Create and print a tensor

build/Makefile

@@ -0,0 +1,29 @@
+# Compiler
+CXX := g++
+
+# Compiler flags
+CXXFLAGS := -Wall -Werror -fpic
+
+# Source files
+SRCS := ../src/tensor.cpp
+
+# Object files
+OBJS := $(SRCS:.cpp=.o)
+
+# Target shared object file
+TARGET := libtensor.so
+
+# Default target
+all: $(TARGET)
+
+# Rule to build the shared object file
+$(TARGET): $(OBJS)
+	$(CXX) -shared -o $@ $^
+
+# Rule to compile each source file into an object file
+%.o: %.cpp
+	$(CXX) $(CXXFLAGS) -c $^ -o $@   # Use -o $@ to specify the output file
+
+# Clean rule
+clean:
+	$(RM) $(OBJS) $(TARGET)

python/tensor.py

@@ -0,0 +1,54 @@
+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, 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 __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 __del__(self):
+        self.lib.free_tensor(self.tensor)
+
+    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

@@ -0,0 +1,90 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "kkkk <tensor.c_int_Array_2 object at 0x7f990806fcc0> @@ c_int(2)\n",
+      "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"
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "Number of indices must match the number of dimensions",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 6\u001b[0m\n\u001b[1;32m      4\u001b[0m shape \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m3\u001b[39m]\n\u001b[1;32m      5\u001b[0m tensor \u001b[38;5;241m=\u001b[39m Tensor(data, shape)\n\u001b[0;32m----> 6\u001b[0m \u001b[43mTensor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__getitem__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtensor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Documentos/recreate_pytorch/foo/python/tensor.py:15\u001b[0m, in \u001b[0;36mTensor.__getitem__\u001b[0;34m(self, indices)\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, indices):\n\u001b[1;32m     14\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(indices) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim:\n\u001b[0;32m---> 15\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNumber of indices must match the number of dimensions\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     16\u001b[0m     indices \u001b[38;5;241m=\u001b[39m (ctypes\u001b[38;5;241m.\u001b[39mc_int \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mlen\u001b[39m(indices))(\u001b[38;5;241m*\u001b[39mindices)\n\u001b[1;32m     17\u001b[0m     value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlib\u001b[38;5;241m.\u001b[39mget_item(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtensor, indices)  \n",
+      "\u001b[0;31mValueError\u001b[0m: Number of indices must match the number of dimensions"
+     ]
+    }
+   ],
+   "source": [
+    "from tensor import Tensor\n",
+    "\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.shape\n",
+    "Tensor.__getitem__(tensor, [0, 0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-648269760\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tensor[1, 1])  # Accessing an element"
+   ]
+  },
+  {
+   "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
+}

src/tensor.cpp

@@ -0,0 +1,67 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include "tensor.h"
+
+extern "C" {
+
+    Tensor *create_tensor(float *data, int *shape, int ndim) {
+        Tensor *tensor = (Tensor *)malloc(sizeof(Tensor));
+        if (tensor == NULL) {
+            fprintf(stderr, "Memory allocation failed\n");
+            exit(1);
+        }
+        tensor->data = data;
+        tensor->shape = shape;
+        tensor->ndim = ndim;
+
+        tensor->strides = (int *)malloc(ndim * sizeof(int));
+        if (tensor->strides == NULL) {
+            fprintf(stderr, "Memory allocation failed\n");
+            exit(1);
+        }
+        int stride = 1;
+        for (int i = ndim - 1; i >= 0; i--) {
+            tensor->strides[i] = stride;
+            stride *= shape[i];
+        }
+
+        printf("Tensor created successfully\n");
+        printf("Tensor information:\n");
+        printf("Number of dimensions: %d\n", tensor->ndim);
+        printf("Shape: [");
+        for (int i = 0; i < ndim; i++) {
+            printf("%d", tensor->shape[i]);
+            if (i < ndim - 1) {
+                printf(", ");
+            }
+        }
+        printf("]\n");
+
+        printf("Data:\n[");
+        for (int i = 0; i < stride; i++) {
+            printf("%.2f", tensor->data[i]);
+            if (i < stride - 1) {
+                printf(", ");
+            }
+        }
+        printf("]\n");
+
+        
+        return tensor;
+    }
+
+    float get_item(Tensor *tensor, int *indices) {
+        int index = 0;
+        for (int i = 0; i < tensor->ndim; i++) {
+            index += indices[i] * tensor->strides[i];
+        }
+        return tensor->data[index];
+    }
+
+    void free_tensor(Tensor *tensor) {
+        free(tensor->data);
+        free(tensor->shape);
+        free(tensor->strides);
+        free(tensor);
+    }
+}

src/tensor.h

@@ -0,0 +1,17 @@
+#ifndef TENSOR_H
+#define TENSOR_H
+
+typedef struct {
+    float *data;
+    int *strides;
+    int *shape;
+    int ndim;
+} Tensor;
+
+extern "C" {
+    Tensor *create_tensor(float *data, int *shape, int ndim);
+    float get_item(Tensor *tensor, int *indices);
+    void delete_tensor(Tensor* tensor);
+}
+
+#endif /* TENSOR_H */