打印函数在 Keras/Tensorflow 中的调用函数内不打印任何内容

Question

我想使用 print 命令打印下面的调用函数中的一些对象，但当代码成功运行时它什么也打印不出来。我正在阅读（THIS）keras 调试教程，但我仍然很困惑为什么它没有打印任何内容。

#Hyperparams 
learning_rate = 0.001
weight_decay = 0.0001
batch_size = 100 
num_epochs = 1

image_size = 72  # We'll resize input images to this size
patch_size = 6  # Size of the patches to be extract from the input images
num_patches = (image_size // patch_size) ** 2
projection_dim = 64
num_heads = 4
transformer_units = [
projection_dim * 2,
projection_dim,
]  # Size of the transformer layers
transformer_layers = 8
mlp_head_units = [2048, 1024]

我想打印下面的调用函数中的（位置和编码）。为此，我使用了打印，但它不起作用。而这里，他们就这么做了。

class PatchEncoder(layers.Layer):
  def __init__(self, num_patches, projection_dim, position_embedding):
  super.__init__()
  self.num_patches = num_patches
  self.projection = layers.Dense(units=projection_dim)
  self.position_embedding = layers.Embedding(
    input_dim=num_patches, output_dim=projection_dim
  )

  def call(self, patch):
  positions = tf.range(start=0, limit=self.num_patches, delta=1)
  encoded = self.projection(patch) + self.position_embedding(positions)
  print("Encoded shape is:",encoded.shape)
  print("pos.shape is:", positions.shape)
  return encoded

Answer 1

对于评论中分享的代码。将其添加为导入之前的第一个代码单元。

%%bash
pip install -U tensorflow_addons

在感兴趣的日常中添加哟

class Patches(layers.Layer):
    def __init__(self, patch_size):
        super(Patches, self).__init__()
        self.patch_size = patch_size

    def call(self, images):
        print("yo")
        batch_size = tf.shape(images)[0]
        patches = tf.image.extract_patches(
            images=images,
            sizes=[1, self.patch_size, self.patch_size, 1],
            strides=[1, self.patch_size, self.patch_size, 1],
            rates=[1, 1, 1, 1],
            padding="VALID",
        )
        patch_dims = patches.shape[-1]
        patches = tf.reshape(patches, [batch_size, -1, patch_dims])
        return patches

运行用于打印示例图像的单元格，然后就会打印。

yo
Image size: 72 X 72
Patch size: 6 X 6
Patches per image: 144
Elements per patch: 108

Answer 2

尝试添加 tf.print() 而不仅仅是 print() 语句