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April 26, 2017 00:21
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| layer { | |
| name: "Image1" | |
| type: "ImageData" | |
| top: "img0" | |
| include { | |
| phase: TRAIN | |
| } | |
| image_data_param { | |
| source: "img1_list.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Image2" | |
| type: "ImageData" | |
| top: "img1" | |
| include { | |
| phase: TRAIN | |
| } | |
| image_data_param { | |
| source: "img2_list.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Flow" | |
| type: "FloData" | |
| top: "flow_gt_aug" | |
| include { | |
| phase: TRAIN | |
| } | |
| image_data_param { | |
| source: "flo_list.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Image1" | |
| type: "ImageData" | |
| top: "img0" | |
| include { | |
| phase: TEST | |
| } | |
| image_data_param { | |
| source: "img1_list_test.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Image2" | |
| type: "ImageData" | |
| top: "img1" | |
| include { | |
| phase: TEST | |
| } | |
| image_data_param { | |
| source: "img2_list_test.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Flow" | |
| type: "FloData" | |
| top: "flow_gt_aug" | |
| include { | |
| phase: TEST | |
| } | |
| image_data_param { | |
| source: "flo_list_test.txt" | |
| root_folder: "./" | |
| batch_size: 8 | |
| } | |
| } | |
| layer { | |
| name: "Mean1" | |
| type: "Mean" | |
| bottom: "img0" | |
| top: "img0_aug" | |
| mean_param { | |
| operation: SUBTRACT | |
| input_scale: 0.0039216 | |
| value: 0.411451 | |
| value: 0.432060 | |
| value: 0.450141 | |
| } | |
| } | |
| layer { | |
| name: "Mean2" | |
| type: "Mean" | |
| bottom: "img1" | |
| top: "img1_aug" | |
| mean_param { | |
| operation: SUBTRACT | |
| input_scale: 0.0039216 | |
| value: 0.410602 | |
| value: 0.431021 | |
| value: 0.448553 | |
| } | |
| } | |
| layer { | |
| name: "Eltwise3" | |
| type: "Eltwise" | |
| bottom: "flow_gt_aug" | |
| top: "scaled_flow_gt" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.05 | |
| } | |
| } | |
| layer { | |
| name: "Concat1" | |
| type: "Concat" | |
| bottom: "img0_aug" | |
| bottom: "img1_aug" | |
| top: "input" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "input" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "conv2" | |
| top: "conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU4" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU5" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU6" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU7" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Convolution" | |
| bottom: "conv5" | |
| top: "conv5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU8" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU9" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU10" | |
| type: "ReLU" | |
| bottom: "conv6_1" | |
| top: "conv6_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "Convolution1" | |
| type: "Convolution" | |
| bottom: "conv6_1" | |
| top: "predict_flow6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Downsample1" | |
| type: "Downsample" | |
| bottom: "scaled_flow_gt" | |
| bottom: "predict_flow6" | |
| top: "blob24" | |
| } | |
| layer { | |
| name: "flow_loss6" | |
| type: "L1Loss" | |
| bottom: "predict_flow6" | |
| bottom: "blob24" | |
| top: "flow_loss6" | |
| loss_weight: 0.32 | |
| l1_loss_param { | |
| l2_per_location: true | |
| } | |
| } | |
| layer { | |
| name: "deconv5" | |
| type: "Deconvolution" | |
| bottom: "conv6_1" | |
| top: "deconv5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU11" | |
| type: "ReLU" | |
| bottom: "deconv5" | |
| top: "deconv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow6to5" | |
| type: "Deconvolution" | |
| bottom: "predict_flow6" | |
| top: "upsampled_flow6_to_5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat2" | |
| type: "Concat" | |
| bottom: "conv5_1" | |
| bottom: "deconv5" | |
| bottom: "upsampled_flow6_to_5" | |
| top: "concat5" | |
| } | |
| layer { | |
| name: "Convolution2" | |
| type: "Convolution" | |
| bottom: "concat5" | |
| top: "predict_flow5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Downsample2" | |
| type: "Downsample" | |
| bottom: "scaled_flow_gt" | |
