 10279 net.cpp:157] Top shape: 1 48 183 215 (1888560) I0726 16:15:38.268612 10279 net.cpp:165] Memory required for data: 28347552 I0726 16:15:38.268618 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268625 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268630 10279 net.cpp:434] MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_1_pointwise_Conv2D I0726 16:15:38.268636 10279 net.cpp:408] MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268682 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268689 10279 net.cpp:157] Top shape: 1 48 183 215 (1888560) I0726 16:15:38.268692 10279 net.cpp:165] Memory required for data: 35901792 I0726 16:15:38.268700 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268707 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268712 10279 net.cpp:434] MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268716 10279 net.cpp:395] MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.268725 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268775 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.268782 10279 net.cpp:157] Top shape: 1 48 183 215 (1888560) I0726 16:15:38.268786 10279 net.cpp:165] Memory required for data: 43456032 I0726 16:15:38.268791 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_1_pointwise_Relu I0726 16:15:38.268797 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_1_pointwise_Relu I0726 16:15:38.268801 10279 net.cpp:434] MobilenetV1_Conv2d_1_pointwise_Relu <- MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268805 10279 net.cpp:395] MobilenetV1_Conv2d_1_pointwise_Relu -> MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.268822 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_1_pointwise_Relu I0726 16:15:38.268828 10279 net.cpp:157] Top shape: 1 48 183 215 (1888560) I0726 16:15:38.268832 10279 net.cpp:165] Memory required for data: 51010272 I0726 16:15:38.268836 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_depthwise_depthwise I0726 16:15:38.268843 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_2_depthwise_depthwise I0726 16:15:38.268848 10279 net.cpp:434] MobilenetV1_Conv2d_2_depthwise_depthwise <- MobilenetV1_Conv2d_1_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268854 10279 net.cpp:408] MobilenetV1_Conv2d_2_depthwise_depthwise -> MobilenetV1_Conv2d_2_depthwise_depthwise I0726 16:15:38.268870 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_2_depthwise_depthwise I0726 16:15:38.268877 10279 net.cpp:157] Top shape: 1 48 91 107 (467376) I0726 16:15:38.268882 10279 net.cpp:165] Memory required for data: 52879776 I0726 16:15:38.268887 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_pointwise_Conv2D I0726 16:15:38.268893 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_2_pointwise_Conv2D I0726 16:15:38.268898 10279 net.cpp:434] MobilenetV1_Conv2d_2_pointwise_Conv2D <- MobilenetV1_Conv2d_2_depthwise_depthwise I0726 16:15:38.268904 10279 net.cpp:408] MobilenetV1_Conv2d_2_pointwise_Conv2D -> MobilenetV1_Conv2d_2_pointwise_Conv2D I0726 16:15:38.268919 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_2_pointwise_Conv2D I0726 16:15:38.268926 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.268930 10279 net.cpp:165] Memory required for data: 56618784 I0726 16:15:38.268936 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268944 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268949 10279 net.cpp:434] MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_2_pointwise_Conv2D I0726 16:15:38.268954 10279 net.cpp:408] MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268977 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.268985 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.268990 10279 net.cpp:165] Memory required for data: 60357792 I0726 16:15:38.269001 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269008 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269013 10279 net.cpp:434] MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269019 10279 net.cpp:395] MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.269031 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269057 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269065 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269069 10279 net.cpp:165] Memory required for data: 64096800 I0726 16:15:38.269076 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_2_pointwise_Relu I0726 16:15:38.269083 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_2_pointwise_Relu I0726 16:15:38.269088 10279 net.cpp:434] MobilenetV1_Conv2d_2_pointwise_Relu <- MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269094 10279 net.cpp:395] MobilenetV1_Conv2d_2_pointwise_Relu -> MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.269100 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_2_pointwise_Relu I0726 16:15:38.269106 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269110 10279 net.cpp:165] Memory required for data: 67835808 I0726 16:15:38.269114 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_depthwise_depthwise I0726 16:15:38.269122 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_depthwise_depthwise I0726 16:15:38.269126 10279 net.cpp:434] MobilenetV1_Conv2d_3_depthwise_depthwise <- MobilenetV1_Conv2d_2_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269132 10279 net.cpp:408] MobilenetV1_Conv2d_3_depthwise_depthwise -> MobilenetV1_Conv2d_3_depthwise_depthwise I0726 16:15:38.269147 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_depthwise_depthwise I0726 16:15:38.269155 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269158 10279 net.cpp:165] Memory required for data: 71574816 I0726 16:15:38.269165 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_Conv2D I0726 16:15:38.269174 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_pointwise_Conv2D I0726 16:15:38.269179 10279 net.cpp:434] MobilenetV1_Conv2d_3_pointwise_Conv2D <- MobilenetV1_Conv2d_3_depthwise_depthwise I0726 16:15:38.269186 10279 net.cpp:408] MobilenetV1_Conv2d_3_pointwise_Conv2D -> MobilenetV1_Conv2d_3_pointwise_Conv2D I0726 16:15:38.269206 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_pointwise_Conv2D I0726 16:15:38.269214 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269218 10279 net.cpp:165] Memory required for data: 75313824 I0726 16:15:38.269224 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269232 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269237 10279 net.cpp:434] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_3_pointwise_Conv2D I0726 16:15:38.269243 10279 net.cpp:408] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269263 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269271 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269275 10279 net.cpp:165] Memory required for data: 79052832 I0726 16:15:38.269284 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269290 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269295 10279 net.cpp:434] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269301 10279 net.cpp:395] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.269312 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269338 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.269347 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269351 10279 net.cpp:165] Memory required for data: 82791840 I0726 16:15:38.269358 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_Relu I0726 16:15:38.269366 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_pointwise_Relu I0726 16:15:38.269371 10279 net.cpp:434] MobilenetV1_Conv2d_3_pointwise_Relu <- MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269376 10279 net.cpp:395] MobilenetV1_Conv2d_3_pointwise_Relu -> MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.269383 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_pointwise_Relu I0726 16:15:38.269389 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269393 10279 net.cpp:165] Memory required for data: 86530848 I0726 16:15:38.269397 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split I0726 16:15:38.269405 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split I0726 16:15:38.269410 10279 net.cpp:434] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split <- MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.269417 10279 net.cpp:408] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split -> MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split_0 I0726 16:15:38.269425 10279 net.cpp:408] MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split -> MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split_1 I0726 16:15:38.269435 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split I0726 16:15:38.269441 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269446 10279 net.cpp:157] Top shape: 1 96 91 107 (934752) I0726 16:15:38.269450 10279 net.cpp:165] Memory required for data: 94008864 I0726 16:15:38.269454 10279 layer_factory.hpp:77] Creating layer Conv2d_3_pool I0726 16:15:38.269462 10279 net.cpp:100] Creating Layer Conv2d_3_pool I0726 16:15:38.269466 10279 net.cpp:434] Conv2d_3_pool <- MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split_0 I0726 16:15:38.269474 10279 net.cpp:408] Conv2d_3_pool -> Conv2d_3_pool I0726 16:15:38.269488 10279 net.cpp:150] Setting up Conv2d_3_pool I0726 16:15:38.269496 10279 net.cpp:157] Top shape: 1 96 46 54 (238464) I0726 16:15:38.269500 10279 net.cpp:165] Memory required for data: 94962720 I0726 16:15:38.269505 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_depthwise_depthwise I0726 16:15:38.269512 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_4_depthwise_depthwise I0726 16:15:38.269517 10279 net.cpp:434] MobilenetV1_Conv2d_4_depthwise_depthwise <- MobilenetV1_Conv2d_3_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_3_pointwise_Relu_0_split_1 I0726 16:15:38.269523 10279 net.cpp:408] MobilenetV1_Conv2d_4_depthwise_depthwise -> MobilenetV1_Conv2d_4_depthwise_depthwise I0726 16:15:38.269541 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_4_depthwise_depthwise I0726 16:15:38.269546 10279 net.cpp:157] Top shape: 1 96 45 53 (228960) I0726 16:15:38.269551 10279 net.cpp:165] Memory required for data: 95878560 I0726 16:15:38.277405 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_pointwise_Conv2D I0726 16:15:38.277427 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_4_pointwise_Conv2D I0726 16:15:38.277434 10279 net.cpp:434] MobilenetV1_Conv2d_4_pointwise_Conv2D <- MobilenetV1_Conv2d_4_depthwise_depthwise I0726 16:15:38.277443 10279 net.cpp:408] MobilenetV1_Conv2d_4_pointwise_Conv2D -> MobilenetV1_Conv2d_4_pointwise_Conv2D I0726 16:15:38.277483 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_4_pointwise_Conv2D I0726 16:15:38.277494 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277499 10279 net.cpp:165] Memory required for data: 97710240 I0726 16:15:38.277505 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277513 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277518 10279 net.cpp:434] MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_4_pointwise_Conv2D I0726 16:15:38.277525 10279 net.cpp:408] MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277544 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277550 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277554 10279 net.cpp:165] Memory required for data: 99541920 I0726 16:15:38.277562 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277571 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277575 10279 net.cpp:434] MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277582 10279 net.cpp:395] MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.277595 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277612 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277621 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277624 10279 net.cpp:165] Memory required for data: 101373600 I0726 16:15:38.277637 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_4_pointwise_Relu I0726 16:15:38.277645 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_4_pointwise_Relu I0726 16:15:38.277650 10279 net.cpp:434] MobilenetV1_Conv2d_4_pointwise_Relu <- MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277657 10279 net.cpp:395] MobilenetV1_Conv2d_4_pointwise_Relu -> MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.277664 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_4_pointwise_Relu I0726 16:15:38.277670 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277675 10279 net.cpp:165] Memory required for data: 103205280 I0726 16:15:38.277679 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_depthwise_depthwise I0726 16:15:38.277688 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_5_depthwise_depthwise I0726 16:15:38.277693 10279 net.cpp:434] MobilenetV1_Conv2d_5_depthwise_depthwise <- MobilenetV1_Conv2d_4_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277699 10279 net.cpp:408] MobilenetV1_Conv2d_5_depthwise_depthwise -> MobilenetV1_Conv2d_5_depthwise_depthwise I0726 16:15:38.277716 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_5_depthwise_depthwise I0726 16:15:38.277724 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277727 10279 net.cpp:165] Memory required for data: 105036960 I0726 16:15:38.277734 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_pointwise_Conv2D I0726 16:15:38.277740 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_5_pointwise_Conv2D I0726 16:15:38.277746 10279 net.cpp:434] MobilenetV1_Conv2d_5_pointwise_Conv2D <- MobilenetV1_Conv2d_5_depthwise_depthwise I0726 16:15:38.277752 10279 net.cpp:408] MobilenetV1_Conv2d_5_pointwise_Conv2D -> MobilenetV1_Conv2d_5_pointwise_Conv2D I0726 16:15:38.277793 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_5_pointwise_Conv2D I0726 16:15:38.277803 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277807 10279 net.cpp:165] Memory required for data: 106868640 I0726 16:15:38.277814 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277822 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277827 10279 net.cpp:434] MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_5_pointwise_Conv2D I0726 16:15:38.277834 10279 net.cpp:408] MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277851 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277858 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277863 10279 net.cpp:165] Memory required for data: 108700320 I0726 16:15:38.277869 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277878 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277884 10279 net.cpp:434] MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277889 10279 net.cpp:395] MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.277900 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277917 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.277925 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277930 10279 net.cpp:165] Memory required for data: 110532000 I0726 16:15:38.277936 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_5_pointwise_Relu I0726 16:15:38.277943 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_5_pointwise_Relu I0726 16:15:38.277948 10279 net.cpp:434] MobilenetV1_Conv2d_5_pointwise_Relu <- MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.277954 10279 net.cpp:395] MobilenetV1_Conv2d_5_pointwise_Relu -> MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.277961 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_5_pointwise_Relu I0726 16:15:38.277967 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.277972 10279 net.cpp:165] Memory required for data: 112363680 I0726 16:15:38.277976 