shyoshyo

~/p/ncurses-6.1 ➜ ./configure --prefix=$HOME/.local --enable-shared --with-shared --without-debug

shyoshyo

#!/bin/sh
sudo fdisk -l
sudo grub-install --root-directory=/mnt /dev/sda
sudo mount /dev/sda2 /mnt

shyoshyo

#!/usr/bin/env python3

"""
整数拆分问题：n 个相同的球，分成若干堆，有几种分法？
如果要和上界比较，那么绘制下列图像：
  * 分拆数及其上界随 n 变化的图像
  * 分拆数与其上界之比随 n 变化的图像
"""

import argparse

shyoshyo

def spectral_normed_weight(W, u=None, num_iters=1, update_collection=tf.GraphKeys.UPDATE_OPS, name='spectral_norm', eps=1e-12, reuse=False):
    with tf.variable_scope(name, reuse=reuse):
        W_shape = W.shape.as_list()
        n_in    = W.shape[:-1].num_elements()
        n_out   = W.shape[-1].value

        W_reshaped = tf.reshape(W, [n_in, n_out])

        if u is None: u = tf.get_variable("u", shape=[1, n_out], initializer=tf.truncated_normal_initializer(), trainable=False)
        # if u is None: u = tf.Variable(tf.truncated_normal(shape=[1, n_out]), name='u', trainable=False)

shyoshyo

CXX = /usr/bin/g++
NVCC = /usr/local/cuda-9.1/bin/nvcc

CUDA_LIB    = /usr/local/cuda-9.1/lib64
CUDA_INC    = /usr/local/cuda-9.1/include
CUDA_CFLAGS = -I $(CUDA_INC)
CUDA_LFLAGS = -lcudart -L $(CUDA_LIB)

TF_LIB    = $(shell python -c 'import tensorflow as tf; print(tf.sysconfig.get_lib())')
TF_INC    = $(shell python -c 'import tensorflow as tf; print(tf.sysconfig.get_include())')