tf 前向 predict加速

import tensorflow as tf
import numpy as np
import time

from tensorflow import keras

print(tf.__version__)
loop_times = 100
input_data = np.zeros((2,8,8))
model  = keras.Sequential([
    keras.layers.Flatten(input_shape=(8,8)),
    keras.layers.Dense(10)
])
model.compile(optimizer='adam',loss='softmax')

#####################################
clock = time.time()

for i in range(loop_times):
    res = model.predict(x=input_data)

print(time.time() - clock,'s')
print(res)
#####################################
clock = time.time()

for i in range(loop_times):
    res = model.predict(x=tf.data.Dataset.from_tensors(input_data))

print(time.time() - clock, 's')
print(res)

#####################################
clock = time.time()
for i in range(loop_times):
    res_m = model(input_data, training=False)
    res = np.array(res_m)

print(time.time() - clock, 's')
print(res_m)
print(res)