YusukeSuzuki

import random
from random import choice

import tensorflow as tf
import numpy as np
import pyfastnoisesimd as fns

def ch3_fractal_noise(size_chw, seed,
    color_gain_min=0.5, color_gain_max=1.0,
    octaves_min=3, octaves_max=6,

YusukeSuzuki

$ python3 -m fastrnns.bench
Namespace(cnns=None, cuda_pointwise_block_count=None, cuda_pointwise_block_size=None, cuda_pointwise_loop_level=None, device='cuda', executor=None, fuser='te', group=['cnns', 'rnns'], hiddenSize=512, inputSize=512, miniBatch=64, nloops=100, numLayers=1, print_json=None, rnns=None, sep=' ', seqLength=100, variable_lstms=False, warmup=10)
Benchmarking LSTMs...
            name          avg_fwd          std_fwd         info_fwd          avg_bwd          std_bwd         info_bwd
           cudnn            3.384           0.2857             None            3.613          0.06748             None
            aten            9.766            0.415             None            18.85           0.1766             None
             jit            10.48           0.1774             None            18.53           0.8058             None
      jit_premul            8.273          0.07718             None            14.63           0.1991             None
 jit_premul_bias            8.143       

YusukeSuzuki

DCT_TABLE_BUFFER = b"\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\x00\x00\x80?\xbe\x14\xfb?0\xdb\xd4?\xda9\x8e?\xc0\xc5\xc7>\xc0\xc5\xc7\xbe\xda9\x8e\xbf0\xdb\xd4\xbf\xbe\x14\xfb\xbf\xbe\x14\xfb?0\xdb\xd4?\xda9\x8e?\xc0\xc5\xc7>\xc0\xc5\xc7\xbe\xda9

YusukeSuzuki

directories = [ 
    $(readlink -m ~/Downloads).strip(),
    $(readlink -m ~/Desktop).strip(),
    ]   

for d in directories:
    ls -l @(p)

YusukeSuzuki

import os
import tensorflow as tf
from tensorflow.contrib import tpu
from tensorflow.contrib.cluster_resolver import TPUClusterResolver

IMAGE_FILES='gs://MY_OWN_GCS_BUCKET/celeba/files.txt'
SIZE=(128,128)
BATCH=128
LR=1e-4

YusukeSuzuki

global_step = 243830
global_step = 243840
global_step = 243850
2018-11-20 23:42:59.740578: W tensorflow/core/common_runtime/bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 301.50MiB. The caller indicates that this is not a failure, bu
t may mean that there could be performance gains if more memory were available.
2018-11-20 23:42:59.741211: W tensorflow/core/common_runtime/bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 301.50MiB. The caller indicates that this is not a failure, bu
t may mean that there could be performance gains if more memory were available.
2018-11-20 23:42:59.741553: E tensorflow/stream_executor/cuda/cuda_dnn.cc:81] 
Traceback (most recent call last):
  File "/home/yusuke/.pyenv/versions/tf1.10/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1278, in _do_call

YusukeSuzuki

import tensorflow as tf
import numpy as np
from keras.layers import Conv2D

img = tf.constant(np.ones([16,128,128,3]), dtype=tf.float32)
conv = Conv2D(32, 3)
y = conv(img)

graph = tf.get_default_graph()

YusukeSuzuki

from pathlib import Path
import cv2

d = Path('val2017')

for f in d.glob('*.jpg'):
    img = cv2.imread(str(f))

YusukeSuzuki

import tensorflow as tf
import numpy as np
import sys

# simple k-means clustering with tensorflow
# this is my practice code for tensorflow graph coding

# parameters

K_SIZE = 5

YusukeSuzuki

#!/usr/bin/env python3

# This is full TensolFlow version of Ryan Dahl's Automatic Colorization.
# The original is here -> http://tinyclouds.org/colorize/
import sys
import tensorflow as tf

INPUT_EDGE = 224
INPUT_FILE = 'shark.jpg'
OUTPUT_FILE = 'shark-color.jpg'