小编Mil*_*lvi的帖子

鉴于PyTorch中的代码如下,Keras的等价物是什么？

class Network(nn.Module):

    def __init__(self, state_size, action_size):
        super(Network, self).__init__()

        # Inputs = 5, Outputs = 3, Hidden = 30
        self.fc1 = nn.Linear(5, 30)
        self.fc2 = nn.Linear(30, 3)

    def forward(self, state):
        x = F.relu(self.fc1(state))
        outputs = self.fc2(x)
        return outputs

是这个吗？

model = Sequential()
model.add(Dense(units=30, input_dim=5, activation='relu'))
model.add(Dense(units=30, activation='relu'))
model.add(Dense(units=3, activation='linear'))

还是这个？

model = Sequential()
model.add(Dense(units=30, input_dim=5, activation='linear'))
model.add(Dense(units=30, activation='relu'))
model.add(Dense(units=3, activation='linear'))

或者是吗？

model = Sequential()
model.add(Dense(units=30, input_dim=5, activation='relu'))
model.add(Dense(units=30, activation='linear'))
model.add(Dense(units=3, activation='linear'))

谢谢

这是在Keras中定义自定义损失函数。代码如下：

from keras import backend as K
from keras.models import Sequential
from keras.layers import Dense
from keras.callbacks import EarlyStopping
from keras.optimizers import Adam

def custom_loss_function(y_true, y_pred):
    a_numpy_y_true_array = K.eval(y_true)
    a_numpy_y_pred_array = K.eval(y_pred)

    # some million dollar worth custom loss that needs numpy arrays to be added here...

    return K.mean(K.binary_crossentropy(y_true, y_pred), axis=-1)


def build_model():
    model= Sequential()
    model.add(Dense(16, input_shape=(701, ), activation='relu'))
    model.add(Dense(16, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss=custom_loss_function, optimizer=Adam(lr=0.005), metrics=['accuracy'])  
    return model

model = build_model()
early_stop = EarlyStopping(monitor="val_loss", patience=1) 
model.fit(kpca_X, y, epochs=50, validation_split=0.2, callbacks=[early_stop], …

我正在尝试创建一个启用了LogPublishingOptions. 虽然启用 LogPublishingOptions ES 表示它没有足够的权限在 Cloudwatch 上创建 LogStream。

我尝试创建一个带有角色的策略并将该策略附加到 ES 引用的 LogGroup，但它不起作用。以下是我的弹性搜索云形成模板，

AWSTemplateFormatVersion: 2010-09-09

Resources:
  MYLOGGROUP:
    Type: 'AWS::Logs::LogGroup'
    Properties:
      LogGroupName: index_slow

  MYESROLE:
    Type: 'AWS::IAM::Role'
    Properties:
      AssumeRolePolicyDocument:
        Version: 2012-10-17
        Statement:
          - Effect: Allow
            Principal:
              Service: es.amazonaws.com
            Action: 'sts:AssumeRole'
      ManagedPolicyArns:
        - 'arn:aws:iam::aws:policy/AmazonESFullAccess'
        - 'arn:aws:iam::aws:policy/CloudWatchFullAccess'
      RoleName: !Join
        - '-'
        - - es
          - !Ref 'AWS::Region'

  PolicyDocESIndexSlow :
    Type: AWS::IAM::Policy
    Properties:
      PolicyDocument:
        Version: 2012-10-17
        Statement:
          - Effect: Allow
            Action: 
             - logs:PutLogEvents
             - logs:CreateLogStream
            Resource: 'arn:aws:logs:*'
      PolicyName: !Ref MYLOGGROUP
      Roles:
        - !Ref MYESROLE …