[engine.trainer] Save more informative constants when using an MPS compute engine

src/mednet/engine/trainer.py

@@ -14,7 +14,12 @@ import lightning.pytorch.loggers
 import torch.nn
 
 from ..utils.checkpointer import CHECKPOINT_ALIASES
-from ..utils.resources import ResourceMonitor, cpu_constants, cuda_constants
+from ..utils.resources import (
+    ResourceMonitor,
+    cpu_constants,
+    cuda_constants,
+    mps_constants,
+)
 from .callbacks import LoggingCallback
 from .device import DeviceManager, SupportedPytorchDevice
 
@@ -96,11 +101,13 @@ def static_information_to_csv(
                 if results is not None:
                     logdata.update(results)
             case "mps":
-                pass
+                results = mps_constants()
+                if results is not None:
+                    logdata.update(results)
             case _:
                 pass
 
-        logdata["model_size"] = model_size
+        logdata["number-of-model-parameters"] = model_size
         logwriter = csv.DictWriter(f, fieldnames=logdata.keys())
         logwriter.writeheader()
         logwriter.writerow(logdata)

src/mednet/utils/resources.py

@@ -77,6 +77,73 @@ def run_nvidia_smi(
     return retval
 
 
+def run_powermetrics(
+    time_window_ms: int = 500, key: str | None = None
+) -> dict[str, typing.Any] | None:
+    """Returns GPU information from the system.
+
+    For a comprehensive list of options and help, execute ``man powermetrics``
+    on a Mac computer with Apple silicon.
+
+
+    Parameters
+    ----------
+
+    time_window_ms
+        The amount of time, in milliseconds, to collect usage information on
+        the GPU.
+
+    key
+        If specified returns only a sub-key of the dictionary.
+
+
+    Returns
+    -------
+
+    data
+        A dictionary containing the GPU information.
+    """
+
+    cmd = [
+        "sudo",
+        "-n",
+        "/usr/bin/powermetrics",
+        "--samplers",
+        "gpu_power",
+        f"-i{time_window_ms}",
+        "-n1",
+        "-fplist",
+    ]
+
+    try:
+        raw_bytes = subprocess.check_output(cmd)
+        data = plistlib.loads(raw_bytes)
+        return data[key] if key is not None else data
+
+    except subprocess.CalledProcessError:
+        import inspect
+        import warnings
+
+        warnings.warn(
+            inspect.cleandoc(
+                f"""Cannot run `sudo powermetrics` without a password. Probably,
+                you did not setup sudo to execute the macOS CLI application
+                `powermetrics` passwordlessly and therefore this warning is
+                being issued. This does not affect the running of your model
+                training, only the ability of the resource monitor of gathering
+                GPU usage information on macOS while using the MPS compute
+                backend.  To configure this properly and get rid of this
+                warning, execute `sudo visudo` and add the following line where
+                suitable: `yourusername ALL=(ALL) NOPASSWD:SETENV:
+                /usr/bin/powermetrics`. Replace `yourusername` by your actual
+                username on the machine. Test the setup running the command
+                `{' '.join(cmd)}` by hand."""
+            )
+        )
+
+    return None
+
+
 def cuda_constants() -> dict[str, str | int | float] | None:
     """Returns GPU (static) information using nvidia-smi.
 
@@ -85,7 +152,6 @@ def cuda_constants() -> dict[str, str | int | float] | None:
     Returns
     -------
 
-    data : :py:class:`tuple`, None
         If ``nvidia-smi`` is not available, returns ``None``, otherwise, we
         return a dictionary containing the following ``nvidia-smi`` query
         information, in this order:
@@ -105,6 +171,37 @@ def cuda_constants() -> dict[str, str | int | float] | None:
     return retval
 
