Aesara Error: Expected an array-like object, but found a Variable

Questions v5
1

Hi all,

I’m new to PyMC, so please excuse me if this is basic. I’ve been writing an Aesara function which calls another Aesara function. This is throwing an error and I havent found any answers in the docs or forms. Appreciate any help.

Here is a simplified version of the code:

x1 = at.dscalar(‘x’)
y1 = at.dscalar(‘y’)
z1 = x1 + y1
f1 = function([x1, y1], z1)

x2 = at.dscalar(‘x’)
y2 = at.dscalar(‘y’)
z2 = f1(x1, x2) + 5
f2 = function([x2, y2], z2)

When I compile I get this error:

TypeError Traceback (most recent call last)
Cell In [1469], line 9
7 x2 = at.dscalar(‘x’)
8 y2 = at.dscalar(‘y’)
----> 9 z2 = f1(x1, x2) + 5
10 f2 = function([x2, y2], z2)

File /opt/conda/lib/python3.10/site-packages/aesara/compile/function/types.py:859, in Function.call(self, *args, **kwargs)
857 else:
858 try:
→ 859 s.storage[0] = s.type.filter(
860 arg, strict=s.strict, allow_downcast=s.allow_downcast
861 )
863 except Exception as e:
864 function_name = “aesara function”

File /opt/conda/lib/python3.10/site-packages/aesara/tensor/type.py:139, in TensorType.filter(self, data, strict, allow_downcast)
136 # Explicit error message when one accidentally uses a Variable as
137 # input (typical mistake, especially with shared variables).
138 if isinstance(data, Variable):
→ 139 raise TypeError(
140 "Expected an array-like object, but found a Variable: "
141 "maybe you are trying to call a function on a (possibly "
142 “shared) variable instead of a numeric array?”
143 )
145 if isinstance(data, np.memmap) and (data.dtype == self.numpy_dtype):
146 # numpy.memmap is a “safe” subclass of ndarray,
147 # so we can use it wherever we expect a base ndarray.
148 # however, casting it would defeat the purpose of not
149 # loading the whole data into memory
150 pass

TypeError: Bad input argument with name “x” to aesara function with name “/tmp/ipykernel_92/1263410689.py:4” at index 0 (0-based).
Backtrace when that variable is created:

File “/opt/conda/lib/python3.10/site-packages/ipykernel/zmqshell.py”, line 528, in run_cell
return super().run_cell(*args, **kwargs)
File “/opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 2885, in run_cell
result = self._run_cell(
File “/opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 2940, in _run_cell
return runner(coro)
File “/opt/conda/lib/python3.10/site-packages/IPython/core/async_helpers.py”, line 129, in pseudo_sync_runner
coro.send(None)
File “/opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3139, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File “/opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3318, in run_ast_nodes
if await self.run_code(code, result, async=asy):
File “/opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py”, line 3378, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File “/tmp/ipykernel_92/1263410689.py”, line 1, in
x1 = at.dscalar(‘x’)
Expected an array-like object, but found a Variable: maybe you are trying to call a function on a (possibly shared) variable instead of a numeric array?
Blockquote

I see that it’s causing an issue when I pass the Variable rather than an array-like object, but I don’t know how to get around this.

Thanks in advance.

2

Once you compile the first function f1, the output (z2) will be a numpy array, not an Aesara tensor, so you can’t use that as an output of a compiled function (f2).

All you need to do is forego the first compile, wait until you’ve programmed all the computation you want do, then compile everything in one go:

    x1 = at.dscalar(‘x1’)
    y1 = at.dscalar(‘y1’)

    z1 = x1 + y1
    z2 = z1 + 5
    f2 = function([x1, y1], z2)

If you wanted f2 to return the intermediate computation z1, you could add that as an additional output of f2.

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