rename model as as_model

Author: theorashid

docs/api_reference.rst

@@ -8,7 +8,7 @@ methods in the current release of PyMC experimental.
 .. autosummary::
    :toctree: generated/
 
-   model
+   as_model
    MarginalModel
    model_builder.ModelBuilder
 

pymc_experimental/__init__.py

@@ -26,4 +26,4 @@
 from pymc_experimental import distributions, gp, utils
 from pymc_experimental.inference.fit import fit
 from pymc_experimental.model.marginal_model import MarginalModel
-from pymc_experimental.model.model_api import model
+from pymc_experimental.model.model_api import as_model

pymc_experimental/model/model_api.py

@@ -3,7 +3,7 @@
 import pymc as pm
 
 
-def model(*model_args, **model_kwargs):
+def as_model(*model_args, **model_kwargs):
     R"""
     Decorator to provide context to PyMC models declared in a function.
     This removes all need to think about context managers and lets you separate creating a generative model from using the model.
@@ -25,7 +25,7 @@ def model(*model_args, **model_kwargs):
             pm.sample()
 
         # functional API using decorator
-        @pmx.model(coords={"obs": ["a", "b"]})
+        @pmx.as_model(coords={"obs": ["a", "b"]})
         def basic_model():
             pm.Normal("x", 0., 1., dims="obs")
 

pymc_experimental/tests/model/test_model_api.py

@@ -13,7 +13,7 @@ def test_logp():
     with pm.Model(coords=coords) as model:
         pm.Normal("x", 0.0, 1.0, dims="obs")
 
-    @pmx.model(coords=coords)
+    @pmx.as_model(coords=coords)
     def model_wrapped():
         pm.Normal("x", 0.0, 1.0, dims="obs")