# 递归神经网络不可思议的有效性（下）

### 代数几何（Latex）

\begin{proof}
We may assume that $\mathcal{I}$ is an abelian sheaf on $\mathcal{C}$.
\item Given a morphism $\Delta : \mathcal{F} \to \mathcal{I}$
is an injective and let $\mathfrak q$ be an abelian sheaf on $X$.
Let $\mathcal{F}$ be a fibered complex. Let $\mathcal{F}$ be a category.
\begin{enumerate}
\item \hyperref[setain-construction-phantom]{Lemma}
\label{lemma-characterize-quasi-finite}
Let $\mathcal{F}$ be an abelian quasi-coherent sheaf on $\mathcal{C}$.
Let $\mathcal{F}$ be a coherent $\mathcal{O}_X$-module. Then
$\mathcal{F}$ is an abelian catenary over $\mathcal{C}$.
\item The following are equivalent
\begin{enumerate}
\item $\mathcal{F}$ is an $\mathcal{O}_X$-module.
\end{lemma}

### Linux源代码

/*
* Increment the size file of the new incorrect UI_FILTER group information
* of the size generatively.
*/
static int indicate_policy(void)
{
int error;
if (fd == MARN_EPT) {
/*
* The kernel blank will coeld it to userspace.
*/
if (ss->segment < mem_total)
unblock_graph_and_set_blocked();
else
ret = 1;
goto bail;
}
selector = seg / 16;
setup_works = true;
for (i = 0; i < blocks; i++) {
seq = buf[i++];
bpf = bd->bd.next + i * search;
if (fd) {
current = blocked;
}
}
rw->name = "Getjbbregs";
bprm_self_clearl(&iv->version);
regs->new = blocks[(BPF_STATS << info->historidac)] | PFMR_CLOBATHINC_SECONDS << 12;
return segtable;
}

/*
* If this error is set, we will need anything right after that BSD.
*/
static void action_new_function(struct s_stat_info *wb)
{
unsigned long flags;
int lel_idx_bit = e->edd, *sys & ~((unsigned long) *FIRST_COMPAT);
buf[0] = 0xFFFFFFFF & (bit << 4);
min(inc, slist->bytes);
printk(KERN_WARNING "Memory allocated x/x, "
min(min(multi_run - s->len, max) * num_data_in),
frame_pos, sz + first_seg);
div_u64_w(val, inb_p);
spin_unlock(&disk->queue_lock);
mutex_unlock(&s->sock->mutex);
mutex_unlock(&func->mutex);
return disassemble(info->pending_bh);
}

static void num_serial_settings(struct tty_struct *tty)
{
if (tty == tty)
disable_single_st_p(dev);
pci_disable_spool(port);
return 0;
}

static void do_command(struct seq_file *m, void *v)
{
int column = 32 << (cmd[2] & 0x80);
if (state)
cmd = (int)(int_state ^ (in_8(&ch->ch_flags) & Cmd) ? 2 : 1);
else
seq = 1;
for (i = 0; i < 16; i++) {
if (k & (1 << 1))
pipe = (in_use & UMXTHREAD_UNCCA) +
((count & 0x00000000fffffff8) & 0x000000f) << 8;
if (count == 0)
sub(pid, ppc_md.kexec_handle, 0x20000000);
pipe_set_bytes(i, 0);
}
/* Free our user pages pointer to place camera if all dash */
subsystem_info = &of_changes[PAGE_SIZE];
rek_controls(offset, idx, &soffset);
/* Now we want to deliberately put it to device */
control_check_polarity(&context, val, 0);
for (i = 0; i < COUNTER; i++)
seq_puts(s, "policy ");
}

/*
*
*   This program is free software; you can redistribute it and/or modify it
* the Free Software Foundation.
*
*        This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
*   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
*
*  GNU General Public License for more details.
*
*   You should have received a copy of the GNU General Public License
*    along with this program; if not, write to the Free Software Foundation,
*  Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/

#include <linux/kexec.h>
#include <linux/errno.h>
#include <linux/io.h>
#include <linux/platform_device.h>
#include <linux/multi.h>
#include <linux/ckevent.h>

#include <asm/io.h>
#include <asm/prom.h>
#include <asm/e820.h>
#include <asm/system_info.h>
#include <asm/setew.h>
#include <asm/pgproto.h>

#define STACK_DDR(type)     (func)

#define SWAP_ALLOCATE(nr)     (e)
#define emulate_sigs()  arch_get_unaligned_child()
#define access_rw(TST)  asm volatile("movd %%esp, %0, %3" : : "r" (0));   \

static void stat_PC_SEC __read_mostly offsetof(struct seq_argsqueue, \
pC>[1]);

static void
os_prefix(unsigned long sys)
{
#ifdef CONFIG_PREEMPT
PUT_PARAM_RAID(2, sel) = get_state_state();
set_pid_sum((unsigned long)state, current_state_str(),
(unsigned long)-1->lr_full; low;
}

### 了解到底发生了什么

tyntd-iafhatawiaoihrdemot  lytdws  e ,tfti, astai f ogoh eoase rrranbyne 'nhthnee e
plia tklrgd t o idoe ns,smtt   h ne etie h,hregtrs nigtike,aoaenns lng

"Tmont thithey" fomesscerliund
Keushey. Thom here
sheulke, anmerenith ol sivh I lalterthend Bleipile shuwy fil on aseterlome
coaniogennc Phe lism thond hon at. MeiDimorotion in ther thize."

we counter. He stutn co des. His stanted out one ofler that concossions and was
to gearang reay Jotrets and with fre colt otf paitt thin wall. Which das stimn

Aftair fall unsuch that the hall for Prince Velzonski's that me of
her hearly, and behs to so arwage fiving were to it beloge, pavu say falling misfort
how, and Gogition is so overelical and ofter.

"Kite vouch!" he repeated by her
door. "But I would be done and quarts, feeling, then, son is people...."

"Why do what that day," replied Natasha, and wishing to himself the fact the
princess, Princess Mary was easier, fed in had oftened him.
Pierre aking his soul came to the packs and drove up his father-in-law women.

RNN预测结果和神经元激活可视化

### 源代码

1. 有许多功能（slicing,array/matrix等操作）的CPU / GPU透明的Tensor库。
2. 一个完全独立的代码库，它基于脚本语言（最好是 Python），工作在Tensors上，实现了所有深度学习方面的东西（前馈/后馈，图形计算等）。
3. 它应该可以轻松共享预训练模型（Caffe在这方面做的很好，其他几个则存在不足），这也是至关重要的。
4. 没有编译过程（或者说不要像Theano目前那样做）。深度学习是朝着更大更复杂的网络发展，所以在复杂图算法中花费的时间会成倍增加。重要的是，长时间或者是在开发阶段不进行编译所带来的影响是非常巨大的。而且，进行编译的话就会丢失可解释性和有效进行日志记录/调试的能力。如果为提高效率在图算法开发好后立即编译，那么这样做是可取的。

I've the RNN with and works, but the computed with program of the
RNN with and the computed of the RNN with with and the code

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