TensorFlow: Blas GEMM launch failed

匿名 (未验证) 提交于 2019-12-03 01:27:01

问题:

When I'm trying to use TensorFlow with Keras using the gpu, I'm getting this error message:

C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py:2: UserWarning: Update your `fit_generator` call to the Keras 2 API: `fit_generator( 1039       return fn(*args)    1040     except errors.OpError as e:  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)    1020                                  feed_dict, fetch_list, target_list, -> 1021                                  status, run_metadata)    1022   C:\Users\nicol\Anaconda3\envs\tensorflow\lib\contextlib.py in __exit__(self, type, value, traceback)      65             try: ---> 66                 next(self.gen)      67             except StopIteration:  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()     465           compat.as_text(pywrap_tensorflow.TF_Message(status)), --> 466           pywrap_tensorflow.TF_GetCode(status))     467   finally:  InternalError: Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]]  During handling of the above exception, another exception occurred:  InternalError                             Traceback (most recent call last)  in ()       1 history=model.fit_generator(batches, batches.n, nb_epoch=2,  ----> 2                     validation_data=val_batches, nb_val_samples=val_batches.n)  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)      86                 warnings.warn('Update your `' + object_name +      87                               '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 88             return func(*args, **kwargs)      89         wrapper._legacy_support_signature = inspect.getargspec(func)      90         return wrapper  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\models.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_q_size, workers, pickle_safe, initial_epoch)    1108                                         workers=workers,    1109                                         pickle_safe=pickle_safe, -> 1110                                         initial_epoch=initial_epoch)    1111     1112     @interfaces.legacy_generator_methods_support  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)      86                 warnings.warn('Update your `' + object_name +      87                               '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 88             return func(*args, **kwargs)      89         wrapper._legacy_support_signature = inspect.getargspec(func)      90         return wrapper  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_q_size, workers, pickle_safe, initial_epoch)    1888                     outs = self.train_on_batch(x, y,    1889                                                sample_weight=sample_weight, -> 1890                                                class_weight=class_weight)    1891     1892                     if not isinstance(outs, list):  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in train_on_batch(self, x, y, sample_weight, class_weight)    1631             ins = x + y + sample_weights    1632         self._make_train_function() -> 1633         outputs = self.train_function(ins)    1634         if len(outputs) == 1:    1635             return outputs[0]  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py in __call__(self, inputs)    2227         session = get_session()    2228         updated = session.run(self.outputs + [self.updates_op], -> 2229                               feed_dict=feed_dict)    2230         return updated[:len(self.outputs)]    2231   C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)     776     try:     777       result = self._run(None, fetches, feed_dict, options_ptr, --> 778                          run_metadata_ptr)     779       if run_metadata:     780         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)     980     if final_fetches or final_targets:     981       results = self._do_run(handle, final_targets, final_fetches, --> 982                              feed_dict_string, options, run_metadata)     983     else:     984       results = []  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)    1030     if handle is None:    1031       return self._do_call(_run_fn, self._session, feed_dict, fetch_list, -> 1032                            target_list, options, run_metadata)    1033     else:    1034       return self._do_call(_prun_fn, self._session, handle, feed_dict,  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)    1050         except KeyError:    1051           pass -> 1052       raise type(e)(node_def, op, message)    1053     1054   def _extend_graph(self):  InternalError: Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]]  Caused by op 'dense_1/MatMul', defined at:   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\runpy.py", line 193, in _run_module_as_main     "__main__", mod_spec)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\runpy.py", line 85, in _run_code     exec(code, run_globals)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py", line 3, in      app.launch_new_instance()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance     app.start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelapp.py", line 477, in start     ioloop.IOLoop.instance().start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start     super(ZMQIOLoop, self).start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\ioloop.py", line 888, in start     handler_func(fd_obj, events)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper     return fn(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events     self._handle_recv()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv     self._run_callback(callback, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback     callback(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper     return fn(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher     return self.dispatch_shell(stream, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell     handler(stream, idents, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request     user_expressions, allow_stdin)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute     res = shell.run_cell(code, store_history=store_history, silent=silent)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell     return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2683, in run_cell     interactivity=interactivity, compiler=compiler, result=result)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2787, in run_ast_nodes     if self.run_code(code, result):   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2847, in run_code     exec(code_obj, self.user_global_ns, self.user_ns)   File "", line 4, in      model.add(Dense(10, activation='softmax'))   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\models.py", line 466, in add     output_tensor = layer(self.outputs[0])   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\topology.py", line 585, in __call__     output = self.call(inputs, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\layers\core.py", line 840, in call     output = K.dot(inputs, self.kernel)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py", line 936, in dot     out = tf.matmul(x, y)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1801, in matmul     a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1263, in _mat_mul     transpose_b=transpose_b, name=name)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op     op_def=op_def)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op     original_op=self._default_original_op, op_def=op_def)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__     self._traceback = _extract_stack()  InternalError (see above for traceback): Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]] 

