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FancyNet v3
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| # Enter your network definition here. | |
| # Use Shift+Enter to update the visualization.name: "FancyNet" | |
| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 4 | |
| dim: 255 | |
| dim: 255 | |
| } | |
| layer { | |
| name: "conv1/7x7_s2" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1/7x7_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/relu_7x7" | |
| type: "ReLU" | |
| bottom: "conv1/7x7_s2" | |
| top: "conv1/7x7_s2" | |
| } | |
| layer { | |
| name: "pool1/3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv1/7x7_s2" | |
| top: "pool1/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv2/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool1/3x3_s2" | |
| top: "conv2/3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "conv2/3x3_reduce" | |
| top: "conv2/3x3_reduce" | |
| } | |
| layer { | |
| name: "conv2/3x3" | |
| type: "Convolution" | |
| bottom: "conv2/3x3_reduce" | |
| top: "conv2/3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu_3x3" | |
| type: "ReLU" | |
| bottom: "conv2/3x3" | |
| top: "conv2/3x3" | |
| } | |
| layer { | |
| name: "SUPRESS_1" | |
| type: "Convolution" | |
| bottom: "conv2/3x3" | |
| top: "SUPRESS_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool2/3x3_s2" | |
| type: "Pooling" | |
| bottom: "SUPRESS_1" | |
| top: "pool2/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/1x1" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_3a/1x1" | |
| top: "inception_3a/1x1" | |
| } | |
| layer { | |
| name: "inception_3a/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3a/3x3_reduce" | |
| top: "inception_3a/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_3a/3x3" | |
| type: "Convolution" | |
| bottom: "inception_3a/3x3_reduce" | |
| top: "inception_3a/3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_3a/3x3" | |
| top: "inception_3a/3x3" | |
| } | |
| layer { | |
| name: "inception_3a/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/5x5_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3a/5x5_reduce" | |
| top: "inception_3a/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_3a/5x5" | |
| type: "Convolution" | |
| bottom: "inception_3a/5x5_reduce" | |
| top: "inception_3a/5x5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_3a/5x5" | |
| top: "inception_3a/5x5" | |
| } | |
| layer { | |
| name: "inception_3a/pool" | |
| type: "Pooling" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_3a/pool" | |
| top: "inception_3a/pool_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_3a/pool_proj" | |
| top: "inception_3a/pool_proj" | |
| } | |
| layer { | |
| name: "inception_3a/output" | |
| type: "Concat" | |
| bottom: "inception_3a/1x1" | |
| bottom: "inception_3a/3x3" | |
| bottom: "inception_3a/5x5" | |
| bottom: "inception_3a/pool_proj" | |
| top: "inception_3a/output" | |
| } | |
| # Conversion HW -> SW | |
| layer { | |
| name: "pool1/norm1" | |
| type: "LRN" | |
| # bottom: "PLACEHOLDER" | |
| bottom: "inception_3a/output" | |
| top: "pool1/norm1" | |
| lrn_param { | |
| # local_size: 5 | |
| # alpha: 0.0001 | |
| # beta: 0.75 | |
| local_size: 1 | |
| alpha: 0 | |
| beta: 1 | |
| } | |
| } | |
| # | |
| # Conversion SW -> HW | |
| # | |
| # layer { | |
| # name: "loss3/classifier" | |
| # type: "InnerProduct" | |
| # bottom: "data" | |
| # top: "loss3/classifier" | |
| # param { | |
| # lr_mult: 1 | |
| # decay_mult: 1 | |
| # } | |
| # param { | |
| # lr_mult: 2 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 100 | |
| # weight_filler { | |
| # type: "xavier" | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0 | |
| # } | |
| # } | |
| # } | |
| # Hardware Layer | |
| layer { | |
| name: "glob_pool" | |
| type: "Pooling" | |
| bottom: "pool1/norm1" | |
| top: "glob_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 32 | |
| stride: 1 | |
| } | |
| } |
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