INVALID_ARGUMENT: You must feed a value for placeholder tensor ‘inputs‘ with dtype float and shape

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D
import tensorflow as tf
model = Sequential()

model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(48,48,1)))
model.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Flatten())
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(7, activation='softmax'))
model.load_weights('model.h5')
model.save('tfmodel', save_format='tf')

An error is reported when the keras model is transferred to tf and saved

INVALID_ARGUMENT: You must feed a value for placeholder tensor 'inputs' with dtype float and shape [?,22,22,64]
         [[{
    
    {
    
    node inputs}}]]

No value is passed to the Placeholder node inputs, just pass the value to this node Try to
pass the value of the model input input

INVALID_ARGUMENT: You must feed a value for placeholder tensor ‘inputs‘ with dtype float and shape

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