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_depthwise_depthwise I0726 16:15:38.277992 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_6_depthwise_depthwise I0726 16:15:38.277997 10279 net.cpp:434] MobilenetV1_Conv2d_6_depthwise_depthwise <- MobilenetV1_Conv2d_5_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.278003 10279 net.cpp:408] MobilenetV1_Conv2d_6_depthwise_depthwise -> MobilenetV1_Conv2d_6_depthwise_depthwise I0726 16:15:38.278020 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_6_depthwise_depthwise I0726 16:15:38.278028 10279 net.cpp:157] Top shape: 1 192 45 53 (457920) I0726 16:15:38.278033 10279 net.cpp:165] Memory required for data: 114195360 I0726 16:15:38.278038 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_pointwise_Conv2D I0726 16:15:38.278046 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_6_pointwise_Conv2D I0726 16:15:38.278051 10279 net.cpp:434] MobilenetV1_Conv2d_6_pointwise_Conv2D <- MobilenetV1_Conv2d_6_depthwise_depthwise I0726 16:15:38.278057 10279 net.cpp:408] MobilenetV1_Conv2d_6_pointwise_Conv2D -> MobilenetV1_Conv2d_6_pointwise_Conv2D I0726 16:15:38.281857 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_6_pointwise_Conv2D I0726 16:15:38.281893 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.281905 10279 net.cpp:165] Memory required for data: 117858720 I0726 16:15:38.281918 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.281934 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.281947 10279 net.cpp:434] MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_6_pointwise_Conv2D I0726 16:15:38.281965 10279 net.cpp:408] MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282002 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282017 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282021 10279 net.cpp:165] Memory required for data: 121522080 I0726 16:15:38.282032 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282044 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282052 10279 net.cpp:434] MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282061 10279 net.cpp:395] MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.282078 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282101 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282111 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282117 10279 net.cpp:165] Memory required for data: 125185440 I0726 16:15:38.282138 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_6_pointwise_Relu I0726 16:15:38.282146 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_6_pointwise_Relu I0726 16:15:38.282151 10279 net.cpp:434] MobilenetV1_Conv2d_6_pointwise_Relu <- MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282160 10279 net.cpp:395] MobilenetV1_Conv2d_6_pointwise_Relu -> MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.282167 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_6_pointwise_Relu I0726 16:15:38.282174 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282179 10279 net.cpp:165] Memory required for data: 128848800 I0726 16:15:38.282184 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_depthwise_depthwise I0726 16:15:38.282193 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_depthwise_depthwise I0726 16:15:38.282199 10279 net.cpp:434] MobilenetV1_Conv2d_7_depthwise_depthwise <- MobilenetV1_Conv2d_6_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282207 10279 net.cpp:408] MobilenetV1_Conv2d_7_depthwise_depthwise -> MobilenetV1_Conv2d_7_depthwise_depthwise I0726 16:15:38.282225 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_depthwise_depthwise I0726 16:15:38.282233 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282238 10279 net.cpp:165] Memory required for data: 132512160 I0726 16:15:38.282244 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_Conv2D I0726 16:15:38.282264 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_pointwise_Conv2D I0726 16:15:38.282271 10279 net.cpp:434] MobilenetV1_Conv2d_7_pointwise_Conv2D <- MobilenetV1_Conv2d_7_depthwise_depthwise I0726 16:15:38.282280 10279 net.cpp:408] MobilenetV1_Conv2d_7_pointwise_Conv2D -> MobilenetV1_Conv2d_7_pointwise_Conv2D I0726 16:15:38.282452 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_pointwise_Conv2D I0726 16:15:38.282464 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282469 10279 net.cpp:165] Memory required for data: 136175520 I0726 16:15:38.282475 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282483 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282490 10279 net.cpp:434] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_7_pointwise_Conv2D I0726 16:15:38.282500 10279 net.cpp:408] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282519 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282527 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282531 10279 net.cpp:165] Memory required for data: 139838880 I0726 16:15:38.282539 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282546 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282553 10279 net.cpp:434] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282562 10279 net.cpp:395] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.282575 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282595 