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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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} |