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examples/causal_inference/regression_discontinuity.ipynb
This could be something with Windows
───────────────────────────────────── Error running examples/causal_inference/regression_discontinuity.ipynb ───────────────────────────────────── --------------------------------------------------------------------------- Exception encountered at "In [10]": --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/link/basic.py:102, in Container.__set__(self, value) 100 try: 101 # Use in-place filtering when/if possible --> 102 self.storage[0] = self.type.filter_inplace( 103 value, self.storage[0], **kwargs 104 ) 105 except NotImplementedError: File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/graph/type.py:128, in Type.filter_inplace(self, value, storage, strict, allow_downcast) 109 """Return data or an appropriately wrapped/converted data by converting it in-place. 110 111 This method allows one to reuse old allocated memory. If this method (...) 126 NotImplementedError 127 """ --> 128 raise NotImplementedError() NotImplementedError: During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) Cell In[10], line 8 6 # posterior prediction (see technical note above) 7 with model: ----> 8 pm.set_data({"x": _x, "treated": _treated}) 9 ppc = pm.sample_posterior_predictive(idata, var_names=["mu", "y"]) 11 # plotting File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pymc/model/core.py:2092, in set_data(new_data, model, coords) 2089 model = modelcontext(model) 2091 for variable_name, new_value in new_data.items(): -> 2092 model.set_data(variable_name, new_value, coords=coords) File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pymc/model/core.py:1161, in Model.set_data(self, name, values, coords) 1158 # store it as tuple for immutability as in add_coord 1159 self._coords = tuple(new_coords) -> 1161 shared_object.set_value(values) File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/compile/sharedvalue.py:134, in SharedVariable.set_value(self, new_value, borrow) 132 self.container.value = new_value 133 else: --> 134 self.container.value = copy.deepcopy(new_value) File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/link/basic.py:106, in Container.__set__(self, value) 102 self.storage[0] = self.type.filter_inplace( 103 value, self.storage[0], **kwargs 104 ) 105 except NotImplementedError: --> 106 self.storage[0] = self.type.filter(value, **kwargs) 108 except Exception as e: 109 e.args = (*e.args, f'Container name "{self.name}"') File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/tensor/type.py:204, in TensorType.filter(self, data, strict, allow_downcast) 195 if up_dtype != self.dtype: 196 err_msg = ( 197 f"{self} cannot store a value of dtype {data.dtype} without " 198 "risking loss of precision. If you do not mind " (...) 202 f'"function". Value: "{data!r}"' 203 ) --> 204 raise TypeError(err_msg) 205 elif ( 206 allow_downcast is None 207 and isinstance(data, float | np.floating) (...) 210 # Special case where we allow downcasting of Python float 211 # literals to floatX, even when floatX=='float32' 212 data = _asarray(data, self.dtype) TypeError: ('Vector(bool, shape=(?,)) cannot store a value of dtype float64 without risking loss of precision. If you do not mind this loss, you can: 1) explicitly cast your data to bool, or 2) set "allow_input_downcast=True" when calling "function". 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This could be something with Windows
The text was updated successfully, but these errors were encountered: