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You are a powerful agentic AI coding assistant, powered by Claude 3.5 Sonnet. You operate exclusively in Cursor, the world's best IDE. | |
You are pair programming with a USER to solve their coding task. | |
The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question. | |
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more. | |
This information may or may not be relevant to the coding task, it is up for you to decide. | |
Your main goal is to follow the USER's instructions at each message, denoted by the <user_query> tag. | |
<communication> | |
1. Be conversational but professional. |
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# coding=utf-8 | |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software |
CMake를 왜 쓰는거죠?
좋은 툴은 Visual Studio 뿐입니다. 그 이외에는 전부 사도(邪道)입니다 사도! - 작성자
- 이 문서는 CMake를 주관적으로 서술합니다
- 이 문서를 통해 CMake를 시작하기엔 적합하지 않습니다
https://cgold.readthedocs.io/en/latest/ 3.1 챕터까지 따라해본 이후 기본사항들을 속성으로 익히는 것을 돕기위한 보조자료로써 작성되었습니다
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#!/usr/bin/env python | |
# -*- coding:UTF-8 -*- | |
import torch | |
import torch.nn as nn | |
import torch.nn.init as init | |
def weight_init(m): | |
''' |
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x = torch.randn(10) | |
print(x) | |
y, ind = torch.sort(x, 0) | |
print("y", y) | |
print("ind", ind) | |
unsorted = y.new(*y.size()) | |
unsorted.scatter_(0, ind, y) | |
print("unsorted:", unsorted) | |
print((x - unsorted).abs().max()) |
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#!/usr/bin/env python3 | |
""" | |
License: MIT License | |
Copyright (c) 2023 Miel Donkers | |
Very simple HTTP server in python for logging requests | |
Usage:: | |
./server.py [<port>] | |
""" | |
from http.server import BaseHTTPRequestHandler, HTTPServer |
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#!/usr/bin/env python | |
# coding=utf-8 | |
import numpy as np | |
""" | |
1: Procedure Policy_Iteration(S,A,P,R) | |
2: Inputs | |
3: S is the set of all states | |
4: A is the set of all actions | |
5: P is state transition function specifying P(s'|s,a) |
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# | |
# mnist_cnn_bn.py date. 5/21/2016 | |
# date. 6/2/2017 check TF 1.1 compatibility | |
# | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
import os |
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""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
import numpy as np | |
import cPickle as pickle | |
import gym | |
# hyperparameters | |
H = 200 # number of hidden layer neurons | |
batch_size = 10 # every how many episodes to do a param update? | |
learning_rate = 1e-4 | |
gamma = 0.99 # discount factor for reward |
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