Show progress bar while fitting to training data

autosklearn/automl.py

@@ -600,7 +600,6 @@ def fit(
         -------
         self
         """
-        progress_bar = ProgressBar(total=self._time_for_task, disable=self.disable_progress_bar)
         if (X_test is not None) ^ (y_test is not None):
             raise ValueError("Must provide both X_test and y_test together")
 
@@ -630,6 +629,9 @@ def fit(
         # By default try to use the TCP logging port or get a new port
         self._logger_port = logging.handlers.DEFAULT_TCP_LOGGING_PORT
 
+        progress_bar = ProgressBar(
+            total=self._time_for_task, disable=self.disable_progress_bar
+        )
         # Once we start the logging server, it starts in a new process
         # If an error occurs then we want to make sure that we exit cleanly
         # and shut it down, else it might hang

autosklearn/estimators.py

@@ -382,6 +382,10 @@ def __init__(
             Whether autosklearn should process string features. By default the
             textpreprocessing is enabled.
 
+        disable_progress_bar: bool = False
+            Whether to disable the progress bar that is displayed in the console
+            while fitting to the training data.
+
         Attributes
         ----------
         cv_results_ : dict of numpy (masked) ndarrays
@@ -527,7 +531,7 @@ def build_automl(self):
             get_trials_callback=self.get_trials_callback,
             dataset_compression=self.dataset_compression,
             allow_string_features=self.allow_string_features,
-            disable_progress_bar=self.disable_progress_bar
+            disable_progress_bar=self.disable_progress_bar,
         )
 
         return automl

autosklearn/experimental/askl2.py

@@ -166,6 +166,7 @@ def __init__(
         load_models: bool = True,
         dataset_compression: Union[bool, Mapping[str, Any]] = True,
         allow_string_features: bool = True,
+        disable_progress_bar: bool = False,
     ):
 
         """
@@ -284,6 +285,10 @@ def __init__(
         load_models : bool, optional (True)
             Whether to load the models after fitting Auto-sklearn.
 
+        disable_progress_bar: bool = False
+            Whether to disable the progress bar that is displayed in the console
+            while fitting to the training data.
+
         Attributes
         ----------
 
@@ -337,6 +342,7 @@ def __init__(
             scoring_functions=scoring_functions,
             load_models=load_models,
             allow_string_features=allow_string_features,
+            disable_progress_bar=disable_progress_bar,
         )
 
     def train_selectors(self, selected_metric=None):

autosklearn/util/progress_bar.py

@@ -1,38 +1,65 @@
+import datetime
 import time
-
 from threading import Thread
-from tqdm import trange
+
+from tqdm import trange  # type: ignore
 
 
 class ProgressBar(Thread):
-    """A Thread that displays a tqdm progress bar in the console."""
+    """
+    A Thread that displays a tqdm progress bar in the console.
 
-    def __init__(self, total: float, update_interval: float = 1.0, disable: bool = False):
-        """
-        Parameters
-        ----------
-        total: the total amount that the progress bar should reach
-        update_interval: reduce this to update the progress bar more frequently
-        disable: flag that turns on or off the progress bar. If false, then no thread is started or created.
-        """
+    It is specialized to display information relevant to fitting to the training data
+    with auto-sklearn.
+
+    Parameters
+    ----------
+    total : int
+        The total amount that should be reached by the progress bar once it finishes
+    update_interval : float
+        Specifies how frequently the progress bar is updated (in seconds)
+    disable : bool
+        Turns on or off the progress bar. If True, this thread won't be started or
+        initialized.
+    """
+
+    def __init__(
+        self,
+        total: int,
+        update_interval: float = 1.0,
+        disable: bool = False,
+    ):
         self.disable = disable
         if not disable:
             super().__init__(name="_progressbar_")
             self.total = total
             self.update_interval = update_interval
             self.terminated: bool = False
+            # start this thread
             self.start()
 
-    def run(self):
+    def run(self) -> None:
+        """
+        Overrides the run method of Thread. It displays a tqdm progress bar in the
+        console with useful descriptions about the task.
+
+        """
         if not self.disable:
-            for _ in trange(self.total, colour="green"):
+            for _ in trange(
+                self.total,
+                colour="green",
+                desc="Fitting to the training data",
+                postfix=f"The total time budget for this task is"
+                f" {datetime.timedelta(seconds=self.total)}",
+            ):
                 if not self.terminated:
                     time.sleep(self.update_interval)
-                else:
-                    pass  # max out the bar
+            print("Finishing up the task...")
 
-    def stop(self):
+    def stop(self) -> None:
+        """
+        Terminates the thread.
+        """
         if not self.disable:
             self.terminated = True
             super().join()
-

requirements.txt

@@ -14,8 +14,9 @@ pyyaml
 pandas>=1.0
 liac-arff
 threadpoolctl
+tqdm
 
 ConfigSpace>=0.4.21,<0.5
 pynisher>=0.6.3,<0.7
 pyrfr>=0.8.1,<0.9
-smac>=1.2,<1.3
+smac>=1.2,<1.3