Python 3的語法錯誤：無效的語法（機器學習）

Question

我從coursera

# GRADED FUNCTION: backward_propagation 

DEF backward_propagation（參數，高速緩存，X，Y）平面寫入數據分類與一個隱藏層： 「」」 使用上述說明貫徹向後傳播

Arguments: 
parameters -- python dictionary containing our parameters 
cache -- a dictionary containing "Z1", "A1", "Z2" and "A2". 
X -- input data of shape (2, number of examples) 
Y -- "true" labels vector of shape (1, number of examples) 

Returns: 
grads -- python dictionary containing your gradients with respect to different parameters 
""" 
m = X.shape[1] 

# First, retrieve W1 and W2 from the dictionary "parameters". 
### START CODE HERE ### (≈ 2 lines of code) 
W1 = parameters["W1"] 
W2 = parameters["W2"] 
### END CODE HERE ### 

# Retrieve also A1 and A2 from dictionary "cache". 
### START CODE HERE ### (≈ 2 lines of code) 
A1 = cache["A1"] 
A2 = cache["A1"] 
### END CODE HERE ### 

# Backward propagation: calculate dW1, db1, dW2, db2. 
### START CODE HERE ### (≈ 6 lines of code, corresponding to 6 equations on slide above) 
dZ2= A2-Y 
dW2 = (1/m)*np.dot(dZ2,A1.T) 
db2 = (1/m)*np.sum(dZ2, axis=1, keepdims=True) 
dZ1 = np.multiply(np.dot(W2.T, dZ2),1 - np.power(A1, 2) 
dW1 = (1/m) * np.dot(dZ1, X.T) 
db1 = (1/m)*np.sum(dZ1,axis1,keepdims=True) 
### END CODE HERE ### 

grads = {"dW1": dW1, 
     "db1": db1, 
     "dW2": dW2, 
     "db2": db2} 

return grads 

和當運行此代碼： 文件 「」，第36行 DW1 =（1/M）* np.dot（DZ1，XT） ^ 語法錯誤：無效語法

Answer 1

正如在其中一個註釋中提到的，您在dZ1中缺少右括號。 並在「db1」中將「axis1」寫入axis = 1。