simple_net.prototxt

name: "SimpleTriNet"

layer {
	name: "data"
	type: "Module"
	top: "anchor"
	top: "negative"
	top: "positive"
	module_param {
		module: "triplet_layers"
		type: "MnistData"
		param_str: "{ 'data': 'data/mnist_train_data.bin', 'labels': 'data/mnist_train_labels.bin', 'batch_size': 64 }"
	}
}

########### Anchor

layer {
	name: "conv1"
	type: "Convolution"
	bottom: "anchor"
	top: "conv1"
	param {
		name: "conv1_w"
		lr_mult: 1
	}
	param {
		name: "conv1_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 20
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool1"
	type: "Pooling"
	bottom: "conv1"
	top: "pool1"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "conv2"
	type: "Convolution"
	bottom: "pool1"
	top: "conv2"
	param {
		name: "conv2_w"
		lr_mult: 1
	}
	param {
		name: "conv2_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 50
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool2"
	type: "Pooling"
	bottom: "conv2"
	top: "pool2"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "ip1"
	type: "InnerProduct"
	bottom: "pool2"
	top: "ip1"
	param {
		name: "ip1_w"
		lr_mult: 1
	}
	param {
		name: "ip1_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 500
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "relu1"
	type: "ReLU"
	bottom: "ip1"
	top: "ip1"
}

layer {
	name: "ip2"
	type: "InnerProduct"
	bottom: "ip1"
	top: "ip2"
	param {
		name: "ip2_w"
		lr_mult: 1
	}
	param {
		name: "ip2_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 10
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "feat"
	type: "InnerProduct"
	bottom: "ip2"
	top: "feat"
	param {
		name: "feat_w"
		lr_mult: 1
	}
	param {
		name: "feat_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 2
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

########### Positive

layer {
	name: "conv1_p"
	type: "Convolution"
	bottom: "positive"
	top: "conv1_p"
	param {
		name: "conv1_w"
		lr_mult: 1
	}
	param {
		name: "conv1_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 20
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool1_p"
	type: "Pooling"
	bottom: "conv1_p"
	top: "pool1_p"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "conv2_p"
	type: "Convolution"
	bottom: "pool1_p"
	top: "conv2_p"
	param {
		name: "conv2_w"
		lr_mult: 1
	}
	param {
		name: "conv2_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 50
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool2_p"
	type: "Pooling"
	bottom: "conv2_p"
	top: "pool2_p"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "ip1_p"
	type: "InnerProduct"
	bottom: "pool2_p"
	top: "ip1_p"
	param {
		name: "ip1_w"
		lr_mult: 1
	}
	param {
		name: "ip1_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 500
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "relu1_p"
	type: "ReLU"
	bottom: "ip1_p"
	top: "ip1_p"
}

layer {
	name: "ip2_p"
	type: "InnerProduct"
	bottom: "ip1_p"
	top: "ip2_p"
	param {
		name: "ip2_w"
		lr_mult: 1
	}
	param {
		name: "ip2_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 10
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "feat_p"
	type: "InnerProduct"
	bottom: "ip2_p"
	top: "feat_p"
	param {
		name: "feat_w"
		lr_mult: 1
	}
	param {
		name: "feat_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 2
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

########### Negative

layer {
	name: "conv1_n"
	type: "Convolution"
	bottom: "negative"
	top: "conv1_n"
	param {
		name: "conv1_w"
		lr_mult: 1
	}
	param {
		name: "conv1_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 20
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool1_n"
	type: "Pooling"
	bottom: "conv1_n"
	top: "pool1_n"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "conv2_n"
	type: "Convolution"
	bottom: "pool1_n"
	top: "conv2_n"
	param {
		name: "conv2_w"
		lr_mult: 1
	}
	param {
		name: "conv2_b"
		lr_mult: 2
	}
	convolution_param {
		num_output: 50
		kernel_size: 5
		stride: 1
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "pool2_n"
	type: "Pooling"
	bottom: "conv2_n"
	top: "pool2_n"
	pooling_param {
		pool: MAX
		kernel_size: 2
		stride: 2
	}
}

layer {
	name: "ip1_n"
	type: "InnerProduct"
	bottom: "pool2_n"
	top: "ip1_n"
	param {
		name: "ip1_w"
		lr_mult: 1
	}
	param {
		name: "ip1_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 500
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "relu1_n"
	type: "ReLU"
	bottom: "ip1_n"
	top: "ip1_n"
}

layer {
	name: "ip2_n"
	type: "InnerProduct"
	bottom: "ip1_n"
	top: "ip2_n"
	param {
		name: "ip2_w"
		lr_mult: 1
	}
	param {
		name: "ip2_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 10
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "feat_n"
	type: "InnerProduct"
	bottom: "ip2_n"
	top: "feat_n"
	param {
		name: "feat_w"
		lr_mult: 1
	}
	param {
		name: "feat_b"
		lr_mult: 2
	}
	inner_product_param {
		num_output: 2
		weight_filler {
			type: "xavier"
		}
		bias_filler {
			type: "constant"
		}
	}
}

layer {
	name: "loss"
	type: "Module"
	bottom: "feat"
	bottom: "feat_p"
	bottom: "feat_n"
	top: "loss"
	threshold_param {
		threshold: 0.2
	}
	module_param {
		module: "triplet_layers"
		type: "TripletLoss"
	}
}