PythonのTFLearn形状が完全に定義されていますが、その代わりだったしなければならない（1、1、？、32）

Question

こんにちは、私は私の自己に挑戦したかったので、CNNの予測株式をしようとしていていますし、私はそれがConvd2Dが完全に定義されていませんが、私はそのエラーを修正するためにそこに置くために他に何かわからないことを考えて、このエラーを越えカム。誰かが私をここに助けることができる私のコードは、私が手にエラーが

File "C:\Users\User\Desktop\Python Projects\Intel_Stock_Price_Prediction.py", line 38, in <module> 
    convnet = conv_2d(convnet, 32, 1, activation='relu') 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tflearn\layers\conv.py", line 85, in conv_2d 
    restore=restore) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\framework\python\ops\arg_scope.py", line 181, in func_with_args 
    return func(*args, **current_args) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tflearn\variables.py", line 65, in variable 
    validate_shape=validate_shape) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1065, in get_variable 
    use_resource=use_resource, custom_getter=custom_getter) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 962, in get_variable 
    use_resource=use_resource, custom_getter=custom_getter) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 367, in get_variable 
    validate_shape=validate_shape, use_resource=use_resource) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 352, in _true_getter 
    use_resource=use_resource) 
    File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 685, in _get_single_variable 
    "but instead was %s." % (name, shape)) 
ValueError: Shape of a new variable (Conv2D/W) must be fully defined, but instead was (1, 1, ?, 32). 

ある

import tflearn 
import numpy as np 
from tflearn.layers.conv import conv_2d, max_pool_2d 
from tflearn.layers.core import input_data, dropout, fully_connected 
from tflearn.layers.estimator import regression 
import csv 
import math 

prices = [] 
templist = [] 
X = [] 
Y = [] 
i=0 

def get_data(filename): 
    with open(filename, 'r') as csvfile: 
     csvFileReader = csv.reader(csvfile) 
     next(csvFileReader) 
     for row in csvFileReader: 
      prices.append(float(row[1])) 
    return 

get_data('intc.csv') 
i=len(prices)-5 
while i>5: 
    X.append(prices[i-5:i]) 
    Y.append(prices[i-6]) 
    i-=1 



#X, Y, test_x, test_y = mnist.load_data(one_hot=True) 

X = np.reshape(X,(-1,len(X),len(X[0]),1)) 

convnet = input_data(shape=[None, 241, 5, None], name='input') 

convnet = conv_2d(convnet, 32, 1, activation='relu') 
convnet = max_pool_2d(convnet, 1) 

convnet = conv_2d(convnet, 64, 1, activation='relu') 
convnet = max_pool_2d(convnet, 1) 

convnet = fully_connected(convnet, 1024, activation='relu') 
convnet = dropout(convnet, 0.8) 

convnet = fully_connected(convnet, 1, activation='softmax') 
convnet = regression(convnet, optimizer='adam', learning_rate=0.01, loss='categorical_crossentropy', name='targets') 

model = tflearn.DNN(convnet) 
model.fit({'input': X}, {'targets': Y}, n_epoch=2, snapshot_step=500, show_metric=True) 
model.save('quicktest.model') 

で誰かが感謝してください助けることができます。

Answer 1

ここでエラーがinput_data機能に関連しています。入力データの形状を完全に定義する必要があります。バッチディメンションにはNoneを使用できますが、他の入力ディメンションには使用できません。

# replace this line 
convnet = input_data(shape=[None, 241, 5, None], name='input') 
# hopefully with your correct input dimension. you need provide a value 
# in your case 
num_channels =1 
convnet = input_data(shape=[None, 241, 5, num_channels], name='input')