When I'm trying to use TensorFlow with Keras using the cpu, I'm getting this error message:

C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py:5: UserWarning: Update your `fit_generator` call to the Keras 2 API: `fit_generator( 1039       return fn(*args)    1040     except errors.OpError as e:  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)    1020                                  feed_dict, fetch_list, target_list, -> 1021                                  status, run_metadata)    1022   C:\Users\nicol\Anaconda3\envs\tensorflow\lib\contextlib.py in __exit__(self, type, value, traceback)      65             try: ---> 66                 next(self.gen)      67             except StopIteration:  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()     465           compat.as_text(pywrap_tensorflow.TF_Message(status)), --> 466           pywrap_tensorflow.TF_GetCode(status))     467   finally:  InternalError: Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]]      [[Node: Assign_3/_84 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_374_Assign_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]  During handling of the above exception, another exception occurred:  InternalError                             Traceback (most recent call last)  in ()       3 with tf.device('/cpu:0'):       4     history=model.fit_generator(batches, batches.n, nb_epoch=2,  ----> 5                     validation_data=val_batches, nb_val_samples=val_batches.n)  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)      86                 warnings.warn('Update your `' + object_name +      87                               '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 88             return func(*args, **kwargs)      89         wrapper._legacy_support_signature = inspect.getargspec(func)      90         return wrapper  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\models.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_q_size, workers, pickle_safe, initial_epoch)    1108                                         workers=workers,    1109                                         pickle_safe=pickle_safe, -> 1110                                         initial_epoch=initial_epoch)    1111     1112     @interfaces.legacy_generator_methods_support  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)      86                 warnings.warn('Update your `' + object_name +      87                               '` call to the Keras 2 API: ' + signature, stacklevel=2) ---> 88             return func(*args, **kwargs)      89         wrapper._legacy_support_signature = inspect.getargspec(func)      90         return wrapper  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_q_size, workers, pickle_safe, initial_epoch)    1888                     outs = self.train_on_batch(x, y,    1889                                                sample_weight=sample_weight, -> 1890                                                class_weight=class_weight)    1891     1892                     if not isinstance(outs, list):  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in train_on_batch(self, x, y, sample_weight, class_weight)    1631             ins = x + y + sample_weights    1632         self._make_train_function() -> 1633         outputs = self.train_function(ins)    1634         if len(outputs) == 1:    1635             return outputs[0]  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py in __call__(self, inputs)    2227         session = get_session()    2228         updated = session.run(self.outputs + [self.updates_op], -> 2229                               feed_dict=feed_dict)    2230         return updated[:len(self.outputs)]    2231   C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)     776     try:     777       result = self._run(None, fetches, feed_dict, options_ptr, --> 778                          run_metadata_ptr)     779       if run_metadata:     780         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)     980     if final_fetches or final_targets:     981       results = self._do_run(handle, final_targets, final_fetches, --> 982                              feed_dict_string, options, run_metadata)     983     else:     984       results = []  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)    1030     if handle is None:    1031       return self._do_call(_run_fn, self._session, feed_dict, fetch_list, -> 1032                            target_list, options, run_metadata)    1033     else:    1034       return self._do_call(_prun_fn, self._session, handle, feed_dict,  C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)    1050         except KeyError:    1051           pass -> 1052       raise type(e)(node_def, op, message)    1053     1054   def _extend_graph(self):  InternalError: Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]]      [[Node: Assign_3/_84 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_374_Assign_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]  Caused by op 'dense_1/MatMul', defined at:   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\runpy.py", line 193, in _run_module_as_main     "__main__", mod_spec)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\runpy.py", line 85, in _run_code     exec(code, run_globals)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py", line 3, in      app.launch_new_instance()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance     app.start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelapp.py", line 477, in start     ioloop.IOLoop.instance().start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start     super(ZMQIOLoop, self).start()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\ioloop.py", line 888, in start     handler_func(fd_obj, events)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper     return fn(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events     self._handle_recv()   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv     self._run_callback(callback, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback     callback(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper     return fn(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher     return self.dispatch_shell(stream, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell     handler(stream, idents, msg)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request     user_expressions, allow_stdin)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute     res = shell.run_cell(code, store_history=store_history, silent=silent)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell     return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2683, in run_cell     interactivity=interactivity, compiler=compiler, result=result)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2787, in run_ast_nodes     if self.run_code(code, result):   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2847, in run_code     exec(code_obj, self.user_global_ns, self.user_ns)   File "", line 4, in      model.add(Dense(10, activation='softmax'))   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\models.py", line 466, in add     output_tensor = layer(self.outputs[0])   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\engine\topology.py", line 585, in __call__     output = self.call(inputs, **kwargs)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\layers\core.py", line 840, in call     output = K.dot(inputs, self.kernel)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py", line 936, in dot     out = tf.matmul(x, y)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1801, in matmul     a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1263, in _mat_mul     transpose_b=transpose_b, name=name)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op     op_def=op_def)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op     original_op=self._default_original_op, op_def=op_def)   File "C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__     self._traceback = _extract_stack()  InternalError (see above for traceback): Blas GEMM launch failed : a.shape=(64, 784), b.shape=(784, 10), m=64, n=10, k=784      [[Node: dense_1/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](flatten_1/Reshape, dense_1/kernel/read)]]      [[Node: Assign_3/_84 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_374_Assign_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

