Add tensors (still need to fix)

This commit is contained in:
lucasdelimanogueira 2024-04-26 18:38:07 -03:00
parent daff666ab4
commit 48f8c1d83d
10 changed files with 350 additions and 1 deletions

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@ -5,7 +5,7 @@ CXX := g++
CXXFLAGS := -Wall -Werror -fpic
# Source files
SRCS := ../src/tensor.cpp
SRCS := ../csrc/tensor.cpp
# Object files
OBJS := $(SRCS:.cpp=.o)

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138
csrc/tensor.cpp Normal file
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#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->size = 1;
for (int i = 0; i < ndim; i++) {
tensor->size *= shape[i];
}
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("Number size: %d\n", tensor->size);
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\n\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];
}
Tensor* add_tensor(Tensor* tensor1, Tensor* tensor2) {
if (tensor1->ndim != tensor2->ndim) {
fprintf(stderr, "Tensors must have the same number of dimensions %d and %d for addition\n", tensor1->ndim, tensor2->ndim);
exit(1);
}
int ndim = tensor1->ndim;
int* shape = (int*)malloc(ndim * sizeof(int));
if (shape == NULL) {
fprintf(stderr, "Memory allocation failed\n");
exit(1);
}
printf("Size: %d\n", tensor1->size);
printf("Data: [");
for (int i = 0; i < tensor1->size; i++) {
printf("%.2f", tensor1->data[i]);
if (i < tensor1->size - 1) {
printf(", ");
}
}
printf("]\n");
printf("Size: %d\n", tensor2->size);
printf("Data: [");
for (int i = 0; i < tensor2->size; i++) {
printf("%.2f", tensor2->data[i]);
if (i < tensor2->size - 1) {
printf(", ");
}
}
printf("]\n");
printf("Shapes : [");
for (int i = 0; i < tensor1->ndim; i++) {
printf("%d", tensor1->shape[i]);
if (i < tensor1->ndim - 1) {
printf(", ");
}
}
printf("]\n");
printf("Shapes : [");
for (int i = 0; i < tensor2->ndim; i++) {
printf("%d", tensor2->shape[i]);
if (i < tensor2->ndim - 1) {
printf(", ");
}
}
printf("]\n");
for (int i = 0; i < ndim; i++) {
if (tensor1->shape[i] != tensor2->shape[i]) {
fprintf(stderr, "Tensors must have the same shape %d and %d at index %d for addition\n", tensor1->shape[i], tensor2->shape[i], i);
exit(1);
}
shape[i] = tensor1->shape[i];
}
float* result_data = (float*)malloc(tensor1->size * sizeof(float));
if (result_data == NULL) {
fprintf(stderr, "Memory allocation failed\n");
exit(1);
}
for (int i = 0; i < tensor1->size; i++) {
result_data[i] = tensor1->data[i] + tensor2->data[i];
}
return create_tensor(result_data, shape, ndim);
}
}

19
csrc/tensor.h Normal file
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@ -0,0 +1,19 @@
#ifndef TENSOR_H
#define TENSOR_H
typedef struct {
float *data;
int* strides;
int* shape;
int ndim;
int size;
} Tensor;
extern "C" {
Tensor* create_tensor(float* data, int* shape, int ndim);
float get_item(Tensor* tensor, int* indices);
Tensor* create_tensor(float* data, int* shape, int ndim);
Tensor* add_tensor(Tensor* tensor1, Tensor* tensor2);
}
#endif /* TENSOR_H */

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csrc/tensor.o Normal file

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89
norch/tensor.py Normal file
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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),
('size', ctypes.c_int),
]
class Tensor:
_C = ctypes.CDLL("../build/libtensor.so")
def __init__(self, data):
data, shape = self.flatten(data)
# Adjust the path to the shared library
self.data = (ctypes.c_float * len(data))(*data)
self.shape = shape
self.ndim = len(shape)
Tensor._C.create_tensor.argtypes = [ctypes.POINTER(ctypes.c_float), ctypes.POINTER(ctypes.c_int), ctypes.c_int]
Tensor._C.create_tensor.restype = ctypes.POINTER(CTensor)
self.tensor = Tensor._C.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")
Tensor._C.get_item.argtypes = [ctypes.POINTER(CTensor), ctypes.POINTER(ctypes.c_int)]
Tensor._C.get_item.restype = ctypes.c_float
indices = (ctypes.c_int * len(indices))(*indices)
value = Tensor._C.get_item(self.tensor, indices)
return value
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__()
def __add__(self, other):
if self.shape != other.shape:
raise ValueError("Tensors must have the same shape for addition")
Tensor._C.add_tensor.argtypes = [ctypes.POINTER(CTensor), ctypes.POINTER(CTensor)]
Tensor._C.add_tensor.restype = ctypes.POINTER(CTensor)
result_tensor_ptr = Tensor._C.add_tensor(self.tensor, other.tensor)
result_data = [result_tensor_ptr.contents.data[i] for i in range(self.shape[0] * self.shape[1])]
result_shape = [result_tensor_ptr.contents.shape[i] for i in range(result_tensor_ptr.contents.ndim)]
return Tensor(result_data, result_shape)
if __name__ == "__main__":
from tensor import Tensor
import time
ini = time.time()
a = Tensor([[1, 2, 3], [1, 2, 3]])
b = Tensor([[1, 2, 3], [1, 2, 3]])
c = a + b
fim = time.time()
print(fim-ini)

98
norch/tests.ipynb Normal file
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@ -0,0 +1,98 @@
{
"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
}

5
test.sh Executable file
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@ -0,0 +1,5 @@
cd build
make
cd ..
cd norch
python3 tensor.py