類型錯誤在tensorflow

使用ScipyOptimizerInterface當我嘗試使用ScipyOptimizerInterface優化某些功能。我試圖運行下面的代碼片段（從tensorflow文檔稍微修改），以獲得它如何工作的一些想法。類型錯誤在tensorflow

vector = tf.Variable([7., 7.], 'vector') 
# Make vector norm as small as possible. 
loss = tf.reduce_sum(tf.square(vector)) 

optimizer = tf.contrib.opt.ScipyOptimizerInterface(loss, options={'maxiter': 100}) 

with tf.Session() as session: 
    optimizer.minimize(session) 
# The value of vector should now be [0., 0.].

然而，我得到了以下錯誤消息：

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-27-e81545f4bb15> in <module>() 
     4 loss = tf.reduce_sum(tf.square(vector)) 
     5 
----> 6 optimizer = tf.contrib.opt.ScipyOptimizerInterface(loss, options={'maxiter': 100}) 
     7 
     8 with tf.Session() as session: 

/s/anaconda/....../miniconda2/lib/python2.7/site-packages/tensorflow/contrib/opt/python/training/external_optimizer.pyc in __init__(self, loss, var_list, equalities, inequalities, var_to_bounds, **optimizer_kwargs) 
    124  self.optimizer_kwargs = optimizer_kwargs 
    125 
--> 126  self._packed_var = self._pack(self._vars) 
    127  self._packed_loss_grad = self._pack(loss_grads) 
    128  self._packed_equality_grads = [ 

/s/anaconda/...../miniconda2/lib/python2.7/site-packages/tensorflow/contrib/opt/python/training/external_optimizer.pyc in _pack(cls, tensors) 
    257  else: 
    258  flattened = [array_ops.reshape(tensor, [-1]) for tensor in tensors] 
--> 259  return array_ops.concat(flattened, 0) 
    260 
    261 def _make_eval_func(self, tensors, session, feed_dict, fetches, 

/s/anaconda/...../miniconda2/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.pyc in concat(values, axis, name) 
    1064 return gen_array_ops._concat_v2(values=values, 
    1065         axis=axis, 
-> 1066         name=name) 
    1067 
    1068 

/s/anaconda/...../miniconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.pyc in _concat_v2(values, axis, name) 
    493 """ 
    494 result = _op_def_lib.apply_op("ConcatV2", values=values, axis=axis, 
--> 495         name=name) 
    496 return result 
    497 

/s/anaconda/...../miniconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.pyc in apply_op(self, op_type_name, name, **keywords) 
    461         (prefix, dtype.name)) 
    462    else: 
--> 463     raise TypeError("%s that don't all match." % prefix) 
    464    else: 
    465    raise TypeError("%s that are invalid." % prefix) 

TypeError: Tensors in list passed to 'values' of 'ConcatV2' Op have types [float64, float32, float32, float32, float32, float32, float32, float32, float32, float64, float64, float32, float32, float32, float32, float32, float32, float32, float32, float32, float64, float32, float32] that don't all match.

我使用tensorflow從連續分析1.3.0-RC0和python 2.7.12。你能否告訴我們如何解決這個問題，並防止它發生？

來源

2017-08-16 Kratos1808

錯誤似乎很清楚，您傳遞的張量列表不匹配類型。您可能需要找到某種方法將丟失對象轉換爲所有Float64的列表（以保持完整的精度）。 – csunday95

嗨csunday 95！謝謝你的評論！我的確嘗試過使用下面的代碼：loss = tf.cast（tf.reduce_sum（tf.square（vector）），dtype = tf.float32）但編譯器仍然抱怨第一個參數和其他兩個在initilization優化器是float64！ – Kratos1808

以下代碼適用於張量流版本1.2.0。您還需要初始化變量。

import tensorflow as tf 
vector = tf.Variable([7., 7.], 'vector') 
# Make vector norm as small as possible. 
loss = tf.reduce_sum(tf.square(vector)) 


optimizer = tf.contrib.opt.ScipyOptimizerInterface(
    loss, options={'maxiter': 100}) 

with tf.Session() as session: 
    session.run(tf.global_variables_initializer()) 
    print(session.run(vector)) # results: [7.0, 7.0] 
    optimizer.minimize(session) 
    print(session.run(vector)) # results: [ -1.88996808e-06 -1.88996808e-06]

來源

2017-08-16 18:55:12

嗨Ishant先生！非常感謝您的快速響應！我試圖運行你的代碼，但得到了同樣的錯誤。在我看來，編譯器非常挑剔，並且在啓動優化器時會引發錯誤。順便說一下，我在jupyter筆記本上運行代碼。 – Kratos1808

這個問題可能與您的tensorflow版本或jupyter有關。 –

謝謝Ishant！我會檢查你提到的那兩件事。 – Kratos1808

類型錯誤在tensorflow

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