Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
您最多选择25个主题 主题必须以中文或者字母或数字开头,可以包含连字符 (-),并且长度不得超过35个字符
 
 
 
 
 

48 行
1.7 KiB

import torch
from enum import Enum
class Swish(torch.nn.Module):
def forward(self, data: torch.Tensor) -> torch.Tensor:
return torch.mul(data, torch.sigmoid(data))
class Initialization(Enum):
Zero = 0
XavierGlorotNormal = 1
XavierGlorotUniform = 2
KaimingHeNormal = 3 # also known as Variance scaling
KaimingHeUniform = 4
_init_methods = {
Initialization.Zero: torch.zero_,
Initialization.XavierGlorotNormal: torch.nn.init.xavier_normal_,
Initialization.XavierGlorotUniform: torch.nn.init.xavier_uniform_,
Initialization.KaimingHeNormal: torch.nn.init.kaiming_normal_,
Initialization.KaimingHeUniform: torch.nn.init.kaiming_uniform_,
}
def linear_layer(
input_size: int,
output_size: int,
kernel_init: Initialization = Initialization.XavierGlorotUniform,
kernel_gain: float = 1.0,
bias_init: Initialization = Initialization.Zero,
) -> torch.nn.Module:
"""
Creates a torch.nn.Linear module and initializes its weights.
:param input_size: The size of the input tensor
:param output_size: The size of the output tensor
:param kernel_init: The Initialization to use for the weights of the layer
:param kernel_gain: The multiplier for the weights of the kernel. Note that in
TensorFlow, calling variance_scaling with scale 0.01 is equivalent to calling
KaimingHeNormal with kernel_gain of 0.1
:param bias_init: The Initialization to use for the weights of the bias layer
"""
layer = torch.nn.Linear(input_size, output_size)
_init_methods[kernel_init](layer.weight.data)
layer.weight.data *= kernel_gain
_init_methods[bias_init](layer.bias.data)
return layer