wehub-resource-sync
120 lines
3.3 KiB
Protocol Buffer
120 lines
3.3 KiB
Protocol Buffer
syntax = "proto2";
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package MNN.Compression;
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message QuantizeParams {
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enum RoundMode {
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ROUND_TOWARDS_ZERO = 0;
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ROUND_AWAY_FROM_ZERO = 1;
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ROUND_HALF_TO_EVEN = 2;
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}
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optional RoundMode round_mode = 1 [default = ROUND_AWAY_FROM_ZERO];
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// Quantization parameters for each layer that needs to be quantized.
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// For a block composed of several operators, such as
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// `Convolution` + `BatchNorm` + `Relu`, it should be considered as a
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// single layer.
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repeated LayerQuantizeParams layer = 4;
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}
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message LayerQuantizeParams {
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// Activation quantization parameters.
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// Both symmetric and asymmetric mode are supported for activation,
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// and `zero_point` should always be zero if symmetric mode.
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message ActivationParams {
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// Activation tensor name.
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required string name = 1;
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optional int32 bits = 2 [default = 8];
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repeated float scales = 3;
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optional int32 zero_point = 4 [default = 0];
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optional int32 clamp_min = 5 [default = -128];
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optional int32 clamp_max = 6 [default = 127];
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}
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// Weight quantization parameters.
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// Only symmetric mode is supported. Both channel-wise and tensor-wise
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// quantization are supported, depending on whether `scales` length is
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// equal to output channels.
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message WeightParams {
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// Weight tensor name.
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required string name = 1;
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optional int32 bits = 2 [default = 8];
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repeated float scales = 3;
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optional int32 clamp_min = 4 [default = -128];
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optional int32 clamp_max = 5 [default = 127];
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optional bool asymmetric = 6 [default = false];
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optional int32 block_size = 7 [default = 0];
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}
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message WinogradParams {
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required int32 version = 1 [default = 0];
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// units_attr: {kyStart, kxStart, subKy, subKx, unitY, unitX} x N
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repeated int32 units_attr = 4;
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}
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enum QuantMethod {
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QAT = 0;
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OverflowAware = 1;
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WinogradAware = 2;
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}
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message ConvolutionInfo {
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required int32 input_channel = 1;
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required int32 output_channel = 2;
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repeated int32 kernel_size = 3;
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}
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repeated ActivationParams input = 1;
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repeated WeightParams weight = 2;
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repeated ActivationParams output = 3;
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optional QuantMethod method = 4 [default = QAT];
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optional WinogradParams wino_params = 5;
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optional string op_name = 6;
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optional string subgraph_name = 7;
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optional ConvolutionInfo conv = 8;
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}
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message LevelPrunerParams {
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repeated string weight_tensor_names = 1;
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repeated float prune_ratios = 2;
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repeated string layer_names = 3;
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}
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message SIMDOCPrunerParams {
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repeated string weight_tensor_names = 1;
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repeated float prune_ratios = 2;
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repeated string layer_names = 3;
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repeated int32 oc_blocks = 4;
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}
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message PruneParams {
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enum PruneType {
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RANDOM = 0;
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SIMD_OC = 1;
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FILTER = 2;
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}
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optional PruneType type = 1 [default = RANDOM];
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optional LevelPrunerParams level_pruner_params = 2;
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optional SIMDOCPrunerParams simd_oc_pruner_params = 3;
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}
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message CompressionAlgo {
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enum CompressionType {
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QUANTIZE = 0;
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PRUNE = 1;
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}
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optional CompressionType type = 1 [default = QUANTIZE];
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optional QuantizeParams quant_params = 2;
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optional PruneParams prune_params = 3;
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}
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// Model compression algorithm pipeline.
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message Pipeline {
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required string version = 1 [default = "0.0.0"];
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repeated CompressionAlgo algo = 2;
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optional string mnn_uuid = 3;
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optional bool for_guide = 4 [default = false];
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}
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