Summarize model as rich table

[ricardoV94]

From pymc-devs/pymc#7210 (comment)

import numpy as np
import pymc as pm

from pymc_experimental.printing import model_table

coords = {"subject": range(20), "param": ["a", "b"]}
with pm.Model(coords=coords) as m:
    x = pm.Data("x", np.random.normal(size=(20, 2)), dims=("subject", "param"))
    y = pm.Data("y", np.random.normal(size=(20,)), dims="subject")

    beta = pm.Normal("beta", mu=0, sigma=1, dims="param")
    mu = pm.Deterministic("mu", pm.math.dot(x, beta), dims="subject")
    sigma = pm.HalfNormal("sigma", sigma=1)

    y_obs = pm.Normal("y_obs", mu=mu, sigma=sigma, observed=y, dims="subject")

model_table(m)

 Variable  Expression         Dimensions             
─────────────────────────────────────────────────────
      x =  Data               subject[20] × param[2] 
      y =  Data               subject[20]            
                                                     
   beta ~  Normal(0, 1)       param[2]               
  sigma ~  HalfNormal(0, 1)                          
                              Parameter count = 3    
                                                     
     mu =  f(beta)            subject[20]            
                                                     
  y_obs ~  Normal(mu, sigma)  subject[20]     

[ricardoV94]

The output will be automatically improved once these issues are solved:

1. Textual representation of the model does not show Data variables or dependency on them pymc#7536
2. Richer textual representation of parameter relationships pymc#7538