TensorFlow:Blas GEMM启动失败

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(<keras.pre..., 37800, epochs=2, validation_data=<keras.pre..., validation_steps=4200)` from ipykernel import kernelapp as app Epoch 1/2 InternalError Traceback (most recent call last) C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args) 1038 try: -> 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) <ipython-input-13-2a52d1079a66> in <module>() 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 <module> 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 "<ipython-input-10-1e7a3b259f23>", line 4, in <module> 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)]]

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(<keras.pre..., 37800, validation_steps=4200, validation_data=<keras.pre..., epochs=2)` Epoch 1/2 --------------------------------------------------------------------------- InternalError Traceback (most recent call last) C:\Users\nicol\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args) 1038 try: -> 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) <ipython-input-14-f66b4d3d5b88> in <module>() 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 <module> 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 "<ipython-input-12-1e7a3b259f23>", line 4, in <module> 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"]()]]

3条回答

网友

1楼 · 编辑于 2024-06-26 11:01:37

也有同样的错误。可能与tensorflow是allocating all gpu memory的问题有关。但建议的修复方法对我来说不起作用，而且还不可能通过keras.json或命令行限制tensorflow的gpu内存使用。将keras的后端切换到ano为我解决了这个问题（如何找到here）。

网友

2楼 · 编辑于 2024-06-26 11:01:37

这是一个简单的解决方案，但要想搞清楚这一切简直是一场噩梦

在Windows上，我发现Keras安装在Anaconda3\Lib\site packages\Keras中

资料来源：

https://www.tensorflow.org/guide/using_gpu

https://github.com/keras-team/keras/blob/master/keras/backend/tensorflow_backend.py

在keras/tensorflow_backend.py文件中找到以下内容您将添加config.gpu_选项。这两个位置的allow_growth=True

if _SESSION is None:
            if not os.environ.get('OMP_NUM_THREADS'):
                config = tf.ConfigProto(allow_soft_placement=True)
                config.gpu_options.allow_growth=True
            else:
                num_thread = int(os.environ.get('OMP_NUM_THREADS'))
                config = tf.ConfigProto(intra_op_parallelism_threads=num_thread,
                                        allow_soft_placement=True)
                config.gpu_options.allow_growth=True
            _SESSION = tf.Session(config=config)
        session = _SESSION

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3楼 · 编辑于 2024-06-26 11:01:37

这个答案与Tensorflow密切相关：

有时Tensorflow无法在Windows中创建。

使用gpu重新启动笔记本在大多数情况下都能解决这个问题

如果没有，请在代码中添加这些选项后尝试重新启动笔记本。

gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.9)

tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,allow_soft_placement=True)

我在使用Keras时从未遇到过这样的错误，但请尝试重新启动您的笔记本

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