Initializers
GlorotNormal
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layer eddl::GlorotNormal(layer l, int seed = 1234)
Glorot normal initializer, also called Xavier normal initializer.
It draws samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / (fan_in + fan_out)) where fan_in is the number of input units in the weight tensor and fan_out is the number of output units in the weight tensor.
- Parameters
l – Parent layer to initialize
seed – Used to seed the random generator
- Returns
The layer l initialized with the Glorot normal
Example:
l = GlorotNormal(l);
GlorotUniform
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layer eddl::GlorotUniform(layer l, int seed = 1234)
Glorot uniform initializer, also called Xavier uniform initializer.
It draws samples from a uniform distribution within [-limit, limit] where limit is sqrt(6 / (fan_in + fan_out)) where fan_in is the number of input units in the weight tensor and fan_out is the number of output units in the weight tensor.
- Parameters
l – Parent layer to initialize
seed – Used to seed the random generator
- Returns
The layer l initialized with the Glorot uniform
Example:
l = GlorotUniform(l);
RandomNormal
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layer eddl::RandomNormal(layer l, float m = 0.0, float s = 0.1, float seed = 1234)
Random normal initializer.
- Parameters
l – Parent layer to initialize
m – Mean of the normal distribution to draw samples
s – Standard deviation of the normal distribution to draw samples
seed – Used to seed the random generator
- Returns
The layer l initialized with a random normal distribution
Example:
l = RandomNormal(l, 0.0, 0.1);
RandomUniform
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layer eddl::RandomUniform(layer l, float min = 0.0, float max = 0.1, float seed = 1234)
Random uniform initializer.
- Parameters
l – Parent layer to initialize
min – lower bound of the uniform distribution
max – upper bount of the uniform distribution
seed – Used to seed the random generator
- Returns
The layer l initialized with a random normal distribution
Example:
l = RandomUniform(l, -0.05, 0.05);
Constant
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layer eddl::Constant(layer l, float v = 0.1)
Initializer that generates tensors initialized to a constant value.
- Parameters
l – Parent layer to initialize
v – Value of the generator
- Returns
The layer l initialized with a constant value
Example:
l = Constant(l, 0.5);
HeUniform
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layer eddl::HeUniform(layer l, int seed = 1234)
He uniform initializer.
It draws samples from a uniform distribution within [-limit, limit] where limit is sqrt(6 / (fan_in )) where fan_in is the number of input units in the weight tensor
- Parameters
l – Parent layer to initialize
seed – Used to seed the random generator
- Returns
The layer l initialized with the Glorot uniform
Example:
l = HeUniform(l);
HeNormal
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layer eddl::HeNormal(layer l, int seed = 1234)
He normal initializer.
It draws samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / (fan_in)) where fan_in is the number of input units in the weight tensor
- Parameters
l – Parent layer to initialize
seed – Used to seed the random generator
- Returns
The layer l initialized with the Glorot normal
Example:
l = HeNormal(l);