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.282605 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282611 10279 net.cpp:165] Memory required for data: 143502240 I0726 16:15:38.282619 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_Relu I0726 16:15:38.282629 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_pointwise_Relu I0726 16:15:38.282634 10279 net.cpp:434] MobilenetV1_Conv2d_7_pointwise_Relu <- MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282642 10279 net.cpp:395] MobilenetV1_Conv2d_7_pointwise_Relu -> MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.282651 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_pointwise_Relu I0726 16:15:38.282660 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282665 10279 net.cpp:165] Memory required for data: 147165600 I0726 16:15:38.282670 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split I0726 16:15:38.282680 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split I0726 16:15:38.282685 10279 net.cpp:434] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split <- MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.282694 10279 net.cpp:408] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split -> MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split_0 I0726 16:15:38.282704 10279 net.cpp:408] MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split -> MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split_1 I0726 16:15:38.282716 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split I0726 16:15:38.282724 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282730 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282737 10279 net.cpp:165] Memory required for data: 154492320 I0726 16:15:38.282742 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_depthwise_depthwise I0726 16:15:38.282752 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_8_depthwise_depthwise I0726 16:15:38.282759 10279 net.cpp:434] MobilenetV1_Conv2d_8_depthwise_depthwise <- MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split_0 I0726 16:15:38.282768 10279 net.cpp:408] MobilenetV1_Conv2d_8_depthwise_depthwise -> MobilenetV1_Conv2d_8_depthwise_depthwise I0726 16:15:38.282788 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_8_depthwise_depthwise I0726 16:15:38.282799 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.282804 10279 net.cpp:165] Memory required for data: 158155680 I0726 16:15:38.282811 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_pointwise_Conv2D I0726 16:15:38.282843 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_8_pointwise_Conv2D I0726 16:15:38.282853 10279 net.cpp:434] MobilenetV1_Conv2d_8_pointwise_Conv2D <- MobilenetV1_Conv2d_8_depthwise_depthwise I0726 16:15:38.282862 10279 net.cpp:408] MobilenetV1_Conv2d_8_pointwise_Conv2D -> MobilenetV1_Conv2d_8_pointwise_Conv2D I0726 16:15:38.283036 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_8_pointwise_Conv2D I0726 16:15:38.283051 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283056 10279 net.cpp:165] Memory required for data: 161819040 I0726 16:15:38.283064 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283074 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283082 10279 net.cpp:434] MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_8_pointwise_Conv2D I0726 16:15:38.283090 10279 net.cpp:408] MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283110 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283119 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283125 10279 net.cpp:165] Memory required for data: 165482400 I0726 16:15:38.283135 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283144 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283150 10279 net.cpp:434] MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283159 10279 net.cpp:395] MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.283172 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283195 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283205 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283210 10279 net.cpp:165] Memory required for data: 169145760 I0726 16:15:38.283218 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_8_pointwise_Relu I0726 16:15:38.283228 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_8_pointwise_Relu I0726 16:15:38.283234 10279 net.cpp:434] MobilenetV1_Conv2d_8_pointwise_Relu <- MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283242 10279 net.cpp:395] MobilenetV1_Conv2d_8_pointwise_Relu -> MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.283252 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_8_pointwise_Relu I0726 16:15:38.283260 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283265 10279 net.cpp:165] Memory required for data: 172809120 I0726 16:15:38.283272 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_depthwise_depthwise I0726 16:15:38.283282 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_9_depthwise_depthwise I0726 16:15:38.283288 10279 net.cpp:434] MobilenetV1_Conv2d_9_depthwise_depthwise <- MobilenetV1_Conv2d_8_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283296 10279 net.cpp:408] MobilenetV1_Conv2d_9_depthwise_depthwise -> MobilenetV1_Conv2d_9_depthwise_depthwise I0726 16:15:38.283325 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_9_depthwise_depthwise I0726 16:15:38.283335 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283341 10279 net.cpp:165] Memory required for data: 176472480 I0726 16:15:38.283349 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_pointwise_Conv2D I0726 16:15:38.283360 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_9_pointwise_Conv2D I0726 16:15:38.283366 10279 net.cpp:434] MobilenetV1_Conv2d_9_pointwise_Conv2D <- MobilenetV1_Conv2d_9_depthwise_depthwise I0726 16:15:38.283375 10279 net.cpp:408] MobilenetV1_Conv2d_9_pointwise_Conv2D -> MobilenetV1_Conv2d_9_pointwise_Conv2D I0726 16:15:38.283547 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_9_pointwise_Conv2D I0726 16:15:38.283560 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283566 10279 net.cpp:165] Memory required for data: 180135840 I0726 16:15:38.283574 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283584 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283591 10279 net.cpp:434] MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_9_pointwise_Conv2D I0726 16:15:38.283601 10279 net.cpp:408] MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283620 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283628 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283634 10279 net.cpp:165] Memory required for data: 183799200 I0726 16:15:38.283655 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283668 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283674 10279 net.cpp:434] MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283680 10279 net.cpp:395] MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.283694 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283715 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.283723 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283730 10279 net.cpp:165] Memory required for data: 187462560 I0726 16:15:38.283740 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_9_pointwise_Relu I0726 16:15:38.283748 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_9_pointwise_Relu I0726 16:15:38.283756 10279 net.cpp:434] MobilenetV1_Conv2d_9_pointwise_Relu <- MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283763 10279 net.cpp:395] MobilenetV1_Conv2d_9_pointwise_Relu -> MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.283772 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_9_pointwise_Relu I0726 16:15:38.283782 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283787 10279 net.cpp:165] Memory required for data: 191125920 I0726 16:15:38.283793 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_depthwise_depthwise I0726 16:15:38.283802 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_10_depthwise_depthwise I0726 16:15:38.283809 10279 net.cpp:434] MobilenetV1_Conv2d_10_depthwise_depthwise <- MobilenetV1_Conv2d_9_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.283818 10279 net.cpp:408] MobilenetV1_Conv2d_10_depthwise_depthwise -> MobilenetV1_Conv2d_10_depthwise_depthwise I0726 16:15:38.283838 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_10_depthwise_depthwise I0726 16:15:38.283848 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.283852 10279 net.cpp:165] Memory required for data: 194789280 I0726 16:15:38.283859 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_pointwise_Conv2D I0726 16:15:38.283865 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_10_pointwise_Conv2D I0726 16:15:38.283872 10279 net.cpp:434] MobilenetV1_Conv2d_10_pointwise_Conv2D <- MobilenetV1_Conv2d_10_depthwise_depthwise I0726 16:15:38.283881 10279 net.cpp:408] MobilenetV1_Conv2d_10_pointwise_Conv2D -> MobilenetV1_Conv2d_10_pointwise_Conv2D I0726 16:15:38.284054 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_10_pointwise_Conv2D I0726 16:15:38.284066 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284072 10279 net.cpp:165] Memory required for data: 198452640 I0726 16:15:38.284080 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284090 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284097 10279 net.cpp:434] MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_10_pointwise_Conv2D I0726 16:15:38.284106 10279 net.cpp:408] MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284127 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284135 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284142 10279 net.cpp:165] Memory required for data: 202116000 I0726 16:15:38.284158 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284168 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284175 10279 net.cpp:434] MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284184 10279 net.cpp:395] MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.284198 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284219 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284229 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284235 10279 net.cpp:165] Memory required for data: 205779360 I0726 16:15:38.284243 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_10_pointwise_Relu I0726 16:15:38.284253 