/pycaffe-recurrent

IPython notebook for training multilayer LSTM and RNN networks with pycaffe

Primary LanguagePython

pycaffe-recurrent

IPython notebook for training multilayer LSTM and RNN networks with pycaffe

Example of generated code after training on the Linux kernel for a couple hours:

#include "features.h"

#define SCHED_FEAT_NR]);
   		if (iter->nowname, next_list);
   	return 0;
}

static struct ftrace_ops global_ops;
static struct ftrace_ops global_ops;
static struct ftrace_ops global_ops;
static struct ftrace_ops gotax_trace;
}

static void rcu_torture_err_cb(struct rcu_head *rhp)
{
}

static void rcu_torture_err_cb(struct rcu_head *rhp)
{
}

static void sched_feat_disable(int i)
{
   if (static_key_event_set_filter(&task->cpu_blocked);
   }

   if (is_simeans)
   	return trace_opt_init(&se->current);
   return 0;
}

late_initcall(ftrace_test_read_fidst_cpus;
   	struct cwn_breat *current)
{
   if (chip->subtree_control & (1 << ser_ops) {
   		pr_start = NULL = jiffies;
   return 1;
}

static struct perf_event_context *parent, *next_parent;
   struct perf_event_context *cpuct = CANCE_OTHE_SIZE_DABUL) {
   		if (cont.len) {
   		if (cont.owner == current);
}