如何将tf.assign_add操作改写为长尾词？
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本文共计322个文字，预计阅读时间需要2分钟。
tf.assign_add(ref, value, use_locking=None, name=None) 通过向其添加值来更新ref。此操作在更新完成后输出ref。这使得
tf.assign_add(ref,value,use_lockingNone,nameNone)Updaterefbyaddingvaluetoit.Thisoperatitf.assign_add(ref,value,use_lockingNone,nameNone)
Update ref by adding value to it.
This operation outputs “ref” after the update is done. This makes it easier to chain operations that need to use the reset value.
Args: ref: A mutable Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half. Should be from a Variable node. value: A Tensor. Must have the same type as ref. The value to be added to the variable. use_locking: An optional bool. Defaults to False. If True, the addition will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. name: A name for the operation (optional).
b tf.ones([3,3],dtypetf.float32)c tf.Variable(tf.random_normal([3,3],mean1,stddev2,dtypetf.float32),name"c")d tf.assign_add(c,b)init_op tf.global_variables_initializer()with tf.Session() as sess:sess.run(init_op)x, y , z sess.run([c,b,d])print(x," \n!!!\n",y, "\n!!!\n", z, "\n!!!")print(sess.run(d))
输出
[[ 4.723362 0.44867647 0.27219188][ 5.9517117 1.8866203 3.3032823 ][-2.2057695 1.8035562 -0.53330874]] !!![[1. 1. 1.][1. 1. 1.][1. 1. 1.]] !!![[ 4.723362 0.44867647 0.27219188][ 5.9517117 1.8866203 3.3032823 ][-2.2057695 1.8035562 -0.53330874]] !!![[ 5.723362 1.4486765 1.2721919 ][ 6.9517117 2.8866203 4.3032823 ][-1.2057695 2.8035562 0.46669126]]
突然发现用x, y , z sess.run([c,b,d])跑的话c和d结果一样。。。
本文共计322个文字，预计阅读时间需要2分钟。
tf.assign_add(ref, value, use_locking=None, name=None) 通过向其添加值来更新ref。此操作在更新完成后输出ref。这使得
tf.assign_add(ref,value,use_lockingNone,nameNone)Updaterefbyaddingvaluetoit.Thisoperatitf.assign_add(ref,value,use_lockingNone,nameNone)
Update ref by adding value to it.
This operation outputs “ref” after the update is done. This makes it easier to chain operations that need to use the reset value.
Args: ref: A mutable Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half. Should be from a Variable node. value: A Tensor. Must have the same type as ref. The value to be added to the variable. use_locking: An optional bool. Defaults to False. If True, the addition will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. name: A name for the operation (optional).
b tf.ones([3,3],dtypetf.float32)c tf.Variable(tf.random_normal([3,3],mean1,stddev2,dtypetf.float32),name"c")d tf.assign_add(c,b)init_op tf.global_variables_initializer()with tf.Session() as sess:sess.run(init_op)x, y , z sess.run([c,b,d])print(x," \n!!!\n",y, "\n!!!\n", z, "\n!!!")print(sess.run(d))
输出
[[ 4.723362 0.44867647 0.27219188][ 5.9517117 1.8866203 3.3032823 ][-2.2057695 1.8035562 -0.53330874]] !!![[1. 1. 1.][1. 1. 1.][1. 1. 1.]] !!![[ 4.723362 0.44867647 0.27219188][ 5.9517117 1.8866203 3.3032823 ][-2.2057695 1.8035562 -0.53330874]] !!![[ 5.723362 1.4486765 1.2721919 ][ 6.9517117 2.8866203 4.3032823 ][-1.2057695 2.8035562 0.46669126]]
突然发现用x, y , z sess.run([c,b,d])跑的话c和d结果一样。。。