In both cases, the error is with InternalError (see above for traceback): Blas GEMM launch failed Can you tell me how to get Blas GEMM to launch? I installed tensorflow and keras in a 3.5 python anaconda environment where I also installed all needed module (numpy, pandas, scipy, scikit-learn). I have a Windows 10 with a NVIDIA gpu that can use CUDA. I downloaded CUDA and cuDNN. I'm using the Jupyter notebook on Chrome.

Sometimes when I run my code, rather than having this error, I get that it starts running and then it crashes. After the crash, I can't do anything on my jupyter notebook and after some time a pop-up asks me if I want to kill the page. This is an image of what I got after the crash. !(http://www.hostingpics.net/viewer.php?id=647186tensorflowError.png)

P.S. I know my problem is similar as in this question: Tensorflow Basic Example Error: CUBLAS_STATUS_NOT_INITIALIZED but it has not been solved there and I'm not sure this question is clear enough or is exactly the same problem as I have so I'm posting it with my own error message. This problem is different of: TensorFlow: InternalError: Blas SGEMM launch failed Since I have a problem with GEMM rather than SGEMM and that my problem is both with gpu and cpu and it is not solved by the answer of this question.

回答1:

Had the same error. Maybe it is related to the problem that tensorflow is allocating all gpu memory. But the fix recommended there didn't work for me and it is not possible yet to limit tensorflow's gpu memory use via keras.json or commandline. Switching keras' backend to Theano resolved the issue for me (howto can be found here).



回答2:

Try running the sample program simpleCUBLAS (it comes with CUDA) to test your CUBLAS installation and see if it works.

In my case (I am using Ubuntu) I had to reinstall CUDA to solve this issue. After I did that, simpleCUBLAS passed the test.

For some reason I started running into the same issue after a while, and I found that cleaning the directory .nv (inside my home folder) resolved the issue, and simpleCUBLAS test passed again.



回答3:

I was getting exactly the same error message. I realized that there was an error with my CUDA installation, specifically with the cuBLAS library.

You can check if yours has the same problem by running the sample program simpleCUBLAS (it comes with the CUDA installation, you will probably find it in the CUDA home folder:$CUDA_HOME\samples\7_CUDALibraries\simpleCUBLAS)

Try running this program. If the test fails, you have a problem with your CUDA installation. You should try to reinstall it. That's how I solved the same problem here.



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