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TensorFlow: Blas GEMM launch failed

When I try to use TensorFlow with Keras using gpu, I get the following 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(<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)]]

When I try to use TensorFlow with Keras using the CPU, I get 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(<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"]()]]

In both cases, the error is related to InternalError (see above for tracking): Blas GEMM did not start Can you tell me how to start Blas GEMM? I installed shadoworflow and keras in anaconda 3.5 python environment, where I also installed all the necessary module (numpy, pandas, scipy, scikit-learn). I have Windows 10 with NVIDIA gpu that can use CUDA. I downloaded CUDA and cuDNN. I am using a Jupyter laptop in Chrome.

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

keras/tenorflow_backend.py, config.gpu_options.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
+16

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gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.9)

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

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ps -aux | grep program_name

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kill -9 PID

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os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # Force TF to use only the CPU
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Source: https://habr.com/ru/post/1017277/

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