Updated for logger.

sraashis · Dec 6, 2023 · ebdf8f9 · ebdf8f9
1 parent dd0e0e2
commit ebdf8f9
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Showing 6 changed files with 28 additions and 12 deletions.
diff --git a/README.md b/README.md
@@ -59,7 +59,8 @@ class MNISTTrainer(ETRunner):
 
     def new_meter(self):
         return ETMeter(
-            cfm=ConfusionMatrix(num_classes=10, device=self.device['gpu'])
+            cfm=ConfusionMatrix(num_classes=10),
+            device=self.device['gpu']
         )
 
 
@@ -105,7 +106,8 @@ class MyTrainer(ETRunner):
         return ETMeter(
             num_averages=1,
             prf1a=Prf1a(),
-            auc=AUCROCMetrics()
+            auc=AUCROCMetrics(),
+            device=self.device['gpu']
         )
 
     def init_cache(self):

diff --git a/easytorch/easytorch.py b/easytorch/easytorch.py
@@ -229,7 +229,7 @@ def _run_test(self, data_split, engine, dataset_cls, distributed=False) -> dict:
         """ Run and save experiment test scores """
         engine.cache[
             'output_csv_TEST'
-        ] = f"{engine.conf['save_dir']}{_sep}test_results_{engine.conf['RUN-ID']}.csv"
+        ] = f"{engine.conf['save_dir']}{_sep}{engine.conf['RUN-ID']}_test_results.csv"
         with open(engine.cache[f'output_csv_TEST'], 'w') as rw:
             test_out = engine.evaluation(dataloader=dataloader, mode=Phase.TEST,
                                          save_predictions=True, results_writer=rw)
@@ -251,7 +251,7 @@ def _inference(self, data_split, engine, dataset_cls):
 
         engine.cache[
             'output_csv_INFERENCE'
-        ] = f"{engine.conf['save_dir']}{_sep}inference_results_{engine.conf['RUN-ID']}.csv"
+        ] = f"{engine.conf['save_dir']}{_sep}{engine.conf['RUN-ID']}_inference_results.csv"
         with open(engine.cache[f'output_csv_INFERENCE'], 'w') as rw:
             engine.inference(dataloader=dataloader, results_writer=rw)
 
@@ -274,7 +274,13 @@ def run(self, runner_cls: typing.Type[ETRunner],
             self._run(runner_cls, dataset_cls, data_handle_cls)
 
     def _run(self, runner_cls, dataset_cls, data_handle_cls):
-        self.conf['RUN-ID'] = f"RUN{self.conf.get('world_rank', 0)}-" + _uuid.uuid4().hex[:8].upper()
+        run_id_parts = [
+            _dtime.now().strftime(f'%Y-%m-%d_%H%M%S'),
+            f"R{self.conf.get('world_rank', 0)}",
+            _uuid.uuid4().hex[:8].upper()
+        ]
+
+        self.conf['RUN-ID'] = "-".join(run_id_parts)
 
         engine = runner_cls(
             conf=self.conf,
@@ -285,7 +291,8 @@ def _run(self, runner_cls, dataset_cls, data_handle_cls):
         )
 
         engine.cache['START-TIME'] = _dtime.now().strftime("%Y-%m-%d %H:%M:%S")
-        _utils.save_cache(self.conf, {}, name=f"{self.conf['name']}_{self.conf['phase']}".upper())
+        _utils.save_cache(self.conf, {},
+                          name=f"{engine.conf['RUN-ID']}_{self.conf['name']}_{self.conf['phase']}")
 
         self._prepare_nn_engine(engine)
 
@@ -303,4 +310,5 @@ def _run(self, runner_cls, dataset_cls, data_handle_cls):
             self._inference(data_split, engine, dataset_cls)
         _cleanup(engine, engine.data_handle)
         engine.cache['END-TIME'] = _dtime.now().strftime("%Y-%m-%d %H:%M:%S")
-        _utils.save_cache(self.conf, engine.cache, name=f"{engine.conf['name']}_{self.conf['phase']}".upper())
+        _utils.save_cache(self.conf, engine.cache,
+                          name=f"{engine.conf['RUN-ID']}_{self.conf['name']}_{self.conf['phase']}")
diff --git a/easytorch/metrics/metrics.py b/easytorch/metrics/metrics.py
@@ -167,9 +167,13 @@ def dist_gather(self, device='cpu'):
 
 
 class ETMeter:
-    def __init__(self, num_averages=1, **kw):
+    def __init__(self, num_averages=1, device='cpu', **kw):
         self.averages = ETAverages(num_averages)
+        self.device = device
         self.metrics = {**kw}
+        for mk in self.metrics:
+            self.metrics[mk].device = self.device
+            self.metrics[mk].reset()
 
     def get(self):
         res = self.averages.get()

diff --git a/examples/MNIST_easytorch_CNN.ipynb b/examples/MNIST_easytorch_CNN.ipynb
@@ -119,8 +119,9 @@
     "    def new_meter(self):\n",
     "        return ETMeter(\n",
     "            num_averages=2,  # Since we are tracing two losses\n",
-    "            cmf=ConfusionMatrix(num_classes=10, device=self.device['gpu']),\n",
-    "            auc=AUCROCMetrics()\n",
+    "            cmf=ConfusionMatrix(num_classes=10),\n",
+    "            auc=AUCROCMetrics(),\n",
+    "            device=self.device['gpu']\n",
     "        )"
    ]
   },

diff --git a/examples/MNIST_easytorch_CNN.py b/examples/MNIST_easytorch_CNN.py
@@ -42,8 +42,9 @@ def init_cache(self):
     def new_meter(self):
         return ETMeter(
             num_averages=2,  # Since we are tracing two losses
-            cmf=ConfusionMatrix(num_classes=10, device=self.device['gpu']),
+            cmf=ConfusionMatrix(num_classes=10),
             auc=AUCROCMetrics(),
+            device=self.device['gpu']
         )
 
 

diff --git a/setup.py b/setup.py
@@ -29,7 +29,7 @@
 # This call to setup() does all the work
 setup(
     name="easytorch",
-    version="3.8.4",
+    version="3.8.5",
     description="Easy Neural Network Experiments with pytorch",
     long_description=_README,
     long_description_content_type="text/markdown",