From afa78655b87d63a6e04d0376db976557586c3a80 Mon Sep 17 00:00:00 2001
From: Allen Goodman <allen.goodman@icloud.com>
Date: Tue, 2 Jul 2024 17:56:10 -0400
Subject: [PATCH] tests

---
 src/beignet/polynomial/__div.py    | 132 -----------------------------
 src/beignet/polynomial/__init__.py |   2 -
 2 files changed, 134 deletions(-)
 delete mode 100644 src/beignet/polynomial/__div.py

diff --git a/src/beignet/polynomial/__div.py b/src/beignet/polynomial/__div.py
deleted file mode 100644
index 5d09158328..0000000000
--- a/src/beignet/polynomial/__div.py
+++ /dev/null
@@ -1,132 +0,0 @@
-from typing import Callable, Tuple
-
-import torch
-from torch import Tensor
-
-
-def _div(
-    func: Callable,
-    input: Tensor,
-    other: Tensor,
-) -> Tuple[Tensor, Tensor]:
-    input = torch.atleast_1d(input)
-    other = torch.atleast_1d(other)
-
-    dtype = torch.promote_types(input.dtype, other.dtype)
-
-    input = input.to(dtype)
-    other = other.to(dtype)
-
-    m = input.shape[0]
-    n = other.shape[0]
-
-    if m < n:
-        return torch.zeros_like(input[:1]), input
-
-    if n == 1:
-        return input / other[-1], torch.zeros_like(input[:1])
-
-    def f(x: Tensor) -> Tensor:
-        indicies = torch.flip(x, [0])
-
-        indicies = torch.nonzero(indicies, as_tuple=False)
-
-        if indicies.shape[0] > 1:
-            indicies = indicies[:1]
-
-        if indicies.shape[0] < 1:
-            indicies = torch.concatenate(
-                [
-                    indicies,
-                    torch.full(
-                        [
-                            1 - indicies.shape[0],
-                            indicies.shape[1],
-                        ],
-                        0,
-                    ),
-                ],
-                0,
-            )
-
-        return x.shape[0] - 1 - indicies[0][0]
-
-    quotient = torch.zeros(m - n + 1, dtype=input.dtype)
-
-    ridx = input.shape[0] - 1
-
-    size = m - f(other) - 1
-
-    y = torch.zeros(m + n + 1, dtype=input.dtype)
-
-    y[size] = 1.0
-
-    x = quotient, input, y, ridx
-
-    for index in range(0, size):
-        quotient, remainder, y2, ridx1 = x
-
-        j = size - index
-
-        p = func(y2, other)
-
-        pidx = f(p)
-
-        t = remainder[ridx1] / p[pidx]
-
-        remainder_modified = remainder.clone()
-        remainder_modified[ridx1] = 0.0
-
-        a = remainder_modified
-
-        p_modified = p.clone()
-        p_modified[pidx] = 0.0
-
-        b = t * p_modified
-
-        a = torch.atleast_1d(a)
-        b = torch.atleast_1d(b)
-
-        dtype = torch.promote_types(a.dtype, b.dtype)
-
-        a = a.to(dtype)
-        b = b.to(dtype)
-
-        if a.shape[0] > b.shape[0]:
-            output = -b
-
-            output = torch.concatenate(
-                [
-                    output,
-                    torch.zeros(
-                        a.shape[0] - b.shape[0],
-                        dtype=b.dtype,
-                    ),
-                ],
-            )
-            output = a + output
-        else:
-            output = -b
-
-            output = torch.concatenate(
-                [
-                    output[: a.shape[0]] + a,
-                    output[a.shape[0] :],
-                ],
-            )
-
-        remainder = output
-
-        remainder = remainder[: remainder.shape[0]]
-
-        quotient[j] = t
-
-        ridx1 = ridx1 - 1
-
-        y2 = torch.roll(y2, -1)
-
-        x = quotient, remainder, y2, ridx1
-
-    quotient, remainder, _, _ = x
-
-    return quotient, remainder
diff --git a/src/beignet/polynomial/__init__.py b/src/beignet/polynomial/__init__.py
index 3f043ea610..58325d04d5 100644
--- a/src/beignet/polynomial/__init__.py
+++ b/src/beignet/polynomial/__init__.py
@@ -7,7 +7,6 @@
 
 import torch.linalg
 
-from .__div import _div
 from .__fit import _fit
 from .__from_roots import _from_roots
 from .__normed_hermite_e_n import _normed_hermite_e_n
@@ -277,7 +276,6 @@
 torch.set_default_dtype(torch.float64)
 
 __all__ = [
-    "_div",
     "_fit",
     "_from_roots",
     "_normed_hermite_e_n",