ValueError: Input 0 of layer sequential_10 is incompatible with the layer（以下略）｜株式予測

Question

現在の状況

現在、ディープラーニングを用いてAPPLE社の株式予測のプログラムを書いています。その途中で以下のエラーが発生してしまいました。

ValueError: Input 0 of layer sequential_10 is incompatible with the layer: expected axis -1 of input shape to have value 20 but received input with shape [None, 19]

調べても解決できなかったのでこれがどのようなエラーでどこを直せば解決できるのか分かれば教えていただきたいです。以下のコードはリンクを参考にプログラムを書きました。
以下コード

import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from keras.callbacks import EarlyStopping
import matplotlib.pyplot as plt
from keras.layers import Dense, LSTM, Dropout, Flatten
from keras.models import Model
from pandas_datareader import data
from datetime import date
from keras import models
%matplotlib inline
pd.core.common.is_list_like = pd.api.types.is_list_like

#2000年から今日までのAPPLEの株式を読み込む
start = '2000-04-01'
end = date.today()
df = data.DataReader('AAPL', 'yahoo', start, end)

#Adj Closeの値を用いる
price = df['Adj Close']
stc_date = df.index

#model_1の設計
model_1 = models.Sequential()
model_1.add(Dense(5, activation='relu', input_shape=(20,)))
model_1.add(Dropout(0.5))
model_1.add(Dense(1, activation='linear'))
model_1.summary()
model_1.compile(optimizer='adam',
           	loss='mse',
           	metrics=['mae'])

#model_2の設計
model_2 = models.Sequential()
model_2.add(LSTM(10,
             dropout=0.2,
             recurrent_dropout=0.2,
             input_shape=(20,1)))
model_2.add(Dense(5, activation='relu'))
model_2.add(Dropout(0.5))
model_2.add(Dense(1, activation='linear'))
model_2.summary()
model_2.compile(optimizer='adam',
           loss='mse',
           metrics=['mae'])

#入力用、出力用テンソルを出力する関数
def getInputLabel(price, period=20):
  period = period
  input_tensor = []
  label_tensor = []
  for i in range(0, len(price) - period, 1):
    input_tensor.append(price.iloc[i:i + period -1])
    label_tensor.append(price.iloc[i + period -1])
  input_tensor = np.array(input_tensor)
  label_tensor = np.array(label_tensor)
  return input_tensor, label_tensor

#Topixデータを標準化
tmp = price - price.mean()
tmp = tmp/price.std()
input_tensor, label_tensor = getInputLabel(price = tmp)

#トレーニングデータとテストデータに分類
X_train, X_test, y_train, y_test = train_test_split(input_tensor, label_tensor, test_size=0.2,　random_state=100, shuffle=False)

#過学習防止
earlystopping = EarlyStopping(monitor='loss', patience=5)

#model_1学習
model_1.fit(X_train, y_train, batch_size=10, epochs=50, callbacks=[earlystopping])

#model_1学習をした際のエラーメッセージ

ValueError: in user code:

    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:806 train_function  *
        return step_function(self, iterator)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:796 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
        return fn(*args, **kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:789 run_step  **
        outputs = model.train_step(data)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:747 train_step
        y_pred = self(x, training=True)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py:976 __call__
        self.name)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/input_spec.py:216 assert_input_compatibility
        ' but received input with shape ' + str(shape))

    ValueError: Input 0 of layer sequential_10 is incompatible with the layer: expected axis -1 of input shape to have value 20 but received input with shape [None, 19]

Answer 1

def getInputLabel(price, period=20):
period = period
input_tensor = []
label_tensor = []
for i in range(0, len(price) - period, 1):
input_tensor.append(price.iloc[i:i + period -1])
label_tensor.append(price.iloc[i + period -1])
input_tensor = np.array(input_tensor)
label_tensor = np.array(label_tensor)
return input_tensor, label_tensor

のpriceの範囲をi:i + period -1からi:i + periodにしたら起動しました。お騒がせしました。