训练期间打印中间张量

Question

我有一个自定义层，我想打印没有通过自定义层的call()方法链接到返回的张量（如代码所示）的中间张量。我使用的代码是：

class Similarity(Layer):
    
    def __init__(self, num1, num2):    
        super(Similarity, self).__init__()
        self.num1 = num1
        self.num2 = num2
#         self.total = tf.Variable(initial_value=tf.zeros((16,self.num1, 1)), trainable=False)    
        
    def build(self, input_shape):
        super(Similarity, self).build((None, self.num1, 1))
            
    
    def compute_mask(self, inputs, mask=None):
        # Just pass the received mask from previous layer, to the next layer or 
        # manipulate it if this layer changes the shape of the input
        return mask
        
    def call(self, inputs, mask=None):
        print(">>", type(inputs), inputs.shape, inputs)

        normalized = tf.nn.l2_normalize(inputs, axis = 2)
        print("norm", normalized)
        # multiply row i with row j using transpose
        # element wise product
        similarity = tf.matmul(normalized, normalized,
                         adjoint_b = True # transpose second matrix
                         )
    
        print("SIM", similarity)
        
        z=tf.linalg.band_part(similarity, 0, -1)*3 + tf.linalg.band_part(similarity, -1, 0)*2 - tf.linalg.band_part(similarity,0,0)*6 + tf.linalg.band_part(similarity,0,0)
#         z = K.print_tensor(tf.reduce_sum(z, 2, keepdims=True))
        z = tf.reduce_sum(z, 2, keepdims=True)
    
        z = tf.argsort(z)                # <----------- METHOD2: Reassigned the Z to the tensor I want to print temporarily
        z = K.print_tensor(z)
        print(z)
    
        z=tf.linalg.band_part(similarity, 0, -1)*3 + tf.linalg.band_part(similarity, -1, 0)*2 - tf.linalg.band_part(similarity,0,0)*6 + tf.linalg.band_part(similarity,0,0)

        z = K.print_tensor(tf.reduce_sum(z, 2, keepdims=True)) #<------------- THIS LINE WORKS/PRINTS AS Z is returned
        # z = tf.reduce_sum(z, 2, keepdims=True)
        
        
        @tf.function                             
                                              #<------------- METHOD1: Want to print RANKT tensor but this DID NOT WORKED
        def f(z):
            rankt = K.print_tensor(tf.argsort(z))
#             rankt = tf.reshape(rankt, (-1, self.num1))
#             rankt = K.print_tensor(rankt)
            return rankt
        
        pt = f(z)
        
        return z               # <--------- The returned tensor
    
    def compute_output_shape(self, input_shape):
        print("IS", (None, self.num1, 1))
        return (None, self.num1, 1)

更清楚地说,

我用method1来打印@tf.function张量，但它不起作用

其次，在method2中，我临时重新分配了z（在call()之后返回张量），以便它在backprop中执行，并获得打印的值。在此之后，我将z重新分配给原始操作

总而言之，我不想要z的值，但我想打印某个变量的值，该值取决于z，但除了z之外，我无法打印任何变量

Answer 1

这个函数有^{}函数

在急切模式下，它不返回任何内容，只打印张量。当在计算图构建过程中使用时，它返回TF运算符，这些运算符进行标识并打印张量值作为副作用