TensorFlow2.0:张量的合并与分割实例
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2023-11-29 18:23:46
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一 tf.concat( ) 函数–合并
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in [2]: a = tf.ones([4,35,8])...
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一 tf.concat( ) 函数–合并
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in [2]: a = tf.ones([4,35,8]) in [3]: b = tf.ones([2,35,8]) in [4]: c = tf.concat([a,b],axis=0) in [5]: c.shape out[5]: tensorshape([6, 35, 8]) in [6]: a = tf.ones([4,32,8]) in [7]: b = tf.ones([4,3,8]) in [8]: c = tf.concat([a,b],axis=1) in [9]: c.shape out[9]: tensorshape([4, 35, 8])
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二 tf.stack( ) 函数–数据的堆叠,创建新的维度
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in [2]: a = tf.ones([4,35,8]) in [3]: a.shape out[3]: tensorshape([4, 35, 8]) in [4]: b = tf.ones([4,35,8]) in [5]: b.shape out[5]: tensorshape([4, 35, 8]) in [6]: tf.concat([a,b],axis=-1).shape out[6]: tensorshape([4, 35, 16]) in [7]: tf.stack([a,b],axis=0).shape out[7]: tensorshape([2, 4, 35, 8]) in [8]: tf.stack([a,b],axis=3).shape out[8]: tensorshape([4, 35, 8, 2])
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三 tf.unstack( )函数–解堆叠
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in [16]: a = tf.ones([4,35,8]) in [17]: b = tf.ones([4,35,8]) in [18]: c = tf.stack([a,b],axis=0) in [19]: a.shape,b.shape,c.shape out[19]: (tensorshape([4, 35, 8]), tensorshape([4, 35, 8]), tensorshape([2, 4, 35, 8])) in [20]: aa,bb = tf.unstack(c,axis=0) in [21]: aa.shape,bb.shape out[21]: (tensorshape([4, 35, 8]), tensorshape([4, 35, 8])) in [22]: res = tf.unstack(c,axis=1) in [23]: len(res) out[23]: 4
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四 tf.split( ) 函数
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in [16]: a = tf.ones([4,35,8]) in [17]: b = tf.ones([4,35,8]) in [18]: c = tf.stack([a,b],axis=0) in [19]: a.shape,b.shape,c.shape out[19]: (tensorshape([4, 35, 8]), tensorshape([4, 35, 8]), tensorshape([2, 4, 35, 8])) in [20]: aa,bb = tf.unstack(c,axis=0) in [21]: aa.shape,bb.shape out[21]: (tensorshape([4, 35, 8]), tensorshape([4, 35, 8])) in [22]: res = tf.unstack(c,axis=1) in [23]: len(res) out[23]: 4
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