Delete python directory

python/tensor.py

@@ -1,61 +0,0 @@
-import ctypes
-
-class CTensor(ctypes.Structure):
-    _fields_ = [
-        ('data', ctypes.POINTER(ctypes.c_float)),
-        ('strides', ctypes.POINTER(ctypes.c_int)),
-        ('shape', ctypes.POINTER(ctypes.c_int)),
-        ('ndim', ctypes.c_int)
-    ]
-
-class Tensor:
-    def __init__(self, data):
-        data, shape = self.flatten(data)
-        print(data, shape)
-        self.lib = ctypes.CDLL("../build/libtensor.so")  # Adjust the path to the shared library
-        self.data = (ctypes.c_float * len(data))(*data)
-        self.shape = shape
-        self.ndim = len(shape)
-
-        self.lib.create_tensor.argtypes = [ctypes.POINTER(ctypes.c_float), ctypes.POINTER(ctypes.c_int), ctypes.c_int]
-        self.lib.create_tensor.restype = ctypes.POINTER(CTensor)
-
-        self.tensor = self.lib.create_tensor(
-            self.data,
-            (ctypes.c_int * len(shape))(*shape),
-            ctypes.c_int(len(shape))
-        )
-
-    def flatten(self, nested_list):
-        flat_data = []
-        shape = [len(nested_list), len(nested_list[0])]
-        for sublist in nested_list:
-            for item in sublist:
-                flat_data.append(item)
-        return flat_data, shape
-    
-    def __getitem__(self, indices):
-        if len(indices) != self.ndim:
-            raise ValueError("Number of indices must match the number of dimensions")
-        
-        self.lib.get_item.argtypes = [ctypes.POINTER(CTensor), ctypes.POINTER(ctypes.c_int)]
-        self.lib.get_item.restype = ctypes.c_float
-                                           
-        indices = (ctypes.c_int * len(indices))(*indices)
-        value = self.lib.get_item(self.tensor, indices)  
-
-        return value
-
-    def shape(self):
-        return f"Tensor(shape={self.shape})"
-
-    def __str__(self):
-        result = ""
-        for i in range(self.shape[0]):
-            for j in range(self.shape[1]):
-                result += str(self[i, j]) + " "
-            result += "\n"
-        return result.strip()
-
-    def __repr__(self):
-        return self.__str__()

python/tests.ipynb

@@ -1,98 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[0, 1, 2, 0, 2, 2] [2, 3, 3]\n",
-      "Tensor shape: [2, 3, 3]\n",
-      "Tensor created successfully\n",
-      "Tensor information:\n",
-      "Number of dimensions: 3\n",
-      "Shape: [2, 3, 3]\n",
-      "Data:\n",
-      "[0.00, 1.00, 2.00, 0.00, 2.00, 2.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00]\n"
-     ]
-    }
-   ],
-   "source": [
-    "from tensor import Tensor\n",
-    "\n",
-    "data = [[0, 1, 2], [0, 2, 2], [0, 1, 2]]\n",
-    "tensor = Tensor(data)\n",
-    "print(\"Tensor shape:\", tensor.shape)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Tensor created successfully\n",
-      "Tensor information:\n",
-      "Number of dimensions: 2\n",
-      "Shape: [3, 3]\n",
-      "Data:\n",
-      "[0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "0.10000000149011612 0.20000000298023224 0.30000001192092896 \n",
-       "0.4000000059604645 0.5 0.6000000238418579 \n",
-       "0.699999988079071 0.800000011920929 0.8999999761581421"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "data = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]\n",
-    "shape = [3, 3]\n",
-    "tensor = Tensor(data, shape)\n",
-    "tensor\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}