Feature/print value helper

__init__.py

@@ -0,0 +1 @@
+from pymc.printing import print_value

printing.py

@@ -0,0 +1,47 @@
+# pymc/printing.py
+
+"""Helper utilities for debugging PyMC models."""
+
+from pytensor.printing import Print
+
+__all__ = ["print_value"]
+
+
+def print_value(var, name=None):
+    """Print the value of a variable each time it is computed during sampling.
+
+    This wraps the variable in a ``pytensor.printing.Print`` op, which is a
+    pass-through that prints the variable's value as a side effect whenever it
+    is evaluated.
+
+    .. warning::
+        This may significantly affect sampling performance. Use only for
+        debugging purposes.
+
+    Parameters
+    ----------
+    var : TensorVariable
+        The PyMC variable to debug-print.
+    name : str, optional
+        Label shown in the printed output. Defaults to ``var.name``.
+
+    Returns
+    -------
+    TensorVariable
+        The same variable, wrapped in a Print op (value is unchanged).
+
+    Examples
+    --------
+    .. code-block:: python
+
+        import pymc as pm
+
+        with pm.Model():
+            mu = pm.Normal("mu", mu=0, sigma=1)
+            mu = pm.print_value(mu, name="mu")   # prints mu during sampling
+            obs = pm.Normal("obs", mu=mu, sigma=1, observed=[1, 2, 3])
+            idata = pm.sample()
+    """
+    if name is None:
+        name = getattr(var, "name", "value")
+    return Print(name)(var)

pymc/__init__.py

@@ -78,5 +78,5 @@ def __set_compiler_flags():
 from pymc.util import drop_warning_stat
 from pymc.variational import *
 from pymc.vartypes import *
-
+from pymc.printing import print_value
 __version__ = _version.get_versions()["version"]

tests/test_print_value.py

@@ -0,0 +1,39 @@
+# tests/test_printing.py
+
+import pymc as pm
+import pytensor.tensor as pt
+from pytensor.printing import Print
+from pymc.printing import print_value
+
+
+def test_print_value_is_passthrough():
+    """print_value should not change the variable's value."""
+    x = pt.vector("x")
+    x_printed = print_value(x, name="test_x")
+
+    import pytensor
+    import numpy as np
+
+    f = pytensor.function([x], x_printed)
+    result = f([1.0, 2.0, 3.0])
+    np.testing.assert_array_equal(result, [1.0, 2.0, 3.0])
+
+
+def test_print_value_default_name():
+    """print_value should use var.name if no name is given."""
+    x = pt.vector("my_var")
+    x_printed = print_value(x)
+    # The Print op's message should match the variable name
+    assert x_printed.owner.op.message == "my_var"
+
+
+def test_print_value_custom_name():
+    """print_value should use the custom name when provided."""
+    x = pt.vector("x")
+    x_printed = print_value(x, name="custom_label")
+    assert x_printed.owner.op.message == "custom_label"
+
+
+def test_print_value_accessible_from_pm():
+    """print_value should be accessible as pm.print_value."""
+    assert hasattr(pm, "print_value")