Fix obs broadcast mismatch

pymc3/aesaraf.py

@@ -156,6 +156,10 @@ def change_rv_size(
             size = rv_node.op._infer_shape(size, dist_params)
         new_size = tuple(np.atleast_1d(new_size)) + tuple(size)
 
+    # Make sure the new size is int64 so that it doesn't unnecessarily pick
+    # up a `Cast` in some cases
+    new_size = at.as_tensor(new_size, ndim=1, dtype="int64")
+
     new_rv_node = rv_node.op.make_node(rng, new_size, dtype, *dist_params)
     rv_var = new_rv_node.outputs[-1]
     rv_var.name = name

pymc3/model.py

@@ -1116,8 +1116,6 @@ def register_rv(self, rv_var, name, data=None, total_size=None, dims=None, trans
             ):
                 raise TypeError("Observed data cannot consist of symbolic variables.")
 
-            data = pandas_to_array(data)
-
             # `rv_var` is potentially a new variable (e.g. the original
             # variable could have its size changed to match the data, or be a
             # new graph that accounts for missing data)

pymc3/tests/test_aesaraf.py

@@ -23,7 +23,7 @@
 import pytest
 import scipy.sparse as sps
 
-from aesara.graph.basic import Variable, ancestors
+from aesara.graph.basic import Constant, Variable, ancestors
 from aesara.tensor.random.basic import normal, uniform
 from aesara.tensor.random.op import RandomVariable
 from aesara.tensor.subtensor import AdvancedIncSubtensor, AdvancedIncSubtensor1
@@ -67,6 +67,15 @@ def test_change_rv_size():
     assert rv_newer.ndim == 3
     assert rv_newer.eval().shape == (4, 3, 2)
 
+    # Make sure we avoid introducing a `Cast` by converting the new size before
+    # constructing the new `RandomVariable`
+    rv = normal(0, 1)
+    new_size = np.array([4, 3], dtype="int32")
+    rv_newer = change_rv_size(rv, new_size=new_size, expand=False)
+    assert rv_newer.ndim == 2
+    assert isinstance(rv_newer.owner.inputs[1], Constant)
+    assert rv_newer.eval().shape == (4, 3)
+
 
 class TestBroadcasting:
     def test_make_shared_replacements(self):

pymc3/tests/test_distributions_random.py

@@ -379,14 +379,10 @@ def check_rv_size(self):
         sizes_to_check = self.sizes_to_check or [None, (), 1, (1,), 5, (4, 5), (2, 4, 2)]
         sizes_expected = self.sizes_expected or [(), (), (1,), (1,), (5,), (4, 5), (2, 4, 2)]
         for size, expected in zip(sizes_to_check, sizes_expected):
-            actual = change_rv_size(self.pymc_rv, size).eval().shape
+            pymc_rv = self.pymc_dist.dist(**self.pymc_dist_params, size=size)
+            actual = tuple(pymc_rv.shape.eval())
             assert actual == expected, f"size={size}, expected={expected}, actual={actual}"
 
-        # test negative sizes raise
-        for size in [-2, (3, -2)]:
-            with pytest.raises(ValueError):
-                change_rv_size(self.pymc_rv, size).eval()
-
         # test multi-parameters sampling for univariate distributions (with univariate inputs)
         if self.pymc_dist.rv_op.ndim_supp == 0 and sum(self.pymc_dist.rv_op.ndims_params) == 0:
             params = {
@@ -400,7 +396,8 @@ def check_rv_size(self):
                 (5, self.repeated_params_shape),
             ]
             for size, expected in zip(sizes_to_check, sizes_expected):
-                actual = change_rv_size(self.pymc_rv, size).eval().shape
+                pymc_rv = self.pymc_dist.dist(**params, size=size)
+                actual = tuple(pymc_rv.shape.eval())
                 assert actual == expected
 
     def validate_tests_list(self):