project-codenet / model-experiments /token-based-similarity-classification /src /CommonFunctions /Utilities.py
| """ | |
| Module defining some utility functions used with ML applications | |
| """ | |
| import os | |
| import sys | |
| import numpy as np | |
| import tensorflow as tf | |
| import random as python_random | |
| def resetSeeds(): | |
| """ | |
| Reset system seeds for random generators | |
| """ | |
| np.random.seed(123) | |
| python_random.seed(123) | |
| tf.random.set_seed(1234) | |
| def setupCheckpoint(checkpoint_dir): | |
| """ | |
| Set up writing down checkpoints: | |
| - Make checkpoint directory is it does not exist | |
| - Find latest checkpoint | |
| Parameter: | |
| - checkpoint_dir -- Directory for writing down checkpoints | |
| Returns: | |
| """ | |
| if not os.path.exists(checkpoint_dir): | |
| os.makedirs(checkpoint_dir) | |
| latest_checkpoint = None | |
| else: | |
| checkpoints = [checkpoint_dir + "/" + name for | |
| name in os.listdir(checkpoint_dir)] | |
| latest_checkpoint = max(checkpoints, key=os.path.getctime) \ | |
| if checkpoints else None | |
| return latest_checkpoint | |
| def getCheckpoint(checkpoint_dir, checkpoint = None): | |
| """ | |
| Get either the specified checkpoint or the latest one | |
| Parameters: | |
| - checkpoint_dir -- Directory with checkpoints | |
| - checkpoint -- Checkpoint file name | |
| Returns: full path to checkpoint file | |
| """ | |
| if not checkpoint_dir: | |
| sys.exit("Directory with DNN models is not defined") | |
| if not os.path.exists(checkpoint_dir): | |
| sys.exit(f"Directory {checkpoint_dir} with DNN models does not exist") | |
| if checkpoint: | |
| if os.path.exists(f"{checkpoint_dir}/checkpoint"): | |
| return ckpt_file | |
| else: | |
| sys.exit(f"Directory {checkpoint_dir} does not have checkpoint {checkpoint}") | |
| checkpoints = [checkpoint_dir + "/" + name for | |
| name in os.listdir(checkpoint_dir)] | |
| if checkpoints: | |
| return max(checkpoints, key=os.path.getctime) | |
| else: | |
| sys.exit(f"Directory {checkpoint_dir} with DNN models is empty") | |
| def makeCkptCallback(checkpoint_dir, monitor = "val_accuracy"): | |
| """ | |
| - Create callback function for writing down checkpoints | |
| Parameter: | |
| - checkpoint_dir -- Directory for writing down checkpoints | |
| - monitor -- value to monitor | |
| Returns: | |
| - Callback function created | |
| """ | |
| checkpoint_callback = tf.keras.callbacks.ModelCheckpoint( | |
| filepath = checkpoint_dir + "/ckpt-{epoch}", | |
| monitor = monitor, | |
| verbose = 0, save_best_only = True, | |
| save_weights_only = False, | |
| mode = "auto", save_freq= "epoch") | |
| return checkpoint_callback | |
| def memoryUsage(point): | |
| """ | |
| Print memory usage | |
| Parameter: | |
| - point -- identifier of print: string or number | |
| """ | |
| from resource import getrusage, RUSAGE_SELF | |
| _resource_usage = getrusage(RUSAGE_SELF) | |
| print(f"{point}: MEMORY = {_resource_usage.ru_maxrss}") | |
| def makeFilePath(*parts, m = None): | |
| """ | |
| Make path to file and check its existance | |
| Check if the path exists and exit if it is not found | |
| The existance of the path is checked only if | |
| the description of file is defined | |
| Parameters: | |
| - m -- description of the path to pringt in the message | |
| if the path does not exist | |
| - parts -- parts to concatenate to get file path | |
| """ | |
| _p = "/".join(parts).replace("//", "/") | |
| if m and not os.path.exists(_p): | |
| sys.exit(f"{m} {_p} is not found") | |
| return _p | |
| ''' | |
| def accessModules(*modules): | |
| """ | |
| Update sys.path to access required modules | |
| Parameters: | |
| - modules -- modules to access | |
| """ | |
| main_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) | |
| ''' | |