Python AttributeError: 'Tensor' 对象没有属性 'numpy'

AttributeError: 'Tensor' object has no attribute 'numpy'

提问by Frieder Hannenheim

How can I fix this error I downloaded this code from GitHub.

如何修复此错误我从 GitHub 下载了此代码。

predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].numpy()

throws the error

抛出错误

AttributeError: 'Tensor' object has no attribute 'numpy'

Please help me fix this!

请帮我解决这个问题！

I used:

我用了：

sess = tf.Session()
    with sess.as_default():
       predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].eval()

And i get this error. Someone help me i just want it to work why is this so hard?

我得到这个错误。有人帮助我，我只是想让它工作，为什么这么难？

D:\Python>python TextGenOut.py
  File "TextGenOut.py", line 72
    predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].eval()
    ^
IndentationError: unexpected indent

D:\Python>python TextGenOut.py
2018-09-16 21:50:57.008663: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-09-16 21:50:57.272973: W T:\src\github\tensorflow\tensorflow\core\framework\op_kernel.cc:1275] OP_REQUIRES failed at resource_variable_ops.cc:480 : Not found: Container localhost does not exist. (Could not find resource: localhost/model/embedding/embeddings)
Traceback (most recent call last):
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1278, in _do_call
    return fn(*args)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1263, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1350, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error while reading resource variable model/dense/kernel from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/model/dense/kernel)
         [[Node: model/dense/MatMul/ReadVariableOp = ReadVariableOp[dtype=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](model/dense/kernel)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "TextGenOut.py", line 72, in <module>
    predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].eval()
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py", line 680, in eval
    return _eval_using_default_session(self, feed_dict, self.graph, session)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py", line 4951, in _eval_using_default_session
    return session.run(tensors, feed_dict)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 877, in run
    run_metadata_ptr)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1100, in _run
    feed_dict_tensor, options, run_metadata)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1272, in _do_run
    run_metadata)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\client\session.py", line 1291, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error while reading resource variable model/dense/kernel from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/model/dense/kernel)
         [[Node: model/dense/MatMul/ReadVariableOp = ReadVariableOp[dtype=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](model/dense/kernel)]]

Caused by op 'model/dense/MatMul/ReadVariableOp', defined at:
  File "TextGenOut.py", line 66, in <module>
    predictions, hidden = model(input_eval, hidden)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\base_layer.py", line 736, in __call__
    outputs = self.call(inputs, *args, **kwargs)
  File "TextGenOut.py", line 39, in call
    x = self.fc(output)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\base_layer.py", line 736, in __call__
    outputs = self.call(inputs, *args, **kwargs)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\layers\core.py", line 943, in call
    outputs = gen_math_ops.mat_mul(inputs, self.kernel)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4750, in mat_mul
    name=name)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\op_def_library.py", line 510, in _apply_op_helper
    preferred_dtype=default_dtype)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py", line 1094, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1045, in _dense_var_to_tensor
    return var._dense_var_to_tensor(dtype=dtype, name=name, as_ref=as_ref)  # pylint: disable=protected-access
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 1000, in _dense_var_to_tensor
    return self.value()
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 662, in value
    return self._read_variable_op()
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 745, in _read_variable_op
    self._dtype)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\ops\gen_resource_variable_ops.py", line 562, in read_variable_op
    "ReadVariableOp", resource=resource, dtype=dtype, name=name)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\util\deprecation.py", line 454, in new_func
    return func(*args, **kwargs)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py", line 3155, in create_op
    op_def=op_def)
  File "C:\Users\fried\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py", line 1717, in __init__
    self._traceback = tf_stack.extract_stack()

FailedPreconditionError (see above for traceback): Error while reading resource variable model/dense/kernel from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/model/dense/kernel)
         [[Node: model/dense/MatMul/ReadVariableOp = ReadVariableOp[dtype=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](model/dense/kernel)]]

回答by ash

I suspect the place where you copied the code from had eager execution enabled, i.e. had invoked tf.enable_eager_execution()at the start of the program.

我怀疑你复制代码的地方启用了急切执行，即tf.enable_eager_execution()在程序开始时调用。

You could do the same. Hope that helps.

你也可以这样做。希望有帮助。

UPDATE: Note that eager execution is enabled by default in TensorFlow 2.0. So the answer above applies only to TensorFlow 1.x

更新：请注意，在 TensorFlow 2.0 中默认启用 Eager Execution。所以上面的答案只适用于 TensorFlow 1.x

回答by Debosmit Ray

tf.multinomialreturns a Tensor object that contains a 2D list with drawn samples of shape [batch_size, num_samples]. Calling .eval()on that tensor object is expected to return a numpy ndarray.

tf.multinomial返回一个 Tensor 对象，该对象包含一个 2D 列表，其中绘制了 shape 样本[batch_size, num_samples]。调用.eval()该张量对象预计会返回一个 numpy ndarray。

Something like this:

像这样的东西：

predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].eval()

You also need to ensure that you have a session active (doesn't make a lot of sense otherwise):

您还需要确保会话处于活动状态（否则没有多大意义）：

sess = tf.Session()
with sess.as_default():
    predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].eval()

回答by Jonathan L

I saw similar error when I run code something like the following,

当我运行如下代码时，我看到了类似的错误，

tensor = tf.multiply(ndarray, 42)
tensor.numpy()  # throw AttributeError: 'Tensor' object has no attribute 'numpy'

I use anaconda 3 with tensorflow 1.14.0. I upgraded tensorflow with the command below

我将 anaconda 3 与 tensorflow 1.14.0 一起使用。我使用以下命令升级了 tensorflow

conda update tensorflow

now tensorflow is 2.0.0, issue fixed. Try this to see if it resolves your issue.

现在 tensorflow 是 2.0.0，问题已修复。试试这个，看看它是否能解决你的问题。

回答by amalik2205

It happens in older version of TF. So try pip install tensorflow --upgrade

它发生在旧版本的 TF 中。所以试试pip install tensorflow --upgrade

otherwise run

否则运行

import tensorflow as tf
tf.enable_eager_execution()

If you are using Jupyter notebook, restart the Kernel.

如果您使用的是 Jupyter notebook，请重新启动内核。