# PyMC 4 & Aesara Cannot convert Elemwise{pow,no\_inplace}.0 to a tensor variable

**URL:** <https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436>\
**Category:** v5\
**Tags:** modeling, aesara\
**Created:** [February 18, 2023, 1:21pm UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436 "2023-02-18T13:21:39Z")\
**Posts on this page:** 6\
**Page:** 1

<div class="post-metadata">

**Author:** ![Domonitor](https://avatars.discourse-cdn.com/v4/letter/d/e99b99/32.png) [@Domonitor](https://discourse.pymc.io/u/Domonitor)\
**Post date:** [February 18, 2023, 1:21pm UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/1 "2023-02-18T13:21:39Z")

</div>

Hi Everyone. I’ve been struggling for a few days trying to migrate a script that previously ran on PyMC3 + Theano to a version that works with PyMC4 + Aesara - hoping to take advantage of GPU acceleration.

The snippet below isolates my current issue

```auto
import numpy as np
import aesara.tensor as at
import pymc as pm
from pymc import Beta

def geometric_adstock_at(x, alpha=0,L=30, normalize=True):
    w = at.power(alpha, np.arange(L))
    xx = at.stack([at.concatenate([at.zeros(i), x[:x.shape[0]-i]]) for i in range(L)])
    
    if not normalize:
        y = at.dot(w,xx)
    else:
        y = at.dot(w/at.sum(w),xx)
    return y

x_test = np.ones(100)*10000

with pm.Model() as test_model:
    alpha_test = Beta('alpha_test',3,3)
    geometric_adstock_at(x_test, alpha=alpha_test)

```

This results in

```auto
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[1], line 21
     19 with pm.Model() as test_model:
     20 alpha_test = Beta('alpha_test',3,3)
---> 21 geometric_adstock_at(x_test, alpha=alpha_test)

Cell In[1], line 13, in geometric_adstock_at(x, alpha, L, normalize)
     11 y = at.dot(w,xx)
     12 else:
---> 13 y = at.dot(w/at.sum(w),xx)
     14 return y

File ~/SageMaker/custom_39_venv/lib/python3.9/site-packages/aesara/tensor/math.py:2507, in sum(input, axis, dtype, keepdims, acc_dtype)
   2487 def sum(input, axis=None, dtype=None, keepdims=False, acc_dtype=None):
   2488 """
   2489 Computes the sum along the given axis(es) of a tensor `input`.
   2490 
   (...)
   2504 
   2505 """
-> 2507 out = Sum(axis=axis, dtype=dtype, acc_dtype=acc_dtype)(input)
   2509 if keepdims:
   2510 out = makeKeepDims(input, out, axis)

File ~/SageMaker/custom_39_venv/lib/python3.9/site-packages/aesara/graph/op.py:297, in Op. __call__ (self, *inputs, **kwargs)
    255 r"""Construct an `Apply` node using :meth:`Op.make_node` and return its outputs.
    256 
    257 This method is just a wrapper around :meth:`Op.make_node`.
   (...)
    294 
    295 """
    296 return_list = kwargs.pop("return_list", False)
--> 297 node = self.make_node(*inputs, **kwargs)
    299 if config.compute_test_value != "off":
    300 compute_test_value(node)

File ~/SageMaker/custom_39_venv/lib/python3.9/site-packages/aesara/tensor/elemwise.py:1413, in CAReduce.make_node(self, input)
   1412 def make_node(self, input):
-> 1413 input = as_tensor_variable(input)
   1414 inp_dims = input.type.ndim
   1415 inp_dtype = input.type.dtype

File ~/SageMaker/custom_39_venv/lib/python3.9/site-packages/aesara/tensor/ __init__.py:49, in as_tensor_variable(x, name, ndim, **kwargs)
     17 def as_tensor_variable(
     18 x: TensorLike, name: Optional[str] = None, ndim: Optional[int] = None, **kwargs
     19 ) -> "TensorVariable":
     20 """Convert `x` into an equivalent `TensorVariable`.
     21 
     22 This function can be used to turn ndarrays, numbers, `ScalarType` instances,
   (...)
     47 
     48 """
---> 49 return _as_tensor_variable(x, name, ndim, **kwargs)

File ~/anaconda3/envs/custom_39_pymc/lib/python3.9/functools.py:888, in singledispatch.<locals>.wrapper(*args, **kw)
    884 if not args:
    885 raise TypeError(f'{funcname} requires at least '
    886 '1 positional argument')
--> 888 return dispatch(args[0]. __class__ )(*args, **kw)

File ~/SageMaker/custom_39_venv/lib/python3.9/site-packages/aesara/tensor/ __init__.py:56, in _as_tensor_variable(x, name, ndim, **kwargs)
     52 @singledispatch
     53 def _as_tensor_variable(
     54 x: TensorLike, name: Optional[str], ndim: Optional[int], **kwargs
     55 ) -> "TensorVariable":
---> 56 raise NotImplementedError(f"Cannot convert {x!r} to a tensor variable.")

NotImplementedError: Cannot convert Elemwise{pow,no_inplace}.0 to a tensor variable.

