@opherdonchin I opened a PR to keep the stack trace to the original variables, this shows exactly which line of code created the faulty RV: Keep stack trace in random_make_inplace by ricardoV94 · Pull Request #735 · pymc-devs/pytensor · GitHub
The full trackeback is now more verbose, and looks like this:
Traceback (most recent call last):
File "/home/ricardo/Documents/Projects/pytensor/pytensor/compile/function/types.py", line 970, in __call__
self.vm()
File "/home/ricardo/Documents/Projects/pytensor/pytensor/graph/op.py", line 524, in rval
r = p(n, [x[0] for x in i], o)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/op.py", line 330, in perform
smpl_val = self.rng_fn(rng, *([*args, size]))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/basic.py", line 58, in rng_fn
res = cls.rng_fn_scipy(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/basic.py", line 375, in rng_fn_scipy
return stats.halfnorm.rvs(loc, scale, random_state=rng, size=size)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/scipy/stats/_distn_infrastructure.py", line 1057, in rvs
raise ValueError(message)
ValueError: Domain error in arguments. The `scale` parameter must be positive for all distributions, and many distributions have restrictions on shape parameters. Please see the `scipy.stats.halfnorm` documentation for details.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3577, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-9b04c63d3b82>", line 11, in <module>
idata = pm.sample_prior_predictive(samples=100)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pymc/pymc/sampling/forward.py", line 417, in sample_prior_predictive
values = zip(*(sampler_fn() for i in range(samples)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pymc/pymc/sampling/forward.py", line 417, in <genexpr>
values = zip(*(sampler_fn() for i in range(samples)))
^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/compile/function/types.py", line 983, in __call__
raise_with_op(
File "/home/ricardo/Documents/Projects/pytensor/pytensor/link/utils.py", line 528, in raise_with_op
raise exc_value.with_traceback(exc_trace)
File "/home/ricardo/Documents/Projects/pytensor/pytensor/compile/function/types.py", line 970, in __call__
self.vm()
File "/home/ricardo/Documents/Projects/pytensor/pytensor/graph/op.py", line 524, in rval
r = p(n, [x[0] for x in i], o)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/op.py", line 330, in perform
smpl_val = self.rng_fn(rng, *([*args, size]))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/basic.py", line 58, in rng_fn
res = cls.rng_fn_scipy(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/Documents/Projects/pytensor/pytensor/tensor/random/basic.py", line 375, in rng_fn_scipy
return stats.halfnorm.rvs(loc, scale, random_state=rng, size=size)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/scipy/stats/_distn_infrastructure.py", line 1057, in rvs
raise ValueError(message)
ValueError: Domain error in arguments. The `scale` parameter must be positive for all distributions, and many distributions have restrictions on shape parameters. Please see the `scipy.stats.halfnorm` documentation for details.
Apply node that caused the error: halfnormal_rv{0, (0, 0), floatX, True}(RandomGeneratorSharedVariable(<Generator(PCG64) at 0x7FD4400504A0>), [], 11, 0.0, -1)
Toposort index: 1
Inputs types: [RandomGeneratorType, TensorType(int64, shape=(0,)), TensorType(int64, shape=()), TensorType(float32, shape=()), TensorType(int8, shape=())]
Inputs shapes: ['No shapes', (0,), (), (), ()]
Inputs strides: ['No strides', (0,), (), (), ()]
Inputs values: [Generator(PCG64) at 0x7FD4400504A0, array([], dtype=int64), array(11), array(0., dtype=float32), array(-1, dtype=int8)]
Outputs clients: [['output'], ['output', normal_rv{0, (0, 0), floatX, True}(RandomGeneratorSharedVariable(<Generator(PCG64) at 0x7FD440052B20>), [30], 11, m, s)]]
Backtrace when the node is created (use PyTensor flag traceback__limit=N to make it longer):
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/IPython/core/async_helpers.py", line 129, in _pseudo_sync_runner
coro.send(None)
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3334, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3517, in run_ast_nodes
if await self.run_code(code, result, async_=asy):
File "/home/ricardo/miniconda3/envs/pymc/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3577, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-9b04c63d3b82>", line 7, in <module>
s = pm.HalfNormal('s', sigma=-1)
File "/home/ricardo/Documents/Projects/pymc/pymc/distributions/distribution.py", line 555, in __new__
rv_out = cls.dist(*args, **kwargs)
File "/home/ricardo/Documents/Projects/pymc/pymc/distributions/continuous.py", line 846, in dist
return super().dist([0.0, sigma], **kwargs)
File "/home/ricardo/Documents/Projects/pymc/pymc/distributions/distribution.py", line 635, in dist
rv_out = cls.rv_op(*dist_params, size=create_size, **kwargs)
HINT: Use the PyTensor flag `exception_verbosity=high` for a debug print-out and storage map footprint of this Apply node.
It shows it all starts from s = pm.HalfNormal('s', sigma=-1). I still find these very hard to read, but anyway the info will be there.