Initializer

When using an initializer, you need to configure the name item to indicate which initializer to use, and then configure their respective parameters according to different initializer. The following are the names of each initializer.

Initializer	name
Zeros	zeros
Ones	ones
RandomUniform	random_uniform
RandomNormal	random_normal
TruncateNormal	truncate_normal

Zeros

All values Are setted to 0.

Ones

All values Are setted to 1.

RandomUniform

uniform distribution, configure the following parameters:

1. min: low bound value, float type, default: -1.0
2. max: up bound value, float type, default: 1.0

RandomNormal

stochastic normal distribution, configure the following parameters:

1. mean: mean value, float type, default: 0.0
2. stddev: standard deviation, float type, default: 1.0

TruncateNormal

stochastic normal distribution, if the generated value exceeds 2 standard deviations, it is discarded and regenerate, configure the following parameters:

1. mean: mean value, float type, default: 0.0
2. stddev: standard deviation, float type, default: 1.0

Example

import damo
import numpy as np

# zero
param = damo.Parameters()
param.insert("name", "zeros")
# must be float32
value = np.random.random(10).astype(np.float32)
obj = damo.PyInitializer(param)
obj.call(value)
print("zeros: ", value)

# ones
param = damo.Parameters()
param.insert("name", "ones")
# must be float32
value = np.random.random(10).astype(np.float32)
obj = damo.PyInitializer(param)
obj.call(value)
print("ones: ", value)

# random_uniform
param = damo.Parameters()
param.insert("name", "random_uniform")
param.insert("min", -1.0)
param.insert("max", 1.0)
# must be float32
value = np.random.random(10).astype(np.float32)
obj = damo.PyInitializer(param)
obj.call(value)
print("random_uniform: ", value)

# random_normal
param = damo.Parameters()
param.insert("name", "random_normal")
param.insert("mean", 0.0)
param.insert("stddev", 1.0)
# must be float32
value = np.random.random(10).astype(np.float32)
obj = damo.PyInitializer(param)
obj.call(value)
print("random_normal: ", value)

# truncate_normal
param = damo.Parameters()
param.insert("name", "truncate_normal")
param.insert("mean", 0.0)
param.insert("stddev", 1.0)
# must be float32
value = np.random.random(10).astype(np.float32)
obj = damo.PyInitializer(param)
obj.call(value)
print("truncate_normal: ", value)