tensorflow - Blas GEMM 启动失败：Windows 上的 Tensorflow / Jupyter / Anaconda：

问题描述

谢谢你看这个。我正在尝试重新运行我在重新格式化之前运行的脚本。我确定该脚本有效，因为我之前运行过它，但我认为我的配置不太正确。有什么简单的我想念的吗？

我使用本指南安装了 Anaconda / Tensorflow： https ://towardsdatascience.com/tensorflow-gpu-installation-made-easy-use-conda-instead-of-pip-52e5249374bc

我有一个带有 Geforce 2070 的 Windows 10 x64。

Train on 1031 samples, validate on 442 samples
Epoch 1/100000
---------------------------------------------------------------------------
InternalError                             Traceback (most recent call last)
<ipython-input-1-8f1f59f4bdeb> in <module>
     32 checkpointer = ModelCheckpoint(filepath="weights.hdf5", verbose=1, save_best_only=True)
     33 
---> 34 history=model.fit(predictors,target, validation_split=0.3, epochs=100000,verbose=2, callbacks=[checkpointer])
     35 model.load_weights('weights.hdf5')
     36 

~\.conda\envs\tf_gpu\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
   1237                                         steps_per_epoch=steps_per_epoch,
   1238                                         validation_steps=validation_steps,
-> 1239                                         validation_freq=validation_freq)
   1240 
   1241     def evaluate(self,

~\.conda\envs\tf_gpu\lib\site-packages\keras\engine\training_arrays.py in fit_loop(model, fit_function, fit_inputs, out_labels, batch_size, epochs, verbose, callbacks, val_function, val_inputs, shuffle, initial_epoch, steps_per_epoch, validation_steps, validation_freq)
    194                     ins_batch[i] = ins_batch[i].toarray()
    195 
--> 196                 outs = fit_function(ins_batch)
    197                 outs = to_list(outs)
    198                 for l, o in zip(out_labels, outs):

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\keras\backend.py in __call__(self, inputs)
   3725         value = math_ops.cast(value, tensor.dtype)
   3726       converted_inputs.append(value)
-> 3727     outputs = self._graph_fn(*converted_inputs)
   3728 
   3729     # EagerTensor.numpy() will often make a copy to ensure memory safety.

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\eager\function.py in __call__(self, *args, **kwargs)
   1549       TypeError: For invalid positional/keyword argument combinations.
   1550     """
-> 1551     return self._call_impl(args, kwargs)
   1552 
   1553   def _call_impl(self, args, kwargs, cancellation_manager=None):

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\eager\function.py in _call_impl(self, args, kwargs, cancellation_manager)
   1589       raise TypeError("Keyword arguments {} unknown. Expected {}.".format(
   1590           list(kwargs.keys()), list(self._arg_keywords)))
-> 1591     return self._call_flat(args, self.captured_inputs, cancellation_manager)
   1592 
   1593   def _filtered_call(self, args, kwargs):

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\eager\function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
   1690       # No tape is watching; skip to running the function.
   1691       return self._build_call_outputs(self._inference_function.call(
-> 1692           ctx, args, cancellation_manager=cancellation_manager))
   1693     forward_backward = self._select_forward_and_backward_functions(
   1694         args,

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\eager\function.py in call(self, ctx, args, cancellation_manager)
    543               inputs=args,
    544               attrs=("executor_type", executor_type, "config_proto", config),
--> 545               ctx=ctx)
    546         else:
    547           outputs = execute.execute_with_cancellation(

~\.conda\envs\tf_gpu\lib\site-packages\tensorflow_core\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     65     else:
     66       message = e.message
---> 67     six.raise_from(core._status_to_exception(e.code, message), None)
     68   except TypeError as e:
     69     keras_symbolic_tensors = [

~\.conda\envs\tf_gpu\lib\site-packages\six.py in raise_from(value, from_value)

InternalError:  Blas GEMM launch failed : a.shape=(32, 9), b.shape=(9, 10), m=32, n=10, k=9
     [[node dense_1/MatMul (defined at C:\Users\Shawn\.conda\envs\tf_gpu\lib\site-packages\keras\backend\tensorflow_backend.py:3009) ]] [Op:__inference_keras_scratch_graph_887]

Function call stack:
keras_scratch_graph

标签： tensorflowanacondajupyter

tensorflow - Blas GEMM 启动失败：Windows 上的 Tensorflow / Jupyter / Anaconda：

问题描述

解决方案

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