如何修复以下错误。它由5层组成。前三个后面是 GCN 层。第四层是注意力层。错误似乎来自第 4 层，即注意力层。
class SimpleAttLayer():
def __init__(self, attention_size, time_major=False):
self.attention_size = attention_size
self.time_major = time_major
self.vars = {}
def __call__(self, inputs):
if isinstance(inputs, tuple):
# In case of Bi-RNN, concatenate the forward and the backward RNN outputs.
inputs = tf.concat(inputs, 2)
if self.time_major:
# (T,B,D) => (B,T,D)
inputs = tf.transpose(inputs, [1, 0, 2])
hidden_size = inputs.shape[2].value # D value - hidden size of the RNN layer
# Trainable parameters
with tf.variable_scope('v'):
# Applying fully connected layer with non-linear activation to each of the B*T timestamps;
# the shape of `v` is (B,T,D)*(D,A)=(B,T,A), where A=attention_size
w_omega = tf.get_variable(initializer=tf.random_normal([hidden_size, self.attention_size], stddev=0.1), name='w_omega')
self.vars['w_omega'] = w_omega
以下是错误消息：我试图将输入更改为 tf.shape(inputs)[0]。总的来说，我是 GCN 和神经网络的新手。我该如何解决这个问题。
Tensor("features:0", shape=(2136, 2136), dtype=float32)
WARNING:tensorflow:From /content/ACKRec/layers.py:126: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.
[<tf.Tensor 'first/MatMul_1:0' shape=<unknown> dtype=float32>]
Tensor("first/Relu:0", dtype=float32)
1
Tensor("first/Relu_1:0", dtype=float32)
[<tf.Tensor 'graphconvolution_1/MatMul_1:0' shape=<unknown> dtype=float32>]
Tensor("graphconvolution_1/Relu:0", dtype=float32)
2
Tensor("graphconvolution_1/Relu_1:0", dtype=float32)
[<tf.Tensor 'graphconvolution_2/MatMul_1:0' shape=<unknown> dtype=float32>]
Tensor("graphconvolution_2/Relu:0", dtype=float32)
3
Tensor("graphconvolution_2/Relu_1:0", dtype=float32)
<unknown>
Tensor("transpose:0", shape=(?, ?, ?), dtype=float32)
(?, ?, ?)
None
WARNING:tensorflow:From /content/ACKRec/layers.py:191: The name tf.random_normal is deprecated. Please use tf.random.normal instead.
Traceback (most recent call last):
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/tensor_util.py", line 541, in make_tensor_proto
str_values = [compat.as_bytes(x) for x in proto_values]
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/tensor_util.py", line 541, in <listcomp>
str_values = [compat.as_bytes(x) for x in proto_values]
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/util/compat.py", line 71, in as_bytes
(bytes_or_text,))
TypeError: Expected binary or unicode string, got None
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 40, in <module>
model = GCN(placeholders=placeholders, input_dim=features.shape[1], num_support=num_support)
File "/content/ACKRec/models.py", line 129, in __init__
self.build()
File "/content/ACKRec/models.py", line 59, in build
hidden = self.layers[i](self.activations[-1])
File "/content/ACKRec/layers.py", line 191, in __call__
w_omega = tf.get_variable(initializer=tf.random_normal([hidden_size, self.attention_size], stddev=0.1), name='w_omega')
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/ops/random_ops.py", line 69, in random_normal
shape_tensor = tensor_util.shape_tensor(shape)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/tensor_util.py", line 964, in shape_tensor
return ops.convert_to_tensor(shape, dtype=dtype, name="shape")
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/ops.py", line 1184, in convert_to_tensor
return convert_to_tensor_v2(value, dtype, preferred_dtype, name)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/ops.py", line 1242, in convert_to_tensor_v2
as_ref=False)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/ops.py", line 1297, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/constant_op.py", line 286, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/constant_op.py", line 227, in constant
allow_broadcast=True)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/constant_op.py", line 265, in _constant_impl
allow_broadcast=allow_broadcast))
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/framework/tensor_util.py", line 545, in make_tensor_proto
"supported type." % (type(values), values))
TypeError: Failed to convert object of type <class 'tuple'> to Tensor. Contents: (None, 32). Consider casting elements to a supported type.