You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
127 lines
4.0 KiB
127 lines
4.0 KiB
syntax = "proto2";
|
|
|
|
package object_detection.protos;
|
|
|
|
// Configuration proto for the convolution op hyperparameters to use in the
|
|
// object detection pipeline.
|
|
message Hyperparams {
|
|
|
|
// Operations affected by hyperparameters.
|
|
enum Op {
|
|
// Convolution, Separable Convolution, Convolution transpose.
|
|
CONV = 1;
|
|
|
|
// Fully connected
|
|
FC = 2;
|
|
}
|
|
optional Op op = 1 [default = CONV];
|
|
|
|
// Regularizer for the weights of the convolution op.
|
|
optional Regularizer regularizer = 2;
|
|
|
|
// Initializer for the weights of the convolution op.
|
|
optional Initializer initializer = 3;
|
|
|
|
// Type of activation to apply after convolution.
|
|
enum Activation {
|
|
// Use None (no activation)
|
|
NONE = 0;
|
|
|
|
// Use tf.nn.relu
|
|
RELU = 1;
|
|
|
|
// Use tf.nn.relu6
|
|
RELU_6 = 2;
|
|
}
|
|
optional Activation activation = 4 [default = RELU];
|
|
|
|
oneof normalizer_oneof {
|
|
// Note that if nothing below is selected, then no normalization is applied
|
|
// BatchNorm hyperparameters.
|
|
BatchNorm batch_norm = 5;
|
|
// GroupNorm hyperparameters. This is only supported on a subset of models.
|
|
// Note that the current implementation of group norm instantiated in
|
|
// tf.contrib.group.layers.group_norm() only supports fixed_size_resizer
|
|
// for image preprocessing.
|
|
GroupNorm group_norm = 7;
|
|
}
|
|
|
|
// Whether depthwise convolutions should be regularized. If this parameter is
|
|
// NOT set then the conv hyperparams will default to the parent scope.
|
|
optional bool regularize_depthwise = 6 [default = false];
|
|
}
|
|
|
|
// Proto with one-of field for regularizers.
|
|
message Regularizer {
|
|
oneof regularizer_oneof {
|
|
L1Regularizer l1_regularizer = 1;
|
|
L2Regularizer l2_regularizer = 2;
|
|
}
|
|
}
|
|
|
|
// Configuration proto for L1 Regularizer.
|
|
// See https://www.tensorflow.org/api_docs/python/tf/contrib/layers/l1_regularizer
|
|
message L1Regularizer {
|
|
optional float weight = 1 [default = 1.0];
|
|
}
|
|
|
|
// Configuration proto for L2 Regularizer.
|
|
// See https://www.tensorflow.org/api_docs/python/tf/contrib/layers/l2_regularizer
|
|
message L2Regularizer {
|
|
optional float weight = 1 [default = 1.0];
|
|
}
|
|
|
|
// Proto with one-of field for initializers.
|
|
message Initializer {
|
|
oneof initializer_oneof {
|
|
TruncatedNormalInitializer truncated_normal_initializer = 1;
|
|
VarianceScalingInitializer variance_scaling_initializer = 2;
|
|
RandomNormalInitializer random_normal_initializer = 3;
|
|
}
|
|
}
|
|
|
|
// Configuration proto for truncated normal initializer. See
|
|
// https://www.tensorflow.org/api_docs/python/tf/truncated_normal_initializer
|
|
message TruncatedNormalInitializer {
|
|
optional float mean = 1 [default = 0.0];
|
|
optional float stddev = 2 [default = 1.0];
|
|
}
|
|
|
|
// Configuration proto for variance scaling initializer. See
|
|
// https://www.tensorflow.org/api_docs/python/tf/contrib/layers/
|
|
// variance_scaling_initializer
|
|
message VarianceScalingInitializer {
|
|
optional float factor = 1 [default = 2.0];
|
|
optional bool uniform = 2 [default = false];
|
|
enum Mode {
|
|
FAN_IN = 0;
|
|
FAN_OUT = 1;
|
|
FAN_AVG = 2;
|
|
}
|
|
optional Mode mode = 3 [default = FAN_IN];
|
|
}
|
|
|
|
// Configuration proto for random normal initializer. See
|
|
// https://www.tensorflow.org/api_docs/python/tf/random_normal_initializer
|
|
message RandomNormalInitializer {
|
|
optional float mean = 1 [default = 0.0];
|
|
optional float stddev = 2 [default = 1.0];
|
|
}
|
|
|
|
// Configuration proto for batch norm to apply after convolution op. See
|
|
// https://www.tensorflow.org/api_docs/python/tf/contrib/layers/batch_norm
|
|
message BatchNorm {
|
|
optional float decay = 1 [default = 0.999];
|
|
optional bool center = 2 [default = true];
|
|
optional bool scale = 3 [default = false];
|
|
optional float epsilon = 4 [default = 0.001];
|
|
// Whether to train the batch norm variables. If this is set to false during
|
|
// training, the current value of the batch_norm variables are used for
|
|
// forward pass but they are never updated.
|
|
optional bool train = 5 [default = true];
|
|
}
|
|
|
|
// Configuration proto for group normalization to apply after convolution op.
|
|
// https://arxiv.org/abs/1803.08494
|
|
message GroupNorm {
|
|
}
|