我的目标是使用以下代码对具有自定义形状和自定义内核的数组执行Conv2d：

import tensorflow as tf
import numpy as np
import sys
tf.compat.v1.enable_eager_execution()

# kernel
kernel_array = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]])
kernel = tf.keras.initializers.Constant(kernel_array)
print('kernel shape:', kernel_array.shape)
print('kernel:',kernel_array)

# input
input_shape = (3, 3, 4, 1)
x = tf.random.normal(input_shape)
print('x shape:', x.shape)
print('x:',x.numpy())

# output
y = tf.keras.layers.Conv2D(
    3, kernel_array.shape, padding="same", strides=(1, 1),
    kernel_initializer=kernel,
    input_shape=input_shape[1:])(x)
print('y shape:', y.shape)
print('y:',y.numpy())

上面的代码给予我一个这样的错误：

kernel shape: (3, 3)
kernel: [[1 1 1]
 [1 1 1]
 [1 1 1]]
x shape: (3, 3, 4, 1)
x: [[[[-0.01953345]
   [-0.7110965 ]
   [ 0.15634525]
   [ 0.1707633 ]]

  [[-0.70654714]
   [ 2.7564087 ]
   [ 0.60063267]
   [ 2.8321717 ]]

  [[ 1.4761941 ]
   [ 0.34693545]
   [ 0.85550934]
   [ 2.2514896 ]]]

 [[[ 0.82585895]
   [-0.6421492 ]
   [ 1.2688193 ]
   [-0.9054445 ]]

  [[ 1.1591591 ]
   [ 0.7465941 ]
   [ 1.2531661 ]
   [ 2.2717664 ]]

  [[-0.48740315]
   [-0.42796597]
   [ 0.4480274 ]
   [-1.1502023 ]]]

 [[[-0.7792355 ]
   [-0.801604  ]
   [ 1.6724508 ]
   [ 0.25857568]]

  [[ 0.09068593]
   [-0.4783198 ]
   [-0.02883703]
   [-2.1400564 ]]

  [[-0.5518157 ]
   [-1.4513488 ]
   [-0.07611077]
   [ 1.4752681 ]]]]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[6], line 19
     16 print('x:',x.numpy())
     18 # output
---> 19 y = tf.keras.layers.Conv2D(
     20     3, kernel_array.shape, padding="same", strides=(1, 1),
     21     kernel_initializer=kernel,
     22     input_shape=input_shape[1:])(x)
     23 print('y shape:', y.shape)
     24 print('y:',y.numpy())

File c:\Users\xxxx\AppData\Local\Programs\Python\Python310\lib\site-packages\keras\utils\traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs)
     67     filtered_tb = _process_traceback_frames(e.__traceback__)
     68     # To get the full stack trace, call:
     69     # `tf.debugging.disable_traceback_filtering()`
---> 70     raise e.with_traceback(filtered_tb) from None
     71 finally:
     72     del filtered_tb

File c:\Users\xxxx\AppData\Local\Programs\Python\Python310\lib\site-packages\keras\initializers\initializers.py:265, in Constant.__call__(self, shape, dtype, **kwargs)
    261 if layout:
    262     return utils.call_with_layout(
    263         tf.constant, layout, self.value, shape=shape, dtype=dtype
    264     )
--> 265 return tf.constant(self.value, dtype=_get_dtype(dtype), shape=shape)

TypeError: Eager execution of tf.constant with unsupported shape. Tensor [[1. 1. 1.]
 [1. 1. 1.]
 [1. 1. 1.]] (converted from [[1 1 1]
 [1 1 1]
 [1 1 1]]) has 9 elements, but got `shape` (3, 3, 1, 3) with 27 elements).

我不知道错在哪里。我已经尝试改变输入形状，但仍然没有工作了。我错过了什么？