.temporarily work with already released versions of PyTensor

Author: ricardoV94

conda-envs/environment-alternative-backends.yml

@@ -22,7 +22,7 @@ dependencies:
 - numpyro>=0.8.0
 - pandas>=0.24.0
 - pip
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - networkx
 - rich>=13.7.1

conda-envs/environment-dev.yml

@@ -12,7 +12,7 @@ dependencies:
 - numpy>=1.25.0
 - pandas>=0.24.0
 - pip
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - networkx
 - scipy>=1.4.1

conda-envs/environment-docs.yml

@@ -11,7 +11,7 @@ dependencies:
 - numpy>=1.25.0
 - pandas>=0.24.0
 - pip
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - rich>=13.7.1
 - scipy>=1.4.1

conda-envs/environment-test.yml

@@ -14,7 +14,7 @@ dependencies:
 - pandas>=0.24.0
 - pip
 - polyagamma
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - networkx
 - rich>=13.7.1

conda-envs/windows-environment-dev.yml

@@ -12,7 +12,7 @@ dependencies:
 - numpy>=1.25.0
 - pandas>=0.24.0
 - pip
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - networkx
 - rich>=13.7.1

conda-envs/windows-environment-test.yml

@@ -15,7 +15,7 @@ dependencies:
 - pandas>=0.24.0
 - pip
 - polyagamma
-- pytensor>=2.31.6,<2.32
+- pytensor>=2.31.5,<2.32
 - python-graphviz
 - networkx
 - rich>=13.7.1

pymc/dims/distributions/scalar.py

@@ -40,15 +40,15 @@ def _get_sigma_from_either_sigma_or_tau(*, sigma, tau):
 
 
 class Flat(DimDistribution):
-    xrv_op = pxr.as_xrv(flat)
+    xrv_op = pxr._as_xrv(flat)
 
     @classmethod
     def dist(cls, **kwargs):
         return super().dist([], **kwargs)
 
 
 class HalfFlat(PositiveDimDistribution):
-    xrv_op = pxr.as_xrv(halfflat, [], ())
+    xrv_op = pxr._as_xrv(halfflat, [], ())
 
     @classmethod
     def dist(cls, **kwargs):
@@ -102,7 +102,7 @@ def xrv_op(self, nu, sigma, core_dims=None, extra_dims=None, rng=None):
         nu = as_xtensor(nu)
         sigma = as_xtensor(sigma)
         core_rv = HalfStudentTRV.rv_op(nu=nu.values, sigma=sigma.values).owner.op
-        xop = pxr.as_xrv(core_rv)
+        xop = pxr._as_xrv(core_rv)
         return xop(nu, sigma, core_dims=core_dims, extra_dims=extra_dims, rng=rng)
 
 

pymc/dims/distributions/vector.py

@@ -146,7 +146,7 @@ def xrv_op(self, sigma, support_dims, core_dims, extra_dims=None, rng=None):
         support_dims = as_xtensor(support_dims, dims=("_",))
         support_shape = support_dims.values
         core_rv = ZeroSumNormalRV.rv_op(sigma=sigma.values, support_shape=support_shape).owner.op
-        xop = pxr.as_xrv(
+        xop = pxr._as_xrv(
             core_rv,
             core_inps_dims_map=[(), (0,)],
             core_out_dims_map=tuple(range(1, len(core_dims) + 1)),

requirements-dev.txt

@@ -16,7 +16,7 @@ numpydoc
 pandas>=0.24.0
 polyagamma
 pre-commit>=2.8.0
-pytensor>=2.31.6,<2.32
+pytensor>=2.31.5,<2.32
 pytest-cov>=2.5
 pytest>=3.0
 rich>=13.7.1

requirements.txt

@@ -3,7 +3,7 @@ cachetools>=4.2.1
 cloudpickle
 numpy>=1.25.0
 pandas>=0.24.0
-pytensor>=2.31.6,<2.32
+pytensor>=2.31.5,<2.32
 rich>=13.7.1
 scipy>=1.4.1
 threadpoolctl>=3.1.0,<4.0.0