def power_difference_op(input_x, input_y, input_pow):
with tf.Session() as sess:
x = tf.placeholder(tf.float32, name='x')
y = tf.placeholder(tf.float32, name='y')
pow_ = tf.placeholder(tf.float32, name='pow')
z = tf.power_difference(x, y, pow_)
return sess.run(z, feed_dict={x: input_x, y: input_y, pow_: input_pow})
def power_difference_op(input_x,input_y,input_pow):
with tf.Session() as sess:
# TODO：完成TensorFlow接口调用
placeholder_x = tf.placeholder(tf.float32, shape=input_x.shape, name='placeholder_x')
placeholder_y = tf.placeholder(tf.float32, shape=input_y.shape, name='placeholder_y')
placeholder_z = tf.placeholder(tf.float32, name='placeholder_z')
out = tf.power_difference(placeholder_x, placeholder_y, placeholder_z)
return sess.run(out, feed_dict = {placeholder_x:input_x, placeholder_y:input_y, placeholder_z:input_pow})
def power_difference_op(input_x, input_y, input_pow):
with tf.Session() as sess:
x = tf.placeholder(tf.float32, shape=input_x.shape)
y = tf.placeholder(tf.float32, shape=input_y.shape)
pow = tf.placeholder(tf.int32)
out = tf.power_difference(x, y, pow)
return sess.run(out,
feed_dict={
x: input_x,
y: input_y,
pow: input_pow
})
def power_difference_op(input_x,input_y,input_pow):
with tf.Session() as sess:
# TODO：完成TensorFlow接口调用
out = tf.power_difference()
return sess.run(out, feed_dict = {...})