tensorflow-metal makes jupyter notebook kernel dead

import tensorflow as tf
from tensorflow import keras
import numpy as np

(X_train_full, y_train_full), (X_test, y_test) = keras.datasets.fashion_mnist.load_data()
X_train, X_valid = X_train_full[:-5000], X_train_full[-5000:]
y_train, y_valid = y_train_full[:-5000], y_train_full[-5000:]

X_mean = X_train.mean(axis=0, keepdims=True)
X_std = X_train.std(axis=0, keepdims=True) + 1e-7
X_train = (X_train - X_mean) / X_std
X_valid = (X_valid - X_mean) / X_std
X_test = (X_test - X_mean) / X_std

X_train = X_train[..., np.newaxis]
X_valid = X_valid[..., np.newaxis]
X_test = X_test[..., np.newaxis]

from functools import partial

DefaultConv2D = partial(keras.layers.Conv2D,
                        kernel_size=3, activation='relu', padding="SAME")

input_ = keras.layers.Input(shape=[28, 28, 1])
conv0 = DefaultConv2D(filters=64, kernel_size=7)(input_)
pool1 = keras.layers.MaxPooling2D(pool_size=2)(conv0)
conv1 = DefaultConv2D(filters=128)(pool1)
conv2 = DefaultConv2D(filters=128)(conv1)
pool2 = keras.layers.MaxPooling2D(pool_size=2)(conv2)
conv3 = DefaultConv2D(filters=256)(pool2)
conv4 = DefaultConv2D(filters=256)(conv3)
pool3 = keras.layers.MaxPooling2D(pool_size=2)(conv4)
flatten = keras.layers.Flatten()(conv4)
hidden1 = keras.layers.Dense(units=128, activation='relu')(flatten)
dropout1 = keras.layers.Dropout(0.5)(hidden1)
hidden2 = keras.layers.Dense(units=64, activation='relu')(dropout1)
dropout2 = keras.layers.Dropout(0.5)(hidden2)
output = keras.layers.Dense(units=10, activation='softmax')(dropout2)

model = keras.Model(inputs=[input_], outputs=[output])

model.compile(loss="sparse_categorical_crossentropy", optimizer="nadam", metrics=["accuracy"])

model.fit(X_train, y_train, epochs=20, validation_data=(X_valid, y_valid))

However I got the error message the kernel appears to have died. it will restart automatically. in the 3rd cell.

I also ran this python script from terminal one line at a time, and I got the error message I attached above when I tried to run the code conv0 = DefaultConv2D(filters=64, kernel_size=7)(input_)

With tensorflow-metal uninstalled, this code runs without any error messages.