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support inference performance test in benchmark
Change-Id: Idf4fbc6555d757913ef5f4e8a72a92aa1b7d5d24 Change-Id: Idf4fbc6555d757913ef5f4e8a72a92aa1b7d5d24 Change-Id: Idf4fbc6555d757913ef5f4e8a72a92aa1b7d5d24 Change-Id: Idf4fbc6555d757913ef5f4e8a72a92aa1b7d5d24 Change-Id: Idf4fbc6555d757913ef5f4e8a72a92aa1b7d5d24
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models/intel_optimized_models/benchmark/alexnet/deploy.prototxt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,348 @@ | ||
| name: "AlexNet" | ||
| layer { | ||
| name: "data" | ||
| type: "DummyData" | ||
| top: "data" | ||
| dummy_data_param { | ||
| shape: { dim: 256 dim: 3 dim: 227 dim: 227 } | ||
| data_filler { | ||
| type: "constant" | ||
| value: 0.01 | ||
| } | ||
| } | ||
| } | ||
|
|
||
| layer { | ||
| name: "conv1" | ||
| type: "Convolution" | ||
| bottom: "data" | ||
| top: "conv1" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| convolution_param { | ||
| num_output: 96 | ||
| kernel_size: 11 | ||
| stride: 4 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu1" | ||
| type: "ReLU" | ||
| bottom: "conv1" | ||
| top: "conv1" | ||
| } | ||
| layer { | ||
| name: "norm1" | ||
| type: "LRN" | ||
| bottom: "conv1" | ||
| top: "norm1" | ||
| lrn_param { | ||
| local_size: 5 | ||
| alpha: 0.0001 | ||
| beta: 0.75 | ||
| } | ||
| } | ||
| layer { | ||
| name: "pool1" | ||
| type: "Pooling" | ||
| bottom: "norm1" | ||
| top: "pool1" | ||
| pooling_param { | ||
| pool: MAX | ||
| kernel_size: 3 | ||
| stride: 2 | ||
| } | ||
| } | ||
| layer { | ||
| name: "conv2" | ||
| type: "Convolution" | ||
| bottom: "pool1" | ||
| top: "conv2" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| convolution_param { | ||
| num_output: 256 | ||
| pad: 2 | ||
| kernel_size: 5 | ||
| group: 2 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0.1 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu2" | ||
| type: "ReLU" | ||
| bottom: "conv2" | ||
| top: "conv2" | ||
| } | ||
| layer { | ||
| name: "norm2" | ||
| type: "LRN" | ||
| bottom: "conv2" | ||
| top: "norm2" | ||
| lrn_param { | ||
| local_size: 5 | ||
| alpha: 0.0001 | ||
| beta: 0.75 | ||
| } | ||
| } | ||
| layer { | ||
| name: "pool2" | ||
| type: "Pooling" | ||
| bottom: "norm2" | ||
| top: "pool2" | ||
| pooling_param { | ||
| pool: MAX | ||
| kernel_size: 3 | ||
| stride: 2 | ||
| } | ||
| } | ||
| layer { | ||
| name: "conv3" | ||
| type: "Convolution" | ||
| bottom: "pool2" | ||
| top: "conv3" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| convolution_param { | ||
| num_output: 384 | ||
| pad: 1 | ||
| kernel_size: 3 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu3" | ||
| type: "ReLU" | ||
| bottom: "conv3" | ||
| top: "conv3" | ||
| } | ||
| layer { | ||
| name: "conv4" | ||
| type: "Convolution" | ||
| bottom: "conv3" | ||
| top: "conv4" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| convolution_param { | ||
| num_output: 384 | ||
| pad: 1 | ||
| kernel_size: 3 | ||
| group: 2 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0.1 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu4" | ||
| type: "ReLU" | ||
| bottom: "conv4" | ||
| top: "conv4" | ||
| } | ||
| layer { | ||
| name: "conv5" | ||
| type: "Convolution" | ||
| bottom: "conv4" | ||
| top: "conv5" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| convolution_param { | ||
| num_output: 256 | ||
| pad: 1 | ||
| kernel_size: 3 | ||
| group: 2 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0.1 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu5" | ||
| type: "ReLU" | ||
| bottom: "conv5" | ||
| top: "conv5" | ||
| } | ||
| layer { | ||
| name: "pool5" | ||
| type: "Pooling" | ||
| bottom: "conv5" | ||
| top: "pool5" | ||
| pooling_param { | ||
| pool: MAX | ||
| kernel_size: 3 | ||
| stride: 2 | ||
| } | ||
| } | ||
| layer { | ||
| name: "fc6" | ||
| type: "InnerProduct" | ||
| bottom: "pool5" | ||
| top: "fc6" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| inner_product_param { | ||
| num_output: 4096 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.005 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0.1 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu6" | ||
| type: "ReLU" | ||
| bottom: "fc6" | ||
| top: "fc6" | ||
| } | ||
| layer { | ||
| name: "drop6" | ||
| type: "Dropout" | ||
| bottom: "fc6" | ||
| top: "fc6" | ||
| dropout_param { | ||
| dropout_ratio: 0.5 | ||
| } | ||
| } | ||
| layer { | ||
| name: "fc7" | ||
| type: "InnerProduct" | ||
| bottom: "fc6" | ||
| top: "fc7" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| inner_product_param { | ||
| num_output: 4096 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.005 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0.1 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "relu7" | ||
| type: "ReLU" | ||
| bottom: "fc7" | ||
| top: "fc7" | ||
| } | ||
| layer { | ||
| name: "drop7" | ||
| type: "Dropout" | ||
| bottom: "fc7" | ||
| top: "fc7" | ||
| dropout_param { | ||
| dropout_ratio: 0.5 | ||
| } | ||
| } | ||
| layer { | ||
| name: "fc8" | ||
| type: "InnerProduct" | ||
| bottom: "fc7" | ||
| top: "fc8" | ||
| param { | ||
| lr_mult: 1 | ||
| decay_mult: 1 | ||
| } | ||
| param { | ||
| lr_mult: 2 | ||
| decay_mult: 0 | ||
| } | ||
| inner_product_param { | ||
| num_output: 1000 | ||
| weight_filler { | ||
| type: "gaussian" | ||
| std: 0.01 | ||
| } | ||
| bias_filler { | ||
| type: "constant" | ||
| value: 0 | ||
| } | ||
| } | ||
| } | ||
| layer { | ||
| name: "prob" | ||
| type: "Softmax" | ||
| bottom: "fc8" | ||
| top: "prob" | ||
| } |
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