BUG: `model_to_graphviz` fails with `Flat` variables

Describe the issue:

The call to pm.model_to_graphviz or model.to_graphviz fails if the model contains a pm.Flat variable. According to the error message, it tries to sample from the flat variable.

Reproduceable code example:

import numpy as np
import pandas as pd
import pymc as pm

RANDOM_SEED = 8927
rng = np.random.default_rng(RANDOM_SEED)

size = 200
true_intercept = 1
true_slope = 2

x = np.linspace(0, 1, size)
true_regression_line = true_intercept + true_slope * x
y = true_regression_line + rng.normal(scale=0.5, size=size)

data = pd.DataFrame({"x": x, "y": y})

with pm.Model() as model:
    intercept = pm.Flat("intercept") # <--- Flat prior here causes model.to_graphviz() to fail
    sigma = pm.HalfCauchy("sigma", beta=10)
    slope = pm.Normal("slope", 0, sigma=20)
    likelihood = pm.Normal("y", mu=intercept + slope * x, sigma=sigma, observed=y)
    idata = pm.sample(3000)

pm.model_to_graphviz(model)

Error message:

Traceback (most recent call last):
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/link/utils.py", line 197, in streamline_default_f
    thunk()
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/graph/op.py", line 545, in rval
    r = p(n, [x[0] for x in i], o)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/tensor/random/op.py", line 430, in perform
    self.rng_fn(rng, *args, None if size is None else tuple(size)),
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/distributions/continuous.py", line 357, in rng_fn
    raise NotImplementedError("Cannot sample from flat variable")
NotImplementedError: Cannot sample from flat variable

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/rebane/dev/salk/turnout-model/model_test/tmp.py", line 25, in <module>
    pm.model_to_graphviz(model)
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/model_graph.py", line 763, in model_to_graphviz
    plates=graph.get_plates(var_names=var_names),
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/model_graph.py", line 349, in get_plates
    var_name: tuple(map(int, fast_eval(self.model[var_name].shape)))
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/model_graph.py", line 77, in fast_eval
    return function([], var, mode=_cheap_eval_mode)()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/compile/function/types.py", line 1038, in __call__
    outputs = vm() if output_subset is None else vm(output_subset=output_subset)
              ^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/link/utils.py", line 201, in streamline_default_f
    raise_with_op(fgraph, node, thunk)
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/link/utils.py", line 526, in raise_with_op
    raise exc_value.with_traceback(exc_trace)
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/link/utils.py", line 197, in streamline_default_f
    thunk()
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/graph/op.py", line 545, in rval
    r = p(n, [x[0] for x in i], o)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pytensor/tensor/random/op.py", line 430, in perform
    self.rng_fn(rng, *args, None if size is None else tuple(size)),
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/distributions/continuous.py", line 357, in rng_fn
    raise NotImplementedError("Cannot sample from flat variable")
NotImplementedError: Cannot sample from flat variable
Apply node that caused the error: flat_rv{"->()"}(RNG(<Generator(PCG64) at 0x13B388900>), NoneConst{None})
Toposort index: 0
Inputs types: [RandomGeneratorType, <pytensor.tensor.type_other.NoneTypeT object at 0x1105da480>]
Inputs shapes: ['No shapes', 'No shapes']
Inputs strides: ['No strides', 'No strides']
Inputs values: [Generator(PCG64) at 0x13B388900, None]
Outputs clients: [[], [Shape(intercept)]]

Backtrace when the node is created (use PyTensor flag traceback__limit=N to make it longer):
  File "/Users/rebane/dev/salk/turnout-model/model_test/tmp.py", line 19, in <module>
    intercept = pm.Flat("intercept") # <--- Flat prior here causes model.to_graphviz() to fail
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/distributions/distribution.py", line 529, in __new__
    rv_out = cls.dist(*args, **kwargs)
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/distributions/continuous.py", line 370, in dist
    res = super().dist([], **kwargs)
  File "/Users/rebane/miniconda3/envs/test/lib/python3.12/site-packages/pymc/distributions/distribution.py", line 598, in dist
    return 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.

PyMC version information:

• PyMC: 5.27.0
• PyTensor: 2.36.1
• Python: 3.12.0
• Operating system: macOS Sequoia 15.6.1
• How did you install PyMC: pip

Context for the issue:

Visualizing the model fails. Does not block my work.

Start in pymc/model_graph.py, especially model_to_graphviz, get_plates, and fast_eval, and reproduce the failure with the Flat-variable example from the issue. Trace why evaluating the variable shape attempts to sample from Flat, then add coverage for this model graph case. Done means model_to_graphviz and model.to_graphviz render models containing pm.Flat without raising NotImplementedError.