def test_compresses_images_specified(self):
"Test function compresses images with filename and input dir args."
args = self.parser.parse_args(['test.png', '-i', self.testdir])
compress(args)
result = os.listdir(self.testdir)[1]
expected = 'test_compressed.png'
self.assertEqual(result, expected)
def test_compresses_images_specified(self):
"Test function compresses images with filename and input dir args."
args = self.parser.parse_args(['test.png', '-i', self.testdir])
compress(args)
result = os.listdir(self.testdir)[1]
expected = 'test_compressed.png'
self.assertEqual(result, expected)
def send_diagram_execute():
global now
global diagram_filename
now = datetime.now()
if diagram_filename is "":
print("Select valid type")
else:
compressor.compress(diagram_filename, topic_name, now)
diagram_filename=""
def test_compresses_images_and_puts_in_output_dir(self):
"""
Test function compresses images with filename, input dir and output dir
args specified. Should also create the output dir if it doesn't exist.
"""
args = self.parser.parse_args(
['test.png', '-i', self.testdir, '-o', self.outputdir])
compress(args)
result = os.listdir(self.outputdir)[0]
expected = 'test.png'
self.assertEqual(result, expected)
def test_compresses_images_and_puts_in_output_dir(self):
"""
Test function compresses images with filename, input dir and output dir
args specified. Should also create the output dir if it doesn't exist.
"""
args = self.parser.parse_args(
['test.png', '-i', self.testdir, '-o', self.outputdir])
compress(args)
result = os.listdir(self.outputdir)[0]
expected = 'test.png'
self.assertEqual(result, expected)
def on_complete(self):
self.cache.release(len(self.page.response))
self.page.response = self.page.partial_response
self.page.partial_response = ''
self.page.complete = True
self.close()
# start compression
if len(self.page.response) > 100:
response = self.page.response
def on_compressed(data):
if response != self.page.response:
return
headers = re.sub(r'(!\r)\n', '\r\n', response[:self.page.response_headers_len])
headers = re.sub(r'content-length\s*:[^\r]*\r\n', '', headers)
headers = headers[:-2] + ('content-length: %i\r\ncontent-encoding: deflate\r\n\r\n' % len(data))
self.page.compressed = headers + data
compress(self.loop, response[self.page.response_headers_len:], on_compressed)
def test_with_bad_filename(self):
"Test function errors out with non-existant filename."
with self.assertRaises(FileNotFoundError):
args = self.parser.parse_args(['test_bad.png', '-i', self.testdir])
compress(args)
import sys
import compressor
file = sys.argv[1]
try:
extension = file.split('.')[1]
except IndexError:
print('File without extension! please enter the complete file name.')
exit(0)
compressor.compress(file)
from compressor import compress
from wiki_converter import wiki_knml_converter
import os
file_name = input("Enter path of XML file:")
wiki_knml_converter(file_name)
file_name = file_name[:-4] + '.knml'
compress(file_name)
os.remove(file_name)
def compress(data):
try:
return compressor.compress(data)
except OSError:
return pycompressor.compress(data)
import torch
import sys
import time
torch.cuda.set_device(0)
a = torch.randn(22, 100, 224, 224)
a = a.cuda()
#print('before sending')
#print(a)
compressor = compressor.compressor(using_cuda=True)
# warmups to amortize allocation costs
c, size = compressor.compress(a)
d = compressor.uncompress(c, size)
del c, size, d
c, size = compressor.compress(a)
d = compressor.uncompress(c, size)
del c, size, d
# benchmark
torch.cuda.synchronize()
start = time.time()
c, size = compressor.compress(a)
torch.cuda.synchronize()
end = time.time()
print('Compression time cost')
print(str(end - start))
#print('during sending')
from matplotlib import cm
from matplotlib import gridspec
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
from compressor import compress, decompress
from smoothing import smooth
if __name__ == '__main__':
sample_rate = 48000
silence_length = 0.4
raw_data = np.fromfile('wtf.bin', dtype=np.int8)
comp_data = compress(raw_data)
smooth_data = smooth(comp_data, int(sample_rate * silence_length))
# print(list(filter(lambda x: x > int(sample_rate * silence_length), zeros)))
# print(list(filter(lambda x: x > int(sample_rate * silence_length), ones)))
# plt.figure(figsize=(13, 8))
#
# ax = plt.subplot(1, 1, 1)
# ax.set_title("Validation Data")
#
# ax.set_autoscaley_on(False)
# ax.set_ylim([32, 43])
# ax.set_autoscalex_on(False)
# # ax.set_xlim([-126, -112])
# plt.scatter(list(range(int(len(comp_data)))),
# comp_data,
def compress(data):
try:
return compressor.compress(data)
except OSError:
return pycompressor.compress(data)
def test_with_bad_filename(self):
"Test function errors out with non-existant filename."
with self.assertRaises(FileNotFoundError):
args = self.parser.parse_args(['test_bad.png', '-i', self.testdir])
compress(args)
torch.cuda.synchronize()
ATOMO_coding_time = time.time() - ATOMO_coding_start
ATOMO_decoding_start = time.time()
result = ATOMO_coder.decode(code)
torch.cuda.synchronize()
ATOMO_decoding_time = time.time() - ATOMO_decoding_start
ATOMO_time = time.time() - ATOMO_start
#Signum
torch.cuda.synchronize()
Signum_start = time.time()
Signum_coding_start = time.time()
temp, tensor_size = compressor.compress(sample)
torch.cuda.synchronize()
Signum_coding_time = time.time() - Signum_coding_start
Signum_decoding_start = time.time()
result = compressor.uncompress(temp, tensor_size)
torch.cuda.synchronize()
Signum_decoding_time = time.time() - Signum_decoding_start
Signum_time = time.time() - Signum_start
print('---------')
print('Signum_full_time', Signum_time)
print('Signum_coding_time', Signum_coding_time)
print('Signum_decoding_time', Signum_decoding_time)