```

Previously (in-line with what worked in my PyMC3 model), I used

```auto
w = at.as_tensor_variable([at.power(alpha,i) for i in range(L)])

```

instead of

```auto
w = at.power(alpha, np.arange(L))

```

But that also spat out errors that I’m unable to resolve.

Any suggestions or advice are greatly appreciated.

PyMC version: 5.0.2  
Aesara version: 2.8.10  
NumPy version: 1.24.2

Running on Python 3.9.16 on a AWS SageMaker Notebook instance

---

<div class="post-metadata">

**Author:** ![ricardoV94](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/ricardov94/32/5775_2.png) [@ricardoV94](https://discourse.pymc.io/u/ricardoV94)\
**Post date:** [February 18, 2023, 2:20pm UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/2 "2023-02-18T14:20:22Z")

</div>

With PyMC 5 you have to use PyTensor and not Aesara.

Just replace `import aesara.tensor` by `import pytensor.tensor`.

---

<div class="post-metadata">

**Author:** ![Ansul](https://avatars.discourse-cdn.com/v4/letter/a/6bbea6/32.png) [@Ansul](https://discourse.pymc.io/u/Ansul)\
**Post date:** [June 15, 2023, 11:22am UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/3 "2023-06-15T11:22:05Z")

</div>

Hi,  
With pymc3, I have tried with aesara as well as pytensor but getting the error -

```auto
import aesara.tensor as at
def geometric_adstock_at(x, alpha=0,L=12, normalize=True):
    w = at.power(alpha, np.arange(L))
    xx = at.stack([at.concatenate([at.zeros(i), x[:x.shape[0]-i]]) for i in range(L)])
    
    if not normalize:
        y = at.dot(w,xx)
    else:
        y = at.dot(w/at.sum(w),xx)
    return y

x_test = np.ones(100)*10000

with pm.Model() as test_model:
    alpha_test = Beta('alpha_test',3,3)
    geometric_adstock_at(x_test, alpha=alpha_test)

```

Error -

```auto
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
/tmp/ipykernel_1364/803033312.py in <module>
     14 with pm.Model() as test_model:
     15 alpha_test = Beta('alpha_test',3,3)
---> 16 geometric_adstock_at(x_test, alpha=alpha_test)

/tmp/ipykernel_1364/803033312.py in geometric_adstock_at(x, alpha, L, normalize)
      7 y = at.dot(w,xx)
      8 else:
----> 9 y = at.dot(w/at.sum(w),xx)
     10 return y
     11 

~/.local/lib/python3.8/site-packages/aesara/tensor/math.py in sum(input, axis, dtype, keepdims, acc_dtype)
   2509 """
   2510 
-> 2511 out = Sum(axis=axis, dtype=dtype, acc_dtype=acc_dtype)(input)
   2512 
   2513 if keepdims:

~/.local/lib/python3.8/site-packages/aesara/graph/op.py in __call__ (self, *inputs, **kwargs)
    293 """
    294 return_list = kwargs.pop("return_list", False)
--> 295 node = self.make_node(*inputs, **kwargs)
    296 
    297 if config.compute_test_value != "off":

~/.local/lib/python3.8/site-packages/aesara/tensor/elemwise.py in make_node(self, input)
   1406 
   1407 def make_node(self, input):
-> 1408 input = as_tensor_variable(input)
   1409 inp_dims = input.type.ndim
   1410 inp_dtype = input.type.dtype

~/.local/lib/python3.8/site-packages/aesara/tensor/ __init__.py in as_tensor_variable(x, name, ndim, **kwargs)
     47 
     48 """
---> 49 return _as_tensor_variable(x, name, ndim, **kwargs)
     50 
     51 

/opt/conda/lib/python3.8/functools.py in wrapper(*args, **kw)
    873 '1 positional argument')
    874 
--> 875 return dispatch(args[0]. __class__ )(*args, **kw)
    876 
    877 funcname = getattr(func, ' __name__', 'singledispatch function')

~/.local/lib/python3.8/site-packages/aesara/tensor/ __init__.py in _as_tensor_variable(x, name, ndim, **kwargs)
     54 x: TensorLike, name: Optional[str], ndim: Optional[int], **kwargs
     55 ) -> "TensorVariable":
---> 56 raise NotImplementedError(f"Cannot convert {x!r} to a tensor variable.")
     57 
     58 

NotImplementedError: Cannot convert Elemwise{pow,no_inplace}.0 to a tensor variable.

