| #include <torch/torch.h> | |
| #include "mnist_reader.h" | |
| #include <fstream> | |
| #include <iomanip> | |
| #include <iostream> | |
| #include <string> | |
| #include <vector> |
| from __future__ import print_function | |
| import argparse | |
| import os | |
| import random | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.parallel | |
| import torch.backends.cudnn as cudnn | |
| import torch.optim as optim | |
| import torch.utils.data |
| namespace torch { | |
| namespace data { | |
| template <typename D = torch::Tensor, typename L = torch::Tensor> | |
| struct Example { | |
| D data; | |
| L label; | |
| }; | |
| template <typename D> |
| class Semaphore { | |
| public: | |
| void post() { | |
| std::lock_guard<std::mutex> lock(mutex_); | |
| count_ += 1; | |
| cv_.notify_one(); | |
| } | |
| void shutdown() { | |
| std::lock_guard<std::mutex> lock(mutex_); |
Hello! We are currently fixing our download links. Please use the following URLs in the meantime. We will replace the link that brought you here soon.
CPU: https://download.pytorch.org/libtorch/nightly/cpu/libtorch-shared-with-deps-latest.zip
CUDA 8.0:
| - Old-style factory functions that accept a type as first argument and size as second argument have been removed. New-style factory functions accepting the size as first argument and [`TensorOptions`](https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/core/TensorOptions.h#L14) as last argument should be used instead. For example, replace your call e.g. to `at::ones(torch::CPU(at::kFloat)), {2, 3})` with `torch::ones({2, 3}, at::kCPU)`. This applies to the following functions: | |
| - `arange` | |
| - `empty` | |
| - `eye` | |
| - `full` | |
| - `linspace` | |
| - `logspace` | |
| - `ones` | |
| - `rand` | |
| - `randint` |
| #include <torch/torch.h> | |
| torch::nn::Linear model(num_features, 1); | |
| torch::optim::SGD optimizer(model->parameters()); | |
| auto data_loader = torch::data::data_loader(dataset); | |
| for (size_t epoch = 0; epoch < 10; ++epoch) { | |
| for (auto batch : data_loader) { | |
| auto prediction = model->forward(batch.data); | |
| auto loss = loss_function(prediction, batch.target); |
| from __future__ import division | |
| from __future__ import print_function | |
| import argparse | |
| import gzip | |
| import os | |
| import sys | |
| import urllib | |
| try: |
| // Place your key bindings in this file to override the defaults | |
| [ | |
| { | |
| "key": "shift+backspace", | |
| "command": "deleteRight", | |
| "when": "textInputFocus && !editorReadonly" | |
| }, | |
| { | |
| "key": "alt+d", | |
| "command": "deleteWordRight", |
