错误的维度数：预期 1，得到 2

Question

I'm doing logistic regression on a dataset for binary classification, but I'm not able to train the model for some reasons. The error:

TypeError: Bad input argument to theano function with name "<ipython-input-41-da82a78c1e80>:4" at index 1 (0-based).  
Backtrace when that variable is created:

  File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
    handler(stream, idents, msg)
  File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "/usr/local/lib/python3.6/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/usr/local/lib/python3.6/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
    if self.run_code(code, result):
  File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-37-e46f93a2582c>", line 2, in <module>
    y = T.ivector('y')
Wrong number of dimensions: expected 1, got 2 with shape (1096, 1).

Please can someone tell me how to fix this as I'm new to theano.

import pandas as pd
import io
from sklearn import preprocessing
test_data = pd.read_csv('bank_data_test.csv').to_numpy()
train_data= pd.read_csv('bank_data_train.csv').to_numpy()
y_train=train_data[:,:1]
y_test=test_data[:,:1]
x_train=train_data[:,1:]
x_test=test_data[:,1:]
sc=StandardScaler()
sc.fit(x_train)
x_train=sc.transform(x_train)
x_test=sc.transform(x_test)
y_train.shape
x = T.fmatrix('x')
y = T.ivector('y')
w_init=np.zeros(x_train.shape[1])
b_init=0.0
w=theano.shared(w_init)
b=theano.shared(b_init)
hypo=1.0/(1.0+T.exp(-T.dot(x,w)-b))
py_x=hypo>0.5
cost=-T.mean(y*T.log(hypo)+(1-y)*T.log(1-hypo))
w_grad=T.grad(cost,w)
b_grad=T.grad(cost,b)
train_op=theano.function(inputs=[x,y],outputs=cost,updates=[
                                                            (w,w-0.05*w_grad),
                                                            (b,b-0.05*b_grad)],
                                                             allow_input_downcast=True)
predict_op=theano.function(inputs=[x],outputs=py_x,allow_input_downcast=True)
for i in range(2000):
  train_op(x_train,y_train)

The error where it shows is: train_op(x_train,y_train)

Answer 1

It looks like y is a matrix instead of a vector. To solve this try:

y = T.ivector('y')[0]

instead.

Answer 2

I don't know what is the problem in your code, but your error comes from the line

y = T.ivector('y')

and not in

train_op(x_train,y_train)