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_10_pointwise_Relu I0726 16:15:38.284260 10279 net.cpp:434] MobilenetV1_Conv2d_10_pointwise_Relu <- MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284267 10279 net.cpp:395] MobilenetV1_Conv2d_10_pointwise_Relu -> MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.284276 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_10_pointwise_Relu I0726 16:15:38.284284 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284291 10279 net.cpp:165] Memory required for data: 209442720 I0726 16:15:38.284296 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_depthwise_depthwise I0726 16:15:38.284307 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_11_depthwise_depthwise I0726 16:15:38.284313 10279 net.cpp:434] MobilenetV1_Conv2d_11_depthwise_depthwise <- MobilenetV1_Conv2d_10_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284322 10279 net.cpp:408] MobilenetV1_Conv2d_11_depthwise_depthwise -> MobilenetV1_Conv2d_11_depthwise_depthwise I0726 16:15:38.284343 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_11_depthwise_depthwise I0726 16:15:38.284353 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284358 10279 net.cpp:165] Memory required for data: 213106080 I0726 16:15:38.284365 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_pointwise_Conv2D I0726 16:15:38.284375 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_11_pointwise_Conv2D I0726 16:15:38.284382 10279 net.cpp:434] MobilenetV1_Conv2d_11_pointwise_Conv2D <- MobilenetV1_Conv2d_11_depthwise_depthwise I0726 16:15:38.284391 10279 net.cpp:408] MobilenetV1_Conv2d_11_pointwise_Conv2D -> MobilenetV1_Conv2d_11_pointwise_Conv2D I0726 16:15:38.284569 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_11_pointwise_Conv2D I0726 16:15:38.284580 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284586 10279 net.cpp:165] Memory required for data: 216769440 I0726 16:15:38.284595 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284605 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284611 10279 net.cpp:434] MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm <- MobilenetV1_Conv2d_11_pointwise_Conv2D I0726 16:15:38.284621 10279 net.cpp:408] MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm -> MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284641 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284649 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284656 10279 net.cpp:165] Memory required for data: 220432800 I0726 16:15:38.284665 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284675 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284682 10279 net.cpp:434] MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale <- MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284689 10279 net.cpp:395] MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale -> MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.284703 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284723 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm_scale I0726 16:15:38.284732 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284737 10279 net.cpp:165] Memory required for data: 224096160 I0726 16:15:38.284746 10279 layer_factory.hpp:77] Creating layer MobilenetV1_Conv2d_11_pointwise_Relu I0726 16:15:38.284754 10279 net.cpp:100] Creating Layer MobilenetV1_Conv2d_11_pointwise_Relu I0726 16:15:38.284760 10279 net.cpp:434] MobilenetV1_Conv2d_11_pointwise_Relu <- MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284770 10279 net.cpp:395] MobilenetV1_Conv2d_11_pointwise_Relu -> MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm (in-place) I0726 16:15:38.284777 10279 net.cpp:150] Setting up MobilenetV1_Conv2d_11_pointwise_Relu I0726 16:15:38.284785 10279 net.cpp:157] Top shape: 1 384 45 53 (915840) I0726 16:15:38.284791 10279 net.cpp:165] Memory required for data: 227759520 I0726 16:15:38.284797 10279 layer_factory.hpp:77] Creating layer feat_concat I0726 16:15:38.284807 10279 net.cpp:100] Creating Layer feat_concat I0726 16:15:38.284813 10279 net.cpp:434] feat_concat <- Conv2d_3_pool I0726 16:15:38.284821 10279 net.cpp:434] feat_concat <- MobilenetV1_Conv2d_7_pointwise_BatchNorm_FusedBatchNorm_MobilenetV1_Conv2d_7_pointwise_Relu_0_split_1 I0726 16:15:38.284829 10279 net.cpp:434] feat_concat <- MobilenetV1_Conv2d_11_pointwise_BatchNorm_FusedBatchNorm I0726 16:15:38.284837 10279 net.cpp:408] feat_concat -> feat_concat F0726 16:15:38.284852 10279 concat_layer.cpp:42] Check failed: top_shape[j] == bottom[i]->shape(j) (46 vs. 45) All inputs must have the same shape, except at concat_axis. *** Check failure stack trace: ***
Hi @iChiaGuo , the crash of the conversion from Tensorflow mobilenet to caffe is a known issue, you can refer the test to get it. And we have no idea about the crash. We will figure it out when we have bandwidth. Thanks.
Hi, I am facing a different issue with Openpose using VGG base network. Can you suggest what the issue might be. Please find the error I receive below.
Traceback (most recent call last):
File "/usr/local/bin/mmconvert", line 11, in
Hi I also got the tensorflowtocaffe issue with the error log 'All inputs must have the same shape, except at concat_axis'. Have you already fixed it?
