python里input输入参数有误

参数有误"/>

python里input输入参数有误

错误：TypeError: ('Bad input argument to theano function with name

"c2.py:77" at index 1(0-based)', 'Wrong number of dimensions:

expected 2, got 1 with shape (128L,).')

请告知如何修理？在

代码和数据可通过以下链接下载：

然后输入这个代码：QU90WxTZ

我的密码是：# -*- coding: utf-8 -*-

import os

import pandas as pd

import theano

from theano import tensor as T

import numpy as np

def normalizeX(X):

return X / 255.0

data = pd.read_csv("digits3a.csv")

trX = normalizeX(data.values[:, 1:].astype(float))

trY = data.values[:, 0]

data = pd.read_csv("digits3b.csv")

teX = normalizeX(data.values.astype(float))

def floatX(X):

return np.asarray(X, dtype=theano.config.floatX)

def init_weights(shape):

return theano.shared(floatX(np.random.randn(*shape) * 0.01))

def model(X, w):

return T.nnet.softmax(T.dot(X, w))

X = T.fmatrix()

Y = T.fmatrix()

w = init_weights((784, 10))

py_x = model(X, w)

y_pred = T.argmax(py_x, axis=1)

cost = T.mean(T.nnet.categorical_crossentropy(py_x, Y))

gradient = T.grad(cost=cost, wrt=w)

update = [[w, w - gradient * 0.05]]

train = theano.function(inputs=[X, Y], outputs=cost, updates=update, allow_input_downcast=True)

predict = theano.function(inputs=[X], outputs=y_pred, allow_input_downcast=True)

for i in range(10):

for start, end in zip(range(0, len(trX), 128), range(128, len(trX), 128)):

cost = train(trX[start:end], trY[start:end])

print i, np.mean(np.argmax(teY, axis=1) == predict(teX))