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Create and print a tensor

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lucasdelimanogueira 2024-04-26 00:33:28 -03:00
parent e05e85663d
commit 06b82066ae
8 changed files with 257 additions and 0 deletions
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python/__pycache__/tensor.cpython-39.pyc Normal file
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python/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)
]
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__()

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{
"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
}