2017-04-04 131 views
0

的apply_gradients在optimizer.py,代碼段的第一部分是ValueError異常(「不提供變量」。)在optimize.py

def apply_gradients(self, grads_and_vars, global_step=None, name=None): 

    grads_and_vars = tuple(grads_and_vars) # Make sure repeat iteration works. 
    if not grads_and_vars: 
     raise ValueError("No variables provided.") 

運行我的程序,我得到了由此引起的特定錯誤的錯誤消息。然後我打印出tuple(grads_and_vars),其中一部分是。我不知道爲什麼它會導致no variables provided的錯誤。

((<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_0:0' shape=(3, 3, 3, 64) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2afc746b5c50>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_1:0' shape=(64,) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2affd48189b0>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_2:0' shape=(3, 3, 64, 64) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2affd486d940>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_3:0' shape=(64,) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2affd488cf98>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_4:0' shape=(3, 3, 64, 128) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2afc746b5d68>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_5:0' shape=(128,) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2affd48f4278>), (<tf.Tensor 'Optimizer/training/clip_by_global_norm/Optimizer/training/clip_by_global_norm/_6:0' shape=(3, 3, 128, 128) dtype=float32>, <tensorflow.python.ops.variables.Variable object at 0x2affd4915e10>), 
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你能提供你所運行的模型的某些方面?你有哪些變量,以及這個apply_gradients操作的是哪個變量? –

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您是否找到解決方案?我也有同樣的錯誤。 – user3104352

回答

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在你的情況,也許你應該嘗試grads_and_vars =名單(ZIP(畢業生,var_list))