Debug tensorboard

Author: icarosadero

pyduino/spectra.py

@@ -108,7 +108,7 @@ def __init__(self,ranges,density_param,maximize=True,log_name=None,reset_density
         self.ids = list(self.reactors.keys())
         self.sorted_ids = sorted(self.ids)
         self.log_init(name=log_name)
-        self.writer = SummaryWriter(self.log.prefix)    
+        self.writer = SummaryWriter(self.log.prefix)
         print(bcolors.OKGREEN,"[INFO]", "Created tensorboard log at", self.log.prefix, bcolors.ENDC)  
         self.payload = self.population_as_dict if self.payload is None else self.payload
         self.data = None
@@ -216,10 +216,10 @@ def log_tensor(self, i):
         This method iterates over the tensor values and fitness scores and logs them using the writer object.
         """
         print(bcolors.BOLD,"[INFO]","LOGGING",datetime.now().strftime("%c"), bcolors.ENDC)
-        for j, params in enumerate(self.view_g()):
-            for param_name, param in zip(self.parameters,params):
-                self.writer.add_scalar(f"{param_name}/{j}", param, i)
-            self.writer.add_scalar(f'Fitness/{j}', self.y[j], i)
+        for k, v in enumerate(self.y):
+            self.writer.add_scalar(f'fitness/{self.ids[k]}', v, i)
+            for j, u in enumerate(self.parameters):
+                self.writer.add_scalar(f'{u}/{self.ids[k]}', self.population[k][j], i)
 
     def gotod(self):
         self.t_gotod_1 = datetime.now()

tests/test_spectra.py

@@ -31,37 +31,4 @@ def test_oracle(self):
         assert isinstance(df, pd.DataFrame)
         y = self.g.ask_oracle(self.g.population)
     def test_logger(self):
-        self.g.GET("test")    
-    def test_log_tensor(self):
-        # Create a mock writer object
-        class MockWriter:
-            def __init__(self):
-                self.scalar_values = {}
-
-            def add_scalar(self, name, value, step):
-                if name not in self.scalar_values:
-                    self.scalar_values[name] = {}
-                self.scalar_values[name][step] = value
-
-        # Create an instance of the Spectra class
-        g = Spectra(**PATHS.HYPERPARAMETERS)
-        g.init()
-        g.y = list(range(len(g.parameters)))
-
-        # Create a mock writer object and assign it to the Spectra instance
-        mock_writer = MockWriter()
-        g.writer = mock_writer
-
-        # Call the log_tensor method
-        g.log_tensor(0)
-
-        # Assert that the scalar values were logged correctly
-        for j, params in enumerate(g.view_g()):
-            for param_name, param in zip(g.parameters, params):
-                expected_name = f"{param_name}/{j}"
-                expected_value = param
-                assert mock_writer.scalar_values[expected_name][0] == expected_value
-
-            expected_fitness_name = f"Fitness/{j}"
-            expected_fitness_value = g.y[j]
-            assert mock_writer.scalar_values[expected_fitness_name][0] == expected_fitness_value
+        self.g.GET("test")