Randomized Seach CV is not working with KerasRegressor about scikeras HOT 1 CLOSED

import numpy as np
from sklearn.model_selection import RandomizedSearchCV
from scikeras.wrappers import KerasRegressor
from scipy.stats import reciprocal
from tensorflow import keras

def build_model(n_hidden, n_neurons, learning_rate, meta):
    model = keras.models.Sequential()
    model.add(keras.layers.InputLayer(input_shape=(meta['n_features_in_'],)))
    for layer in range(n_hidden):
        model.add(keras.layers.Dense(n_neurons, activation="relu"))
    model.add(keras.layers.Dense(1))
    optimizer = keras.optimizers.SGD(learning_rate=learning_rate)
    model.compile(loss="mse", optimizer=optimizer)
    return model

keras_reg = KerasRegressor(build_model, n_hidden=1, n_neurons=30, learning_rate=3e-3)

param_distribs = {
    "n_hidden": [0, 1, 2, 3],
    "n_neurons": np.arange(1, 100).tolist(),
    "learning_rate": reciprocal(3e-4, 3e-2).rvs(1000).tolist(),
}

x = np.random.uniform(size=(10, 8))
y = np.random.randint(0, 1, size=(10,))

rnd_search_cv = RandomizedSearchCV(keras_reg, param_distribs, n_iter=1, cv=1, verbose=2)
rnd_search_cv.fit(x, y, epochs=100, callbacks=[keras.callbacks.EarlyStopping(patience=10)])