serge-sans-paille

    if(GlobalVariable* GA = M.getGlobalVariable("llvm.global.annotations")) {
      // the first operand holds the metadata
      for (Value *AOp : GA->operands()) {
        // all metadata are stored in an array of struct of metadata
        if (ConstantArray *CA = dyn_cast<ConstantArray>(AOp)) {
          // so iterate over the operands
          for (Value *CAOp : CA->operands()) {
            // get the struct, which holds a pointer to the annotated function
            // as first field, and the annotation as second field
            if (ConstantStruct *CS = dyn_cast<ConstantStruct>(CAOp)) {

karpathy

""" 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

StevenLangbroek

export (reducerMap, initialState) => (state = initialState, action) => {
  const reducer = reducerMap[action.type];
  return reducer ? reducer(state, action) : state;
}

lpereira

#include <stdio.h>
#include <stdint.h>
#include <stdlib.h>
#include <ucontext.h>

typedef struct coro_t_		coro_t;
typedef struct thread_t_	thread_t;
typedef int (*coro_function_t)(coro_t *coro);
typedef enum {
    CORO_NEW,