verbose=4 (#140)

* verbose=4 * docstrings for verbose=4
poets-ai · Jan 18, 2021 · 56d4a4c · 56d4a4c
1 parent 1e578e8
commit 56d4a4c
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Showing 2 changed files with 15 additions and 7 deletions.
diff --git a/elegy/callbacks/progbar_logger.py b/elegy/callbacks/progbar_logger.py
@@ -331,6 +331,9 @@ def update(self, current, values=None, finalize=None):
         elif self.verbose == 3:
             self.compact_table_progress(current, finalize)
 
+        elif self.verbose == 4 and finalize:
+            self.compact_table_progress(current, finalize)
+
         self._last_update = now
 
     def add(self, n, values=None):

diff --git a/elegy/model/model.py b/elegy/model/model.py
@@ -222,10 +222,12 @@ def fit(
                 The model is not trained for a number of iterations
                 given by `epochs`, but merely until the epoch
                 of index `epochs` is reached.
-            verbose: 0, 1, 2 or 3. Verbosity mode.
-                0 = silent, 1 = progress bar, 2 = one line per epoch 3 = table.
-                Note that the progress bar is not particularly useful when
-                logged to a file, so verbose=2 is recommended when not running
+            verbose: 0, 1, 2, 3 or 4. Verbosity mode.
+                0 = silent, 1 = progress bar, 2 = one line per epoch,
+                3 = table with updates per step, 4 = table with updates per epoch.
+                Note: verbosity options 1 and 3 may slow down training
+                Note: the progress bar is not particularly useful when
+                logged to a file, so verbose=2 or verbose=4 is recommended when not running
                 interactively (eg, in a production environment).
             callbacks: List of [elegy.callbacks.callback.Callback][] instances.
                 List of callbacks to apply during training.
@@ -475,8 +477,9 @@ def evaluate(
                 it could be either Numpy or Jax array(s).
                 It should be consistent with `x`. If `x` is a generator,
                 `y` should not be specified (since targets will be obtained from `x`).
-            verbose: 0, 1, or 2. Verbosity mode.
-                0 = silent, 1 = progress bar, 2 = one line per epoch.
+            verbose: 0, 1, 2, 3 or 4. Verbosity mode.
+                0 = silent, 1 = progress bar, 2 = one line per epoch
+                3 = table with updates per step, 4 = table with updates per epoch.
             batch_size: Integer or `None`.
                 Number of samples per gradient update.
                 If unspecified, `batch_size` will default to 32.
@@ -588,7 +591,9 @@ def predict(
                 If unspecified, `batch_size` will default to 32.
                 Do not specify the `batch_size` if your data is in the
                 form of generators (since they generate batches).
-            verbose: Verbosity mode, 0 or 1.
+            verbose: Verbosity mode, 0, 1, 2, 3 or 4.
+                0 = silent, 1 = progress bar, 2 = one line per epoch
+                3 = table with updates per step, 4 = table with updates per epoch.
             steps: Total number of steps (batches of samples)
                 before declaring the prediction round finished.
                 Ignored with the default value of `None`.