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Geant4/examples/extended/parameterisations/Par04/training/utils/gpu_limiter.py

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Diff markup

Differences between /examples/extended/parameterisations/Par04/training/utils/gpu_limiter.py (Version 11.3.0) and /examples/extended/parameterisations/Par04/training/utils/gpu_limiter.py (Version 11.2.1)


  1 import os                                           1 import os
  2 from dataclasses import dataclass                   2 from dataclasses import dataclass
  3                                                     3 
  4 import tensorflow as tf                             4 import tensorflow as tf
  5                                                     5 
  6                                                     6 
  7 @dataclass                                          7 @dataclass
  8 class GPULimiter:                                   8 class GPULimiter:
  9     """                                             9     """
 10     Class responsible to set the limits of pos     10     Class responsible to set the limits of possible GPU usage by TensorFlow. Currently, the limiter creates one
 11     instance of logical device per physical de     11     instance of logical device per physical device. This can be changed in a future.
 12                                                    12 
 13     Attributes:                                    13     Attributes:
 14         _gpu_ids: A string representing visibl     14         _gpu_ids: A string representing visible devices for the process. Identifiers of physical GPUs should
 15             be separated by commas (no spaces)     15             be separated by commas (no spaces).
 16         _max_gpu_memory_allocation: An integer     16         _max_gpu_memory_allocation: An integer specifying limit of allocated memory per logical device.
 17                                                    17 
 18     """                                            18     """
 19     _gpu_ids: str                                  19     _gpu_ids: str
 20     _max_gpu_memory_allocation: int                20     _max_gpu_memory_allocation: int
 21                                                    21 
 22     def __call__(self):                            22     def __call__(self):
 23         os.environ["CUDA_VISIBLE_DEVICES"] = f     23         os.environ["CUDA_VISIBLE_DEVICES"] = f"{self._gpu_ids}"
 24         gpus = tf.config.list_physical_devices     24         gpus = tf.config.list_physical_devices('GPU')
 25         if gpus:                                   25         if gpus:
 26             # Restrict TensorFlow to only allo     26             # Restrict TensorFlow to only allocate max_gpu_memory_allocation*1024 MB of memory on one of the GPUs
 27             try:                                   27             try:
 28                 for gpu in gpus:                   28                 for gpu in gpus:
 29                     tf.config.set_logical_devi     29                     tf.config.set_logical_device_configuration(
 30                         gpu,                       30                         gpu,
 31                         [tf.config.LogicalDevi     31                         [tf.config.LogicalDeviceConfiguration(memory_limit=1024 * self._max_gpu_memory_allocation)])
 32                 logical_gpus = tf.config.list_     32                 logical_gpus = tf.config.list_logical_devices('GPU')
 33                 print(len(gpus), "Physical GPU     33                 print(len(gpus), "Physical GPUs,", len(logical_gpus), "Logical GPUs")
 34             except RuntimeError as e:              34             except RuntimeError as e:
 35                 # Virtual devices must be set      35                 # Virtual devices must be set before GPUs have been initialized
 36                 print(e)                           36                 print(e)