| [DNNMark] |
| run_mode=composed |
| |
| [Convolution] |
| name=block1_1_conv |
| n=$N |
| c=3 |
| h=32 |
| w=32 |
| previous_layer=null |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=64 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block1_1_conv |
| name=block1_1_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block1_1_bn |
| name=block1_1_relu |
| activation_mode=relu |
| |
| [Dropout] |
| previous_layer=block1_1_relu |
| name=dropout1_1 |
| dropout_probability=.3 |
| random_seed=0 |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout1_1 |
| name=block1_2_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=64 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block1_2_conv |
| name=block1_2_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block1_2_bn |
| name=block1_2_relu |
| activation_mode=relu |
| |
| |
| [Pooling] |
| previous_layer=block1_2_relu |
| name=pool1_2 |
| pool_mode=max |
| kernel_size=2 |
| pad=0 |
| stride=2 |
| |
| |
| [Convolution] |
| previous_layer=pool1_2 |
| name=block2_1_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=128 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block2_1_conv |
| name=block2_1_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block2_1_bn |
| name=block2_1_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block2_1_relu |
| name=dropout2_1 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| [Convolution] |
| previous_layer=dropout2_1 |
| name=block2_2_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=128 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block2_2_conv |
| name=block2_2_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block2_2_bn |
| name=block2_2_relu |
| activation_mode=relu |
| |
| |
| [Pooling] |
| previous_layer=block2_2_relu |
| name=pool2_2 |
| pool_mode=max |
| kernel_size=2 |
| pad=0 |
| stride=2 |
| |
| |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=pool2_2 |
| name=block3_1_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=256 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block3_1_conv |
| name=block3_1_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block3_1_bn |
| name=block3_1_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block3_1_relu |
| name=dropout3_1 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout3_1 |
| name=block3_2_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=256 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block3_2_conv |
| name=block3_2_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block3_2_bn |
| name=block3_2_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block3_2_relu |
| name=dropout3_2 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout3_2 |
| name=block3_3_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=256 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block3_3_conv |
| name=block3_3_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block3_3_bn |
| name=block3_3_relu |
| activation_mode=relu |
| |
| |
| [Pooling] |
| previous_layer=block3_3_relu |
| name=pool3_3 |
| pool_mode=max |
| kernel_size=2 |
| pad=0 |
| stride=2 |
| |
| |
| |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=pool3_3 |
| name=block4_1_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block4_1_conv |
| name=block4_1_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block4_1_bn |
| name=block4_1_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block4_1_relu |
| name=dropout4_1 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout4_1 |
| name=block4_2_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block4_2_conv |
| name=block4_2_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block4_2_bn |
| name=block4_2_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block4_2_relu |
| name=dropout4_2 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout4_2 |
| name=block4_3_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block4_3_conv |
| name=block4_3_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block4_3_bn |
| name=block4_3_relu |
| activation_mode=relu |
| |
| |
| [Pooling] |
| previous_layer=block4_3_relu |
| name=pool4_3 |
| pool_mode=max |
| kernel_size=2 |
| pad=0 |
| stride=2 |
| |
| |
| |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=pool4_3 |
| name=block5_1_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block5_1_conv |
| name=block5_1_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block5_1_bn |
| name=block5_1_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block5_1_relu |
| name=dropout5_1 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout5_1 |
| name=block5_2_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block5_2_conv |
| name=block5_2_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block5_2_bn |
| name=block5_2_relu |
| activation_mode=relu |
| |
| |
| [Dropout] |
| previous_layer=block5_2_relu |
| name=dropout5_2 |
| dropout_probability=.4 |
| random_seed=0 |
| |
| |
| |
| |
| [Convolution] |
| previous_layer=dropout5_2 |
| name=block5_3_conv |
| conv_mode=convolution |
| kernel_size=3 |
| num_output=512 |
| pad=1 |
| stride=1 |
| conv_fwd_pref=fastest |
| conv_bwd_filter_pref=fastest |
| conv_bwd_data_pref=fastest |
| $CUDNN_CBFA |
| $CUDNN_CBDA |
| |
| [BatchNorm] |
| previous_layer=block5_3_conv |
| name=block5_3_bn |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=block5_3_bn |
| name=block5_3_relu |
| activation_mode=relu |
| |
| |
| [Pooling] |
| previous_layer=block5_3_relu |
| name=pool5_3 |
| pool_mode=max |
| kernel_size=2 |
| pad=0 |
| stride=2 |
| |
| |
| |
| [Dropout] |
| previous_layer=pool5_3 |
| name=dropout5_3 |
| dropout_probability=.5 |
| random_seed=0 |
| |
| |
| [FullyConnected] |
| previous_layer=dropout5_3 |
| name=fc1 |
| num_output=512 |
| |
| |
| [BatchNorm] |
| previous_layer=fc1 |
| name=bn_fc1 |
| batchnorm_mode=per_activation |
| save_intermediates=true |
| exp_avg_factor=1 |
| epsilon=2e-5 |
| |
| [Activation] |
| previous_layer=bn_fc1 |
| name=relu_fc1 |
| activation_mode=relu |
| |
| |
| |
| [Dropout] |
| previous_layer=relu_fc1 |
| name=dropout_fc1 |
| dropout_probability=.5 |
| random_seed=0 |
| |
| |
| [FullyConnected] |
| previous_layer=dropout_fc1 |
| name=fc2 |
| num_output=100 |
