25'ten fazla konu seçemezsiniz
Konular bir harf veya rakamla başlamalı, kısa çizgiler ('-') içerebilir ve en fazla 35 karakter uzunluğunda olabilir.
140 satır
4.3 KiB
140 satır
4.3 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "f0668822",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"from torch.utils.data import Dataset"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "a68847cd",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Help on class Dataset in module torch.utils.data.dataset:\n",
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"\n",
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"class Dataset(typing.Generic)\n",
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" | An abstract class representing a :class:`Dataset`.\n",
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" | \n",
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" | All datasets that represent a map from keys to data samples should subclass\n",
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" | it. All subclasses should overwrite :meth:`__getitem__`, supporting fetching a\n",
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" | data sample for a given key. Subclasses could also optionally overwrite\n",
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" | :meth:`__len__`, which is expected to return the size of the dataset by many\n",
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" | :class:`~torch.utils.data.Sampler` implementations and the default options\n",
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" | of :class:`~torch.utils.data.DataLoader`.\n",
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" | \n",
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" | .. note::\n",
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" | :class:`~torch.utils.data.DataLoader` by default constructs a index\n",
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" | sampler that yields integral indices. To make it work with a map-style\n",
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" | dataset with non-integral indices/keys, a custom sampler must be provided.\n",
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" | \n",
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" | Method resolution order:\n",
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" | Dataset\n",
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" | typing.Generic\n",
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" | builtins.object\n",
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" | \n",
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" | Methods defined here:\n",
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" | \n",
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" | __add__(self, other: 'Dataset[T_co]') -> 'ConcatDataset[T_co]'\n",
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" | \n",
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" | __getitem__(self, index) -> +T_co\n",
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" | \n",
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" | ----------------------------------------------------------------------\n",
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" | Data descriptors defined here:\n",
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" | \n",
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" | __dict__\n",
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" | dictionary for instance variables (if defined)\n",
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" | \n",
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" | __weakref__\n",
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" | list of weak references to the object (if defined)\n",
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" | \n",
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" | ----------------------------------------------------------------------\n",
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" | Data and other attributes defined here:\n",
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" | \n",
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" | __annotations__ = {}\n",
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" | \n",
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" | __orig_bases__ = (typing.Generic[+T_co],)\n",
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" | \n",
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" | __parameters__ = (+T_co,)\n",
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" | \n",
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" | ----------------------------------------------------------------------\n",
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" | Class methods inherited from typing.Generic:\n",
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" | \n",
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" | __class_getitem__(params) from builtins.type\n",
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" | Parameterizes a generic class.\n",
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" | \n",
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" | At least, parameterizing a generic class is the *main* thing this method\n",
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" | does. For example, for some generic class `Foo`, this is called when we\n",
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" | do `Foo[int]` - there, with `cls=Foo` and `params=int`.\n",
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" | \n",
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" | However, note that this method is also called when defining generic\n",
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" | classes in the first place with `class Foo(Generic[T]): ...`.\n",
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" | \n",
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" | __init_subclass__(*args, **kwargs) from builtins.type\n",
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" | This method is called when a class is subclassed.\n",
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" | \n",
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" | The default implementation does nothing. It may be\n",
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" | overridden to extend subclasses.\n",
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"\n"
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]
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}
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],
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"source": [
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"help(Dataset)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "de52bf0e",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"class Mydata(DataSet):\n",
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" def __init__(DataSet):\n",
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" pass\n",
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" \n",
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" def __getitem__(self,idx):\n",
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" \n",
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" \n",
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" "
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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