Rename aesara.tensor.random.opt to aesara.tensor.random.rewriting

aesara/tensor/random/__init__.py

-# Initialize `RandomVariable` optimizations
-import aesara.tensor.random.opt
+# Initialize `RandomVariable` rewrites
+import aesara.tensor.random.rewriting
 import aesara.tensor.random.utils
 from aesara.tensor.random.basic import *
 from aesara.tensor.random.op import RandomState, default_rng

tests/tensor/random/test_basic.py

@@ -60,8 +60,8 @@ from aesara.tensor.type import iscalar, scalar, tensor
 from tests.unittest_tools import create_aesara_param
 
 
-opts = RewriteDatabaseQuery(include=[None], exclude=["cxx_only", "BlasOpt"])
-py_mode = Mode("py", opts)
+rewrites_query = RewriteDatabaseQuery(include=[None], exclude=["cxx_only", "BlasOpt"])
+py_mode = Mode("py", rewrites_query)
 
 
 def fixed_scipy_rvs(rvs_name):

tests/tensor/random/test_opt.py → tests/tensor/random/test_rewriting.py

@@ -19,7 +19,7 @@ from aesara.tensor.random.basic import (
     uniform,
 )
 from aesara.tensor.random.op import RandomVariable
-from aesara.tensor.random.opt import (
+from aesara.tensor.random.rewriting import (
     local_dimshuffle_rv_lift,
     local_rv_size_lift,
     local_subtensor_rv_lift,
@@ -31,7 +31,9 @@ from aesara.tensor.type import iscalar, vector
 no_mode = Mode("py", RewriteDatabaseQuery(include=[], exclude=[]))
 
 
-def apply_local_opt_to_rv(opt, op_fn, dist_op, dist_params, size, rng, name=None):
+def apply_local_rewrite_to_rv(
+    rewrite, op_fn, dist_op, dist_params, size, rng, name=None
+):
     dist_params_at = []
     for p in dist_params:
         p_at = at.as_tensor(p).type()
@@ -50,20 +52,20 @@ def apply_local_opt_to_rv(opt, op_fn, dist_op, dist_params, size, rng, name=None
         p for p in dist_params_at + size_at if not isinstance(p, (slice, Constant))
     ]
 
-    mode = Mode("py", EquilibriumGraphRewriter([opt], max_use_ratio=100))
+    mode = Mode("py", EquilibriumGraphRewriter([rewrite], max_use_ratio=100))
 
-    f_opt = function(
+    f_rewritten = function(
         f_inputs,
         dist_st,
         mode=mode,
     )
 
-    (new_out,) = f_opt.maker.fgraph.outputs
+    (new_out,) = f_rewritten.maker.fgraph.outputs
 
-    return new_out, f_inputs, dist_st, f_opt
+    return new_out, f_inputs, dist_st, f_rewritten
 
 
-def test_inplace_optimization():
+def test_inplace_rewrites():
 
     out = normal(0, 1)
     out.owner.inputs[0].default_update = out.owner.outputs[0]
@@ -87,7 +89,7 @@ def test_inplace_optimization():
     assert np.array_equal(new_out.owner.inputs[1].data, [])
 
 
-def test_inplace_optimization_extra_props():
+def test_inplace_rewrites_extra_props():
     class Test(RandomVariable):
         name = "test"
         ndim_supp = 0
@@ -183,7 +185,7 @@ def test_inplace_optimization_extra_props():
 def test_local_rv_size_lift(dist_op, dist_params, size):
     rng = shared(np.random.default_rng(1233532), borrow=False)
 
-    new_out, f_inputs, dist_st, f_opt = apply_local_opt_to_rv(
+    new_out, f_inputs, dist_st, f_rewritten = apply_local_rewrite_to_rv(
         local_rv_size_lift,
         lambda rv: rv,
         dist_op,
@@ -349,7 +351,7 @@ def test_DimShuffle_lift(ds_order, lifted, dist_op, dist_params, size, rtol):
 
     rng = shared(np.random.default_rng(1233532), borrow=False)
 
-    new_out, f_inputs, dist_st, f_opt = apply_local_opt_to_rv(
+    new_out, f_inputs, dist_st, f_rewritten = apply_local_rewrite_to_rv(
         local_dimshuffle_rv_lift,
         lambda rv: rv.dimshuffle(ds_order),
         dist_op,
@@ -377,9 +379,9 @@ def test_DimShuffle_lift(ds_order, lifted, dist_op, dist_params, size, rtol):
 
     arg_values = [p.get_test_value() for p in f_inputs]
     res_base = f_base(*arg_values)
-    res_opt = f_opt(*arg_values)
+    res_rewritten = f_rewritten(*arg_values)
 
-    np.testing.assert_allclose(res_base, res_opt, rtol=rtol)
+    np.testing.assert_allclose(res_base, res_rewritten, rtol=rtol)
 
 
 @pytest.mark.parametrize(
@@ -472,7 +474,7 @@ def test_Subtensor_lift(indices, lifted, dist_op, dist_params, size):
             i_at.tag.test_value = i
         indices_at += (i_at,)
 
-    new_out, f_inputs, dist_st, f_opt = apply_local_opt_to_rv(
+    new_out, f_inputs, dist_st, f_rewritten = apply_local_rewrite_to_rv(
         local_subtensor_rv_lift,
         lambda rv: rv[indices_at],
         dist_op,
@@ -502,9 +504,9 @@ def test_Subtensor_lift(indices, lifted, dist_op, dist_params, size):
 
     arg_values = [p.get_test_value() for p in f_inputs]
     res_base = f_base(*arg_values)
-    res_opt = f_opt(*arg_values)
+    res_rewritten = f_rewritten(*arg_values)
 
-    np.testing.assert_allclose(res_base, res_opt, rtol=1e-3)
+    np.testing.assert_allclose(res_base, res_rewritten, rtol=1e-3)
 
 
 def test_Subtensor_lift_restrictions():
@@ -615,7 +617,7 @@ def test_Dimshuffle_lift_rename(ds_order, lifted, dist_op, dist_params, size, rt
 
     rng = shared(np.random.default_rng(1233532), borrow=False)
 
-    new_out, *_ = apply_local_opt_to_rv(
+    new_out, *_ = apply_local_rewrite_to_rv(
         local_dimshuffle_rv_lift,
         lambda rv: rv.dimshuffle(ds_order),
         dist_op,

tests/tensor/random/test_utils.py

@@ -11,8 +11,8 @@ from tests import unittest_tools as utt
 
 @pytest.fixture(scope="module", autouse=True)
 def set_aesara_flags():
-    opts = RewriteDatabaseQuery(include=[None], exclude=[])
-    py_mode = Mode("py", opts)
+    rewrites_query = RewriteDatabaseQuery(include=[None], exclude=[])
+    py_mode = Mode("py", rewrites_query)
     with config.change_flags(mode=py_mode, compute_test_value="warn"):
         yield