1.2 tensorflow2.0 常用函数

a
#<tf.Tensor: shape=(4, 2), dtype=float32, numpy=
array([[ 0.491424  ,  0.6428182 ],
       [ 2.247138  ,  0.2008341 ],
       [ 0.93056387,  0.01603121],
       [ 0.33425295, -1.1971117 ]], dtype=float32)>
tf.cast(a,dtype=tf.float64)
a
#<tf.Tensor: shape=(4, 2), dtype=float32, numpy=
array([[ 0.491424  ,  0.6428182 ],
       [ 2.247138  ,  0.2008341 ],
       [ 0.93056387,  0.01603121],
       [ 0.33425295, -1.1971117 ]], dtype=float32)>
tf.reduce_min(a)
#<tf.Tensor: shape=(), dtype=float32, numpy=-1.1971117>
tf.reduce_max(a)
#<tf.Tensor: shape=(), dtype=float32, numpy=2.247138>

#axis = 0 代表纵向，axis = 1 代表横向
tf.reduce_mean(a)
#<tf.Tensor: shape=(), dtype=float32, numpy=0.45824385>
tf.reduce_mean(a,axis=0)
#<tf.Tensor: shape=(2,), dtype=float32, numpy=array([ 1.0008447 , -0.08435705], dtype=float32)>
tf.reduce_mean(a,axis=1)
#<tf.Tensor: shape=(4,), dtype=float32, numpy=array([ 0.5671211 ,  1.223986  ,  0.47329754, -0.4314294 ], dtype=float32)>

#tf.reduce_sum()同理
tf.Varible

tf.add,tf.substract,tf.multiply,tf.divide
tf.square,tf.pow,tf.sqrt
tf.matmul

features = tf.constant([12,23,10,17]) 
labels = tf.constant([0, 1, 1, 0]) 
dataset = tf.data.Dataset.from_tensor_slices((features, labels)) 
dataset
#<TensorSliceDataset shapes: ((), ()), types: (tf.int32, tf.int32)>
for i in dataset:
  print(i)
(<tf.Tensor: shape=(), dtype=int32, numpy=12>, <tf.Tensor: shape=(), dtype=int32, numpy=0>)
(<tf.Tensor: shape=(), dtype=int32, numpy=23>, <tf.Tensor: shape=(), dtype=int32, numpy=1>)
(<tf.Tensor: shape=(), dtype=int32, numpy=10>, <tf.Tensor: shape=(), dtype=int32, numpy=1>)
(<tf.Tensor: shape=(), dtype=int32, numpy=17>, <tf.Tensor: shape=(), dtype=int32, numpy=0>)