| bottom: "predict_flow5" | |
| top: "blob29" | |
| } | |
| layer { | |
| name: "flow_loss5" | |
| type: "L1Loss" | |
| bottom: "predict_flow5" | |
| bottom: "blob29" | |
| top: "flow_loss5" | |
| loss_weight: 0.08 | |
| l1_loss_param { | |
| l2_per_location: true | |
| } | |
| } | |
| layer { | |
| name: "deconv4" | |
| type: "Deconvolution" | |
| bottom: "concat5" | |
| top: "deconv4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU12" | |
| type: "ReLU" | |
| bottom: "deconv4" | |
| top: "deconv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow5to4" | |
| type: "Deconvolution" | |
| bottom: "predict_flow5" | |
| top: "upsampled_flow5_to_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat3" | |
| type: "Concat" | |
| bottom: "conv4_1" | |
| bottom: "deconv4" | |
| bottom: "upsampled_flow5_to_4" | |
| top: "concat4" | |
| } | |
| layer { | |
| name: "Convolution3" | |
| type: "Convolution" | |
| bottom: "concat4" | |
| top: "predict_flow4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Downsample3" | |
| type: "Downsample" | |
| bottom: "scaled_flow_gt" | |
| bottom: "predict_flow4" | |
| top: "blob34" | |
| } | |
| layer { | |
| name: "flow_loss4" | |
| type: "L1Loss" | |
| bottom: "predict_flow4" | |
| bottom: "blob34" | |
| top: "flow_loss4" | |
| loss_weight: 0.02 | |
| l1_loss_param { | |
| l2_per_location: true | |
| } | |
| } | |
| layer { | |
| name: "deconv3" | |
| type: "Deconvolution" | |
| bottom: "concat4" | |
| top: "deconv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU13" | |
| type: "ReLU" | |
| bottom: "deconv3" | |
| top: "deconv3" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow4to3" | |
| type: "Deconvolution" | |
| bottom: "predict_flow4" | |
| top: "upsampled_flow4_to_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat4" | |
| type: "Concat" | |
| bottom: "conv3_1" | |
| bottom: "deconv3" | |
| bottom: "upsampled_flow4_to_3" | |
| top: "concat3" | |
| } | |
| layer { | |
| name: "Convolution4" | |
| type: "Convolution" | |
| bottom: "concat3" | |
| top: "predict_flow3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Downsample4" | |
| type: "Downsample" | |
| bottom: "scaled_flow_gt" | |
| bottom: "predict_flow3" | |
| top: "blob39" | |
| } | |
| layer { | |
| name: "flow_loss3" | |
| type: "L1Loss" | |
| bottom: "predict_flow3" | |
| bottom: "blob39" | |
| top: "flow_loss3" | |
| loss_weight: 0.01 | |
| l1_loss_param { | |
| l2_per_location: true | |
| } | |
| } | |
| layer { | |
| name: "deconv2" | |
| type: "Deconvolution" | |
| bottom: "concat3" | |
| top: "deconv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU14" | |
| type: "ReLU" | |
| bottom: "deconv2" | |
| top: "deconv2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow3to2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow3" | |
| top: "upsampled_flow3_to_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat5" | |
| type: "Concat" | |
| bottom: "conv2" | |
| bottom: "deconv2" | |
| bottom: "upsampled_flow3_to_2" | |
| top: "concat2" | |
| } | |
| layer { | |
| name: "Convolution5" | |
| type: "Convolution" | |
| bottom: "concat2" | |
| top: "predict_flow2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Downsample5" | |
| type: "Downsample" | |
| bottom: "scaled_flow_gt" | |
| bottom: "predict_flow2" | |
| top: "blob44" | |
| } | |
| layer { | |
| name: "flow_loss2" | |
| type: "L1Loss" | |
| bottom: "predict_flow2" | |
| bottom: "blob44" | |
| top: "flow_loss2" | |
| loss_weight: 0.005 | |
| l1_loss_param { | |
| l2_per_location: true | |
| } | |
| } | |
| # layer { | |
| # name: "Eltwise4" | |
| # type: "Eltwise" | |
| # bottom: "predict_flow2" | |
| # top: "final_predict_flow" | |
| # eltwise_param { | |
| # operation: SUM | |
| # coeff: 20.0 | |
| # } | |
| # } | |
| # layer { | |
| # name: "Out1" | |
| # type: "HDF5Output" | |
| # bottom: "img0_aug" | |
| # bottom: "img1_aug" | |
| # hdf5_output_param { | |
| # file_name: "input_images.hdf5" | |
| # } | |
| # } | |
| # layer { | |
| # name: "Out2" | |
| # type: "HDF5Output" | |
| # bottom: "flow_gt_aug" | |
| # bottom: "predict_flow2" | |
| # hdf5_output_param { | |
| # file_name: "input_flow.hdf5" | |
| # } | |
| # } |
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