Upgrade version

CHANGELOGS.rst

@@ -1,6 +1,9 @@
 Change Logs
 ===========
 
+0.7.9
++++++
+
 0.7.8
 +++++
 

_doc/index.rst

@@ -239,9 +239,8 @@ The function replaces dynamic dimensions defined as strings by
 Older versions
 ==============
 
+* `0.7.9 <../v0.7.9/index.html>`_
 * `0.7.8 <../v0.7.8/index.html>`_
-* `0.7.7 <../v0.7.7/index.html>`_
-* `0.7.6 <../v0.7.6/index.html>`_
 * `0.6.3 <../v0.6.3/index.html>`_
 * `0.5.0 <../v0.5.0/index.html>`_
 * `0.4.4 <../v0.4.4/index.html>`_

_unittests/ut_tasks/test_tasks.py

@@ -293,7 +293,7 @@ def test_falcon_mamba_dev(self):
         model(**inputs)
         model(**data["inputs2"])
         self.assertIn((data["size"], data["n_weights"]), [(274958336, 68739584)])
-        if not has_transformers("4.56"):
+        if not has_transformers("4.57"):
             raise unittest.SkipTest("The model has control flow.")
         with torch_export_patches(patch_transformers=True, verbose=10, stop_if_static=1):
             torch.export.export(

_unittests/ut_tasks/test_tasks_image_text_to_text.py

@@ -29,7 +29,7 @@ def test_image_text_to_text_idefics(self):
             )
 
     @hide_stdout()
-    @requires_transformers("4.56.99")
+    @requires_transformers("4.57.99")
     @requires_torch("2.7.99")
     def test_image_text_to_text_gemma3(self):
         """
@@ -53,7 +53,7 @@ def test_image_text_to_text_gemma3(self):
             )
 
     @hide_stdout()
-    @requires_transformers("4.56.99")
+    @requires_transformers("4.57.99")
     @requires_torch("2.7.99")
     def test_image_text_to_text_zai_glm(self):
         """

onnx_diagnostic/__init__.py

@@ -3,5 +3,5 @@
 Functions, classes to dig into a model when this one is right, slow, wrong...
 """
 
-__version__ = "0.7.8"
+__version__ = "0.7.9"
 __author__ = "Xavier Dupré"

onnx_diagnostic/_command_lines_parser.py

@@ -850,13 +850,13 @@ def get_parser_agg() -> ArgumentParser:
         "--filter-in",
         default="",
         help="adds a filter to filter in data, syntax is\n"
-        '``"<column1>:<value1>;<value2>/<column2>:<value3>"`` ...',
+        '``"<column1>:<value1>;<value2>//<column2>:<value3>"`` ...',
     )
     parser.add_argument(
         "--filter-out",
         default="",
         help="adds a filter to filter out data, syntax is\n"
-        '``"<column1>:<value1>;<value2>/<column2>:<value3>"`` ...',
+        '``"<column1>:<value1>;<value2>//<column2>:<value3>"`` ...',
     )
     parser.add_argument(
         "--sbs",

onnx_diagnostic/helpers/_log_helper.py

@@ -118,9 +118,11 @@ def _f(fmt):
         if isinstance(fmt, str):
             cols = fmt.split("//")
             for c in cols:
-                assert ":" in c, f"Unexpected value {c!r} in fmt={fmt!r}"
+                assert ":" in c, f"Unexpected value {c!r} in fmt={fmt!r}, cols={cols!r}"
                 spl = c.split(":")
-                assert len(spl) == 2, f"Unexpected value {c!r} in fmt={fmt!r}"
+                assert (
+                    len(spl) == 2
+                ), f"Unexpected value {c!r} in fmt={fmt!r}, spl={spl}, cols={cols}"
                 name, fil = spl
                 cond[name] = set(fil.split(";"))
         return cond

onnx_diagnostic/helpers/log_helper.py

@@ -1,5 +1,6 @@
 import enum
 import io
+import os
 import pprint
 import re
 import warnings
@@ -270,6 +271,10 @@ def _make_loop(cls, ensemble, verbose):
     def _to_images_bar(
         self, verbose: int = 0, merge: bool = True, title_suffix: Optional[str] = None
     ) -> List[bytes]:
+        """
+        Environment variable ``FIGSIZEH`` can be set to increase the
+        graph height. Default is 1.0.
+        """
         assert merge, f"merge={merge} not implemented yet"
         import matplotlib.pyplot as plt
 
@@ -279,7 +284,8 @@ def _to_images_bar(
         n_cols = 3
         nn = df.shape[1] // n_cols
         nn += int(df.shape[1] % n_cols != 0)
-        fig, axs = plt.subplots(nn, n_cols, figsize=(6 * n_cols, nn * df.shape[0] / 5))
+        ratio = float(os.environ.get("FIGSIZEH", "1"))
+        fig, axs = plt.subplots(nn, n_cols, figsize=(6 * n_cols, nn * df.shape[0] / 3 * ratio))
         pos = 0
         imgs = []
         for c in self._make_loop(df.columns, verbose):