models/research/lstm_object_detection/protos/quant_overrides.proto

syntax = "proto2";

package lstm_object_detection.protos;

// Message to override default quantization behavior.
message QuantOverrides {
  repeated QuantConfig quant_configs = 1;
}

// Parameters to manually create fake quant ops outside of the generic
// tensorflow/contrib/quantize/python/quantize.py script. This may be
// used to override default behaviour or quantize ops not already supported.
message QuantConfig {
  // The name of the op to add a fake quant op to.
  required string op_name = 1;

  // The name of the fake quant op.
  required string quant_op_name = 2;

  // Whether the fake quant op uses fixed ranges. Otherwise, learned moving
  // average ranges are used.
  required bool fixed_range = 3 [default = false];

  // The intitial minimum value of the range.
  optional float min = 4 [default = -6];

  // The initial maximum value of the range.
  optional float max = 5 [default = 6];

  // Number of steps to delay before quantization takes effect during training.
  optional int32 delay = 6 [default = 500000];

  // Number of bits to use for quantizing weights.
  // Only 8 bit is supported for now.
  optional int32 weight_bits = 7 [default = 8];

  // Number of bits to use for quantizing activations.
  // Only 8 bit is supported for now.
  optional int32 activation_bits = 8 [default = 8];
}