| 123456789101112131415161718192021222324252627282930313233343536 |
- ///////////////////////////////////////////
- // Running convGAN-majority-full on imblearn_protein_homo
- ///////////////////////////////////////////
- Load 'data_input/imblearn_protein_homo'
- from imblearn
- Data loaded.
- -> Shuffling data
- ### Start exercise for synthetic point generator
- ====== Step 1/5 =======
- -> Shuffling data
- -> Spliting data to slices
- ------ Step 1/5: Slice 1/5 -------
- -> Reset the GAN
- Traceback (most recent call last):
- File "/benchmark/data/run_all_exercises.py", line 16, in <module>
- runExercise(dataset, None, name, generators[name])
- File "/benchmark/data/library/analysis.py", line 169, in runExercise
- avg = exercise.run(gan, data, resultsFileName=resultsFileName)
- File "/benchmark/data/library/exercise.py", line 127, in run
- self._exerciseWithDataSlice(gan, sliceData, imageFileName=imageFileName)
- File "/benchmark/data/library/exercise.py", line 166, in _exerciseWithDataSlice
- gan.reset(dataSlice.train)
- File "/benchmark/data/library/generators/convGAN.py", line 133, in reset
- self.conv_sample_generator = self._conv_sample_gen()
- File "/benchmark/data/library/generators/convGAN.py", line 237, in _conv_sample_gen
- x = Dense(self.neb * self.gen, activation='relu')(x)
- File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 67, in error_handler
- raise e.with_traceback(filtered_tb) from None
- File "/usr/local/lib/python3.8/dist-packages/keras/backend.py", line 1920, in random_uniform
- return tf.random.uniform(
- tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[76516,1073296] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu [Op:RandomUniform]
|
