tensorflow - 无法对变量进行简单初始化 - 'data type not understood'

Question

我正在运行 Tensorflow 上的 CIFAR-10 教程，但我无法让我的任何变量声明起作用。即使是一些简单的东西:

biases = tf.get_variable('biases', [64], tf.constant_initializer(0.0))

给出错误:

   ---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-23-86228512ca30> in <module>()
----> 1 biases = tf.get_variable('biases', [64], tf.constant_initializer(0.0))

/home/mmm/programs/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape)
    730       initializer=initializer, regularizer=regularizer, trainable=trainable,
    731       collections=collections, caching_device=caching_device,
--> 732       partitioner=partitioner, validate_shape=validate_shape)
    733 
    734 

/home/mmm/programs/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape)
    594           regularizer=regularizer, reuse=self.reuse, trainable=trainable,
    595           collections=collections, caching_device=caching_device,
--> 596           partitioner=partitioner, validate_shape=validate_shape)
    597 
    598   def _get_partitioned_variable(

/home/mmm/programs/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape)
    159         initializer=initializer, regularizer=regularizer, reuse=reuse,
    160         trainable=trainable, collections=collections,
--> 161         caching_device=caching_device, validate_shape=validate_shape)
    162 
    163   def _get_partitioned_variable(

/home/mmm/programs/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, validate_shape)
    423 
    424     should_check = reuse is not None
--> 425     dtype = dtypes.as_dtype(dtype)
    426     shape = tensor_shape.as_shape(shape)
    427 

/home/mmm/programs/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/dtypes.pyc in as_dtype(type_value)
    534 
    535   for key, val in _NP_TO_TF:
--> 536     if key == type_value:
    537       return val
    538 

TypeError: data type not understood

我很想知道哪里出了问题，哪里出了问题。

提前致谢!

Answer 1

我不熟悉该教程，但看起来您提供了 tf.constant_initializer(0.0) 作为您的数据类型，它返回一个初始化程序以生成常量。 tf.get_variable() 的第三个参数应该是变量的数据类型，对于偏差变量，它通常是 tf.float32 或 tf.float64 之类的。