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class Test:
def __init__(self, param1):
pass
def func1(self, skus, quant):
# Signature help for function 2 is not available
self.func2(0, 0)
return None
def func2(self, items, orders):
@equalis3r
equalis3r / init.lua
Last active September 27, 2021 21:03
nvim-lspconfig
-- LSP settings
local nvim_lsp = require("lspconfig")
local on_attach = function(client, bufnr)
vim.api.nvim_buf_set_option(bufnr, "omnifunc", "v:lua.vim.lsp.omnifunc")
local opts = { noremap = true, silent = true }
vim.api.nvim_buf_set_keymap(bufnr, "n", "gD", "<Cmd>lua vim.lsp.buf.declaration()<CR>", opts)
vim.api.nvim_buf_set_keymap(bufnr, "n", "gd", "<Cmd>lua vim.lsp.buf.definition()<CR>", opts)
vim.api.nvim_buf_set_keymap(bufnr, "n", "K", "<Cmd>lua vim.lsp.buf.hover()<CR>", opts)
vim.api.nvim_buf_set_keymap(bufnr, "n", "gi", "<cmd>lua vim.lsp.buf.implementation()<CR>", opts)
@equalis3r
equalis3r / min-char-rnn.py
Created May 10, 2019 15:10 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)