Add np.ndarray as a recognized type for TB histograms.

docs/misc/changelog.rst

@@ -53,6 +53,7 @@ New Features:
 ^^^^^^^^^^^^^
 - Added Python 3.11 support
 - Added Gymnasium 0.29 support (@pseudo-rnd-thoughts)
+- Enabled np.ndarray logging for TensorBoardOutputFormat as histogram (see GH#1634) (@iwishwasaneagle)
 
 `SB3-Contrib`_
 ^^^^^^^^^^^^^^

stable_baselines3/common/logger.py

@@ -412,8 +412,18 @@ def write(self, key_values: Dict[str, Any], key_excluded: Dict[str, Tuple[str, .
                 else:
                     self.writer.add_scalar(key, value, step)
 
-            if isinstance(value, th.Tensor):
-                self.writer.add_histogram(key, value, step)
+            if isinstance(value, (th.Tensor, np.ndarray)):
+                try:
+                    self.writer.add_histogram(key, value, step)
+                except TypeError:
+                    warnings.warn(
+                        "A numpy.ndarray was passed to write which threw a "
+                        "TypeError. This is most likely due to an outdated numpy version (<1.24.0) and/or "
+                        "an outdated torch version (<2.0.0). The ndarray will be converted to a torch.Tensor "
+                        "as a workaround. For more information, "
+                        "see https://github.com/DLR-RM/stable-baselines3/pull/1635"
+                    )
+                    self.writer.add_histogram(key, th.from_numpy(value), step)
 
             if isinstance(value, Video):
                 self.writer.add_video(key, value.frames, step, value.fps)

tests/test_logger.py

@@ -1,3 +1,4 @@
+import functools
 import importlib.util
 import os
 import sys
@@ -250,6 +251,62 @@ def test_report_video_to_unsupported_format_raises_error(tmp_path, unsupported_f
     writer.close()
 
 
+_called = None
+
+
+def get_fail_first_then_pass_fn(fn, exception=Exception):
+    _called = False
+
+    @functools.wraps(fn)
+    def _fn(*args, **kwargs):
+        global _called
+        if not _called:
+            _called = True
+            raise exception()
+        return fn(*args, **kwargs)
+
+    return _fn
+
+
+@pytest.mark.parametrize(
+    "histogram,fail_first_write",
+    [
+        (th.rand(100), False),
+        (np.random.rand(100), False),
+        (np.random.rand(100), True),
+    ],
+)
+def test_report_histogram_to_tensorboard(tmp_path, read_log, fail_first_write, histogram):
+    pytest.importorskip("tensorboard")
+
+    writer = make_output_format("tensorboard", tmp_path)
+
+    if fail_first_write:
+        writer.writer.add_histogram = get_fail_first_then_pass_fn(writer.writer.add_histogram, TypeError)
+
+    writer.write({"data": histogram}, key_excluded={"data": ()})
+
+    log = read_log("tensorboard")
+
+    assert not log.empty
+    assert any("data" in f for f in log.lines)
+    assert any("Histogram" in f for f in log.lines)
+
+    writer.close()
+
+
+@pytest.mark.parametrize("histogram", [list(np.random.rand(100)), tuple(np.random.rand(100)), "1 2 3 4"])
+def test_report_unsupported_type_as_histogram_to_tensorboard(tmp_path, read_log, histogram):
+    pytest.importorskip("tensorboard")
+
+    writer = make_output_format("tensorboard", tmp_path)
+    writer.write({"data": histogram}, key_excluded={"data": ()})
+
+    assert all("Histogram" not in f for f in read_log("tensorboard").lines)
+
+    writer.close()
+
+
 def test_report_image_to_tensorboard(tmp_path, read_log):
     pytest.importorskip("tensorboard")