 
+def mps_constants() -> dict[str, str | int | float] | None:
+    """Returns GPU (static) information using `/usr/bin/powermetrics`.
+
+    Returns
+    -------
+
+    data : :py:class:`tuple`, None
+        If ``nvidia-smi`` is not available, returns ``None``, otherwise, we
+        return a dictionary containing the following ``nvidia-smi`` query
+        information, in this order:
+
+        * ``gpu_name``, as ``gpu_name`` (:py:class:`str`)
+        * ``driver_version``, as ``gpu_driver_version`` (:py:class:`str`)
+        * ``memory.total``, as ``gpu_memory_total`` (transformed to gigabytes,
+          :py:class:`float`)
+    """
+
+    raw_bytes = subprocess.check_output(
+        ["/usr/sbin/system_profiler", "-xml", "SPDisplaysDataType"]
+    )
+    data = plistlib.loads(raw_bytes)
+    name = data[0]["_items"][0]["_name"]
+    no_gpu_cores = int(data[0]["_items"][0]["sppci_cores"])
+
+    return {
+        "apple-processor-model": name,
+        "number-cpu-cores": multiprocessing.cpu_count(),
+        "number-gpu-cores": no_gpu_cores,
+    }
+
+
 def cuda_log() -> dict[str, float] | None:
     """Returns GPU information about current non-static status using nvidia-
     smi.
@@ -114,7 +211,6 @@ def cuda_log() -> dict[str, float] | None:
     Returns
     -------
 
-    data
         If ``nvidia-smi`` is not available, returns ``None``, otherwise, we
         return a dictionary containing the following ``nvidia-smi`` query
         information, in this order:
@@ -153,7 +249,6 @@ def mps_log() -> dict[str, float] | None:
     Returns
     -------
 
-    data
         If ``sudo powermetrics`` is not executable (or is not configured for
         passwordless execution), returns ``None``, otherwise, we return a
         dictionary containing the following query information, in this order:
@@ -163,47 +258,15 @@ def mps_log() -> dict[str, float] | None:
           (:py:class:`float`, in percent)
     """
 
-    cmd = [
-        "sudo",
-        "-n",
-        "/usr/bin/powermetrics",
-        "--samplers",
-        "gpu_power",
-        "-i500",
-        "-n1",
-        "-fplist",
-    ]
+    result = run_powermetrics(500, key="gpu")
 
-    try:
-        raw_bytes = subprocess.check_output(cmd)
-        data = plistlib.loads(raw_bytes)
-        return {
-            "frequency-MHz/gpu": float(data["gpu"]["freq_hz"]),
-            "percent-usage/gpu": 100 * (1 - data["gpu"]["idle_ratio"]),
-        }
-
-    except subprocess.CalledProcessError:
-        import inspect
-        import warnings
-
-        warnings.warn(
-            inspect.cleandoc(
-                f"""Cannot run `sudo powermetrics` without a password. Probably,
-                you did not setup sudo to execute the macOS CLI application
-                `powermetrics` passwordlessly and therefore this warning is
-                being issued. This does not affect the running of your model
-                training, only the ability of the resource monitor of gathering
-                GPU usage information on macOS while using the MPS compute
-                backend.  To configure this properly and get rid of this
-                warning, execute `sudo visudo` and add the following line where
-                suitable: `yourusername ALL=(ALL) NOPASSWD:SETENV:
-                /usr/bin/powermetrics`. Replace `yourusername` by your actual
-                username on the machine. Test the setup running the command
-                `{' '.join(cmd)}` by hand."""
-            )
-        )
+    if result is None:
+        return result
 
-    return None
+    return {
+        "frequency-MHz/gpu": float(result["freq_hz"]),
+        "percent-usage/gpu": 100 * (1 - result["idle_ratio"]),
+    }
 
 
 def cpu_constants() -> dict[str, int | float]:
@@ -212,8 +275,7 @@ def cpu_constants() -> dict[str, int | float]:
     Returns
     -------
 
-    data
-        An ordered dictionary (organized as 2-tuples) containing these entries:
+        A dictionary containing these entries:
 
         0. ``cpu_memory_total`` (:py:class:`float`): total memory available,
            in gigabytes