```

And when I am using pytensor, I get the same error -

```auto
import pytensor.tensor as pt
def geometric_adstock_pt(x, alpha=0,L=12, normalize=True):
    w = pt.power(alpha, np.arange(L))
    xx = pt.stack([pt.concatenate([pt.zeros(i), x[:x.shape[0]-i]]) for i in range(L)])
    
    if not normalize:
        y = pt.dot(w,xx)
    else:
        y = pt.dot(w/at.sum(w),xx)
    return y

x_test = np.ones(100)*10000

with pm.Model() as test_model:
    alpha_test = Beta('alpha_test',3,3)
    geometric_adstock_pt(x_test, alpha=alpha_test)

```

Error -

```auto
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
/tmp/ipykernel_1364/2970462427.py in <module>
     14 with pm.Model() as test_model:
     15 alpha_test = Beta('alpha_test',3,3)
---> 16 geometric_adstock_pt(x_test, alpha=alpha_test)

/tmp/ipykernel_1364/2970462427.py in geometric_adstock_pt(x, alpha, L, normalize)
      7 y = pt.dot(w,xx)
      8 else:
----> 9 y = pt.dot(w/at.sum(w),xx)
     10 return y
     11 

~/.local/lib/python3.8/site-packages/aesara/tensor/math.py in sum(input, axis, dtype, keepdims, acc_dtype)
   2509 """
   2510 
-> 2511 out = Sum(axis=axis, dtype=dtype, acc_dtype=acc_dtype)(input)
   2512 
   2513 if keepdims:

~/.local/lib/python3.8/site-packages/aesara/graph/op.py in __call__ (self, *inputs, **kwargs)
    293 """
    294 return_list = kwargs.pop("return_list", False)
--> 295 node = self.make_node(*inputs, **kwargs)
    296 
    297 if config.compute_test_value != "off":

~/.local/lib/python3.8/site-packages/aesara/tensor/elemwise.py in make_node(self, input)
   1406 
   1407 def make_node(self, input):
-> 1408 input = as_tensor_variable(input)
   1409 inp_dims = input.type.ndim
   1410 inp_dtype = input.type.dtype

~/.local/lib/python3.8/site-packages/aesara/tensor/ __init__.py in as_tensor_variable(x, name, ndim, **kwargs)
     47 
     48 """
---> 49 return _as_tensor_variable(x, name, ndim, **kwargs)
     50 
     51 

/opt/conda/lib/python3.8/functools.py in wrapper(*args, **kw)
    873 '1 positional argument')
    874 
--> 875 return dispatch(args[0]. __class__ )(*args, **kw)
    876 
    877 funcname = getattr(func, ' __name__', 'singledispatch function')

~/.local/lib/python3.8/site-packages/aesara/tensor/ __init__.py in _as_tensor_variable(x, name, ndim, **kwargs)
     54 x: TensorLike, name: Optional[str], ndim: Optional[int], **kwargs
     55 ) -> "TensorVariable":
---> 56 raise NotImplementedError(f"Cannot convert {x!r} to a tensor variable.")
     57 
     58 

NotImplementedError: Cannot convert Elemwise{pow,no_inplace}.0 to a tensor variable.

```

Any help would be greatly appreciated!

PyMC3 version: 3.11.5  
Aesara version: 2.9.0  
NumPy version: 1.20.3  
Pytensor version : 2.12.2

---

<div class="post-metadata">

**Author:** ![ricardoV94](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/ricardov94/32/5775_2.png) [@ricardoV94](https://discourse.pymc.io/u/ricardoV94)\
**Post date:** [June 15, 2023, 11:25am UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/4 "2023-06-15T11:25:56Z")

</div>

You can’t mix Aesara and PyMC3.

PyMC3 uses theano-pymc  
PYMC v4 uses aesara  
PyMC v5 uses pytensor

---

<div class="post-metadata">

**Author:** ![ricardoV94](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/ricardov94/32/5775_2.png) [@ricardoV94](https://discourse.pymc.io/u/ricardoV94)\
**Post date:** [June 15, 2023, 11:27am UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/5 "2023-06-15T11:27:44Z")

</div>

Also worth noting that if you are looking into building MMM models in PyMC, there’s a package for that now: [PyMC Marketing — pymc-marketing 0.1.1 documentation](https://www.pymc-marketing.io/en/stable/)

---

<div class="post-metadata">

**Author:** ![Ansul](https://avatars.discourse-cdn.com/v4/letter/a/6bbea6/32.png) [@Ansul](https://discourse.pymc.io/u/Ansul)\
**Post date:** [June 15, 2023, 11:43am UTC](https://discourse.pymc.io/t/pymc-4-aesara-cannot-convert-elemwise-pow-no-inplace-0-to-a-tensor-variable/11436/6 "2023-06-15T11:43:32Z")

</div>

Thanks @ricardoV94 for the prompt response. I have changed the code to use theano-pymc and it does not throw any error. How do I get the value from the geometric\_adstock\_tt function described below. It returns dot.0 value. I need the output of geometric\_adstock\_tt function to create a pandas column

```auto
import theano.tensor as tt
def geometric_adstock_tt(x, alpha=0,L=12, normalize=True):
    w = tt.power(alpha, np.arange(L))
    xx = tt.stack([tt.concatenate([tt.zeros(i), x[:x.shape[0]-i]]) for i in range(L)])
    
    if not normalize:
        y = tt.dot(w,xx)
    else:
        y = tt.dot(w/tt.sum(w),xx)
    return y

x_test = np.ones(100)*10000

with pm.Model() as test_model:
    alpha_test = Beta('alpha_test',3,3)
    print(geometric_adstock_tt(x_test, alpha=alpha_test))
dot.0

```