UnknownError: Failed to get convolution algorithm. This is probably because c

/home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/client/session.py:1751: UserWarning: An interactive session is already active. This can cause out-of-memory errors in some cases. You must explicitly call `InteractiveSession.close()` to release resources held by the other session(s).
  warnings.warn('An interactive session is already active. This can '

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UnknownError                              Traceback (most recent call last)
Cell In[1], line 59
     54 model.add(Dense(num_classes, activation='softmax'))
     56 model.compile(loss=keras.losses.categorical_crossentropy,
     57               optimizer=keras.optimizers.Adadelta(),
     58               metrics=['accuracy'])
---> 59 model.fit(x_train, y_train,
     60           batch_size=batch_size,
     61           epochs=epochs,
     62           verbose=1,
     63           validation_data=(x_test, y_test))
     64 score = model.evaluate(x_test, y_test, verbose=0)
     65 print('Test loss:', score[0])

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:66, in enable_multi_worker.<locals>._method_wrapper(self, *args, **kwargs)
     64 def _method_wrapper(self, *args, **kwargs):
     65   if not self._in_multi_worker_mode():  # pylint: disable=protected-access
---> 66     return method(self, *args, **kwargs)
     68   # Running inside `run_distribute_coordinator` already.
     69   if dc_context.get_current_worker_context():

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:848, in Model.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_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
    841 with traceme.TraceMe(
    842     'TraceContext',
    843     graph_type='train',
    844     epoch_num=epoch,
    845     step_num=step,
    846     batch_size=batch_size):
    847   callbacks.on_train_batch_begin(step)
--> 848   tmp_logs = train_function(iterator)
    849   # Catch OutOfRangeError for Datasets of unknown size.
    850   # This blocks until the batch has finished executing.
    851   # TODO(b/150292341): Allow multiple async steps here.
    852   if not data_handler.inferred_steps:

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:580, in Function.__call__(self, *args, **kwds)
    578     xla_context.Exit()
    579 else:
--> 580   result = self._call(*args, **kwds)
    582 if tracing_count == self._get_tracing_count():
    583   self._call_counter.called_without_tracing()

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py:644, in Function._call(self, *args, **kwds)
    640     pass  # Fall through to cond-based initialization.
    641   else:
    642     # Lifting succeeded, so variables are initialized and we can run the
    643     # stateless function.
--> 644     return self._stateless_fn(*args, **kwds)
    645 else:
    646   canon_args, canon_kwds = \
    647       self._stateful_fn._function_spec.canonicalize_function_inputs(  # pylint: disable=protected-access
    648           *args, **kwds)

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/eager/function.py:2420, in Function.__call__(self, *args, **kwargs)
   2418 with self._lock:
   2419   graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
-> 2420 return graph_function._filtered_call(args, kwargs)

File /home/software/anaconda3/envs/mydlenv/lib/python3.8/site-packages/tensorflow/python/eager/function.py:1661, in ConcreteFunction._filtered_call(self, args, kwargs)
   1647