tf plot_model 사용시 반응없음

import tensorflow as tf
import numpy as np
import pandas as pd
import os
import shutil
import matplotlib.pyplot as plt
from tensorflow.keras.utils import plot_model
from tensorflow.keras.callbacks import TensorBoard
from tensorflow.keras.applications.inception_v3 import InceptionV3
from tensorflow.keras.preprocessing.image import ImageDataGenerator

trainds = tf.keras.preprocessing.image_dataset_from_directory(
  '../Users/ADMIN/Desktop/data/set1/',
  image_size=(150,150),
  batch_size=64,
  subset='training',
  validation_split=0.2,
  seed=1234
)

valds = tf.keras.preprocessing.image_dataset_from_directory(
  '../Users/ADMIN/Desktop/data/set1/',
  image_size=(150,150),
  batch_size=64,
  subset='validation',
  validation_split=0.2,
  seed=1234
)

for i , answer in trainds.take(1): #사진을 보여주는코드임.
    print(i,answer)
    plt.imshow(i[0].numpy().astype("uint8"))
    plt.imshow(i[2].numpy().astype("uint8")) #텐서를 넘파이로 변환하여보여줌
    plt.imshow(i[3].numpy().astype("uint8"))
    plt.show()

def prework(x,y):
    x=tf.cast(x/255.0, tf.float32)  #연산이빨라지게 이미지들을 255값으로 나눈다
    return x,y
train=trainds.map(prework)             #맵함수 는 함수에 들어오는값을 리스트값으로 반복
val=valds.map(prework)

inception_model=InceptionV3(input_shape=(150,150,3),include_top=False,weights=None)
inception_model.load_weights("../Users/ADMIN/Desktop/data/inception_v3.h5")
inception_model.summary()

# inception_model.summary()

#가중치 에 학습안시키기

for i in inception_model.layers:
    i.trainable=False

unfreeze= False
for i in inception_model.layers:  #빠인 튜닝
    if i.name == "mixed9":
        unfreeze = True
    if unfreeze == True:
        i.trainble = True
#믹스드 레이어 10이 발견되면 그부분부터 가중치 학습

lastlayer=inception_model.get_layer("mixed10")

mylayer1 = tf.keras.Sequential([
    tf.keras.layers.experimental.preprocessing.RandomFlip('horizontal_and_vertical'),  #이미지를 비틀고 옮기고 등등해서 복사본을 만드는 방법의 함수
    tf.keras.layers.experimental.preprocessing.RandomRotation(0.1),
    tf.keras.layers.experimental.preprocessing.RandomZoom(0.1),
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(1024, activation="relu"),
])(lastlayer.output)

drop1=tf.keras.layers.Dropout(0.2)(mylayer1)
out=tf.keras.layers.Dense(1,activation="sigmoid")(drop1)

model=tf.keras.Model(inception_model.input,out)
model.compile(loss="binary_crossentropy", optimizer=tf.keras.optimizers.Adam(learning_rate=0.001), metrics=["accuracy"])
model.fit(trainds, validation_data=valds, epochs=15)
plot_model(model, to_file='model.png', show_shapes=False, show_layer_names=False)

사과형님 안녕하심니까 2개의 질문입니다.
for i , answer in trainds.take(1) < Take1 일때는 사진한장만 가져오는게 맞는건가요?
plot_model(model, to_file='model.png', show_shapes=False, show_layer_names=False) <-학습은 잘되는데 이녀석이 실행이안됩니다.
미리감사요.