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‎python/paddle/trainer_config_helpers/tests/configs/img_layers.protostr

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type: "nn"
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layers {
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name: "image"
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type: "data"
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size: 65536
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active_type: ""
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}
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layers {
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name: "__conv_0__"
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type: "exconv"
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size: 3297856
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active_type: ""
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inputs {
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input_layer_name: "image"
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input_parameter_name: "___conv_0__.w0"
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conv_conf {
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filter_size: 32
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channels: 1
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stride: 1
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padding: 1
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groups: 1
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filter_channels: 1
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output_x: 227
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img_size: 256
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caffe_mode: true
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filter_size_y: 32
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padding_y: 1
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stride_y: 1
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}
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}
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bias_parameter_name: "___conv_0__.wbias"
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num_filters: 64
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shared_biases: true
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}
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layers {
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name: "__batch_norm_0__"
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type: "batch_norm"
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size: 3297856
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active_type: "relu"
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inputs {
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input_layer_name: "__conv_0__"
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input_parameter_name: "___batch_norm_0__.w0"
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image_conf {
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channels: 64
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img_size: 227
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}
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}
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inputs {
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input_layer_name: "__conv_0__"
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input_parameter_name: "___batch_norm_0__.w1"
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}
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inputs {
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input_layer_name: "__conv_0__"
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input_parameter_name: "___batch_norm_0__.w2"
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}
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bias_parameter_name: "___batch_norm_0__.wbias"
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moving_average_fraction: 0.899999976158
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}
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layers {
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name: "__crmnorm_0__"
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type: "norm"
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size: 3297856
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active_type: ""
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inputs {
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input_layer_name: "__batch_norm_0__"
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norm_conf {
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norm_type: "cmrnorm-projection"
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channels: 64
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size: 32
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scale: 0.000399999989895
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pow: 0.75
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output_x: 227
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img_size: 227
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blocked: false
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}
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}
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}
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layers {
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name: "__pool_0__"
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type: "pool"
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size: 2458624
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active_type: ""
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inputs {
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input_layer_name: "__conv_0__"
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pool_conf {
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pool_type: "max-projection"
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channels: 64
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size_x: 32
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stride: 1
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output_x: 196
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img_size: 227
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padding: 0
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size_y: 32
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stride_y: 1
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output_y: 196
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img_size_y: 227
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padding_y: 0
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}
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}
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}
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parameters {
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name: "___conv_0__.w0"
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size: 65536
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initial_mean: 0.0
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initial_std: 0.0441941730678
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initial_strategy: 0
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initial_smart: false
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}
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parameters {
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name: "___conv_0__.wbias"
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size: 64
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initial_mean: 0.0
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initial_std: 0.0
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dims: 64
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dims: 1
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initial_strategy: 0
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initial_smart: false
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}
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parameters {
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name: "___batch_norm_0__.w0"
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size: 64
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initial_mean: 1.0
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initial_std: 0.0
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initial_strategy: 0
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initial_smart: false
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}
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parameters {
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name: "___batch_norm_0__.w1"
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size: 64
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initial_mean: 0.0
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initial_std: 0.0
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dims: 1
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dims: 64
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initial_strategy: 0
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initial_smart: false
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is_static: true
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is_shared: true
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}
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parameters {
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name: "___batch_norm_0__.w2"
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size: 64
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initial_mean: 0.0
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initial_std: 0.0
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dims: 1
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dims: 64
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initial_strategy: 0
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initial_smart: false
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is_static: true
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is_shared: true
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}
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parameters {
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name: "___batch_norm_0__.wbias"
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size: 64
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initial_mean: 0.0
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initial_std: 0.0
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dims: 1
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dims: 64
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initial_strategy: 0
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initial_smart: false
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}
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input_layer_names: "image"
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output_layer_names: "__pool_0__"
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output_layer_names: "__crmnorm_0__"
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sub_models {
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name: "root"
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layer_names: "image"
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layer_names: "__conv_0__"
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layer_names: "__batch_norm_0__"
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layer_names: "__crmnorm_0__"
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layer_names: "__pool_0__"
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input_layer_names: "image"
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output_layer_names: "__pool_0__"
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output_layer_names: "__crmnorm_0__"
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is_recurrent_layer_group: false
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}
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‎python/paddle/trainer_config_helpers/tests/configs/last_first_seq.protostr

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type: "nn"
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layers {
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name: "data"
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type: "data"
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size: 30
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active_type: ""
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}
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layers {
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name: "__first_seq_0__"
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type: "seqlastins"
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size: 30
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active_type: "linear"
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inputs {
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input_layer_name: "data"
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}
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select_first: true
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trans_type: "seq"
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}
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layers {
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name: "__first_seq_1__"
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type: "seqlastins"
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size: 30
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active_type: "linear"
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inputs {
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input_layer_name: "data"
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}
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select_first: true
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trans_type: "non-seq"
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}
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layers {
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name: "__last_seq_0__"
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type: "seqlastins"
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size: 30
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active_type: "linear"
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inputs {
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input_layer_name: "data"
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}
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trans_type: "seq"
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}
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layers {
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name: "__last_seq_1__"
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type: "seqlastins"
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size: 30
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active_type: "linear"
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inputs {
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input_layer_name: "data"
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}
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trans_type: "non-seq"
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}
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input_layer_names: "data"
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output_layer_names: "__first_seq_0__"
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output_layer_names: "__first_seq_1__"
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output_layer_names: "__last_seq_0__"
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output_layer_names: "__last_seq_1__"
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sub_models {
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name: "root"
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layer_names: "data"
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layer_names: "__first_seq_0__"
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layer_names: "__first_seq_1__"
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layer_names: "__last_seq_0__"
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layer_names: "__last_seq_1__"
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input_layer_names: "data"
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output_layer_names: "__first_seq_0__"
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output_layer_names: "__first_seq_1__"
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output_layer_names: "__last_seq_0__"
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output_layer_names: "__last_seq_1__"
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is_recurrent_layer_group: false
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}
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