Remove unused diverse_tests

tests/diverse_tests.py

-"""
-  Different tests that are not connected to any particular Op, or
-  functionality of Aesara. Here will go for example code that we will
-  publish in papers, that we should ensure that it will remain
-  operational
-
-"""
-import numpy as np
-import numpy.random
-
-from aesara import config, function, shared
-from aesara.gradient import grad
-from aesara.tensor.math import dot, exp, log
-from aesara.tensor.type import matrix, vector
-from tests import unittest_tools as utt
-
-
-class TestScipy:
-    def test_scipy_paper_example1(self):
-        a = vector("a")  # declare variable
-        b = a + a**10  # build expression
-        f = function([a], b)  # compile function
-        assert np.all(f([0, 1, 2]) == np.array([0, 2, 1026]))
-
-    @config.change_flags(floatX="float64")
-    def test_scipy_paper_example2(self):
-        """This just sees if things compile well and if they run"""
-        rng = numpy.random.default_rng(utt.fetch_seed())
-
-        x = matrix()
-        y = vector()
-        w = shared(rng.standard_normal((100)))
-        b = shared(np.zeros(()))
-
-        # Construct Aesara expression graph
-        p_1 = 1 / (1 + exp(-dot(x, w) - b))
-        xent = -y * log(p_1) - (1 - y) * log(1 - p_1)
-        prediction = p_1 > 0.5
-        cost = xent.mean() + 0.01 * (w**2).sum()
-        gw, gb = grad(cost, [w, b])
-
-        # Compile expressions to functions
-        train = function(
-            inputs=[x, y],
-            outputs=[prediction, xent],
-            updates=[(w, w - 0.1 * gw), (b, b - 0.1 * gb)],
-        )
-        function(inputs=[x], outputs=prediction)
-
-        N = 4
-        feats = 100
-        D = (rng.standard_normal((N, feats)), rng.integers(size=4, low=0, high=2))
-        training_steps = 10
-        for i in range(training_steps):
-            pred, err = train(D[0], D[1])