Python ValueError:尝试将类型不受支持的值(<;class';tf.keras.layers.core.Dense';)转换为张量
尝试将dense1张量层的形状从Python ValueError:尝试将类型不受支持的值(<;class';tf.keras.layers.core.Dense';)转换为张量,python,tensorflow,keras,deep-learning,Python,Tensorflow,Keras,Deep Learning,尝试将dense1张量层的形状从(无,13)更改为(无,1,13) 代码片段 dense1= Dense(13, activation='relu') tf.expand_dims(dense1, axis=1) 这就是错误所在 --------------------------------------------------------------------------- ValueError Traceback (most
(无,13)
更改为(无,1,13)
代码片段
dense1= Dense(13, activation='relu')
tf.expand_dims(dense1, axis=1)
这就是错误所在
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-3-82c32af7a088> in <module>()
----> 1 tf.expand_dims(dense1, axis=1)
10 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
96 dtype = dtypes.as_dtype(dtype).as_datatype_enum
97 ctx.ensure_initialized()
---> 98 return ops.EagerTensor(value, ctx.device_name, dtype)
99
100
ValueError: Attempt to convert a value (<tensorflow.python.keras.layers.core.Dense object at 0x7f58f41d9b00>) with an unsupported type (<class 'tensorflow.python.keras.layers.core.Dense'>) to a Tensor.
---------------------------------------------------------------------------
ValueError回溯(最近一次调用上次)
在()
---->1 tf.展开尺寸(密度1,轴=1)
10帧
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value、ctx、dtype)
96 dtype=dtypes.as\u dtype(dtype).as\u datatype\u enum
97 ctx.确保_已初始化()
--->98返回操作数(值,ctx.device\u名称,数据类型)
99
100
ValueError:尝试将不支持类型()的值()转换为张量。
尝试将其包装在TimeDistributed
层中:
import tensorflow as tf
model = tf.keras.Sequential([
tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(13, activation='relu'),
input_shape=[1, 13])])
model.build(input_shape=[13])
model.summary()
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
time_distributed_3 (TimeDist (None, 1, 13) 182
=================================================================
Total params: 182
Trainable params: 182
Non-trainable params: 0
_________________________________________________________________