From 9c5c4e8c680ec939171a7c4b77a984ab09448d24 Mon Sep 17 00:00:00 2001
From: viklofg <viktoria.lofgren@riksarkivet.se>
Date: Fri, 14 Jun 2024 15:59:31 +0200
Subject: [PATCH] Delete src/htrflow_core/logging directory

---
 src/htrflow_core/logging/gpu_profiler.py  | 46 -----------------------
 src/htrflow_core/logging/line_profiler.py | 31 ---------------
 src/htrflow_core/logging/logger.py        | 25 ------------
 3 files changed, 102 deletions(-)
 delete mode 100644 src/htrflow_core/logging/gpu_profiler.py
 delete mode 100644 src/htrflow_core/logging/line_profiler.py
 delete mode 100644 src/htrflow_core/logging/logger.py

diff --git a/src/htrflow_core/logging/gpu_profiler.py b/src/htrflow_core/logging/gpu_profiler.py
deleted file mode 100644
index 3883915..0000000
--- a/src/htrflow_core/logging/gpu_profiler.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import functools
-import time
-
-import torch
-
-from htrflow_core.logging.logger import CustomLogger
-
-
-def profile_gpu_usage(verbose=0):
-    logger = CustomLogger("GPUProfiler", verbose=verbose).logger
-
-    def decorator(func):
-        @functools.wraps(func)
-        def wrapper(*args, **kwargs):
-            if torch.cuda.is_available():
-                torch.cuda.synchronize()
-                start_time = time.time()
-                start_mem = torch.cuda.memory_allocated()
-                result = func(*args, **kwargs)
-                torch.cuda.synchronize()
-                end_time = time.time()
-                end_mem = torch.cuda.memory_allocated()
-                logger.info(f"Memory Usage for {func.__name__}: {end_mem - start_mem} bytes")
-                logger.info(f"Execution Time for {func.__name__}: {end_time - start_time} seconds")
-            else:
-                logger.warning("CUDA is not available. Running the function without profiling GPU usage.")
-                result = func(*args, **kwargs)
-            return result
-
-        return wrapper
-
-    return decorator
-
-
-if __name__ == "__main__":
-
-    @profile_gpu_usage(verbose=2)
-    def my_gpu_intensive_function(tensor_size, n_operations):
-        a = torch.rand(tensor_size, tensor_size, device="cuda")
-        b = torch.rand(tensor_size, tensor_size, device="cuda")
-        for _ in range(n_operations):
-            a = a * b + torch.sin(a)
-        return a
-
-    if torch.cuda.is_available():
-        result = my_gpu_intensive_function(10000, 1000)
diff --git a/src/htrflow_core/logging/line_profiler.py b/src/htrflow_core/logging/line_profiler.py
deleted file mode 100644
index ecc33d6..0000000
--- a/src/htrflow_core/logging/line_profiler.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import time
-
-from htrflow_core.logging.logger import CustomLogger
-
-
-logger = CustomLogger("ProfileLogger", verbose=3)
-
-
-def profile_performance(func):
-    def wrapper(*args, **kwargs):
-        start_time = time.time()
-        result = func(*args, **kwargs)
-        end_time = time.time()
-        execution_time = end_time - start_time
-        # Use the custom logger for logging
-        logger.logger.debug(f"Function: {func.__name__}, Execution Time: {execution_time} seconds")
-        return result
-
-    return wrapper
-
-
-if __name__ == "__main__":
-
-    @profile_performance
-    def example_function(x):
-        result = 0
-        for i in range(x):
-            result += i
-        return result
-
-    example_function(100)
diff --git a/src/htrflow_core/logging/logger.py b/src/htrflow_core/logging/logger.py
deleted file mode 100644
index 1b2246a..0000000
--- a/src/htrflow_core/logging/logger.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import logging
-
-
-class CustomLogger:
-    def __init__(self, name, verbose=0):
-        self.logger = logging.getLogger(name)
-        self.set_verbose(verbose)
-
-        self.logger.propagate = False
-
-        if not self.logger.handlers:
-            console_handler = logging.StreamHandler()
-            formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
-            console_handler.setFormatter(formatter)
-            self.logger.addHandler(console_handler)
-
-    def set_verbose(self, verbose):
-        if verbose == 1:
-            self.logger.setLevel(logging.WARNING)
-        elif verbose == 2:
-            self.logger.setLevel(logging.INFO)
-        elif verbose >= 3:
-            self.logger.setLevel(logging.DEBUG)
-        else:
-            self.logger.setLevel(logging.ERROR)