"read_from_fs": False
},
{
"samples": n_samples,
"backend": "hub:pytorch",
"read_from_fs": True
},
{
"samples": n_samples,
"backend": "tensorflow",
"read_from_fs": False
},
{
"samples": n_samples,
"backend": "tensorflow",
"read_from_fs": True
},
{
"samples": n_samples,
"backend": "hub:tensorflow",
"read_from_fs": False
},
{
"samples": n_samples,
"backend": "hub:tensorflow",
"read_from_fs": True
},
]
logs = [empty_train_hub(**args) for args in params]
report(logs)
import helper
helper.load_backends()
code = """
(begin
(define (grow)
(set! s (string-append "123" s "456" s "789"))
(set! s (string-append
(substring s (quotient (string-length s) 2) (string-length s))
(substring s 0 (+ 1 (quotient (string-length s) 2)))))
s)
(define (trial n)
(do ((i 0 (+ i 1)))
((> (string-length s) n) (string-length s))
(grow))))
"""
def call_trial(vm):
vm.eval(vm.compile('(define s "abcdef")'))
scm = vm.eval(vm.compile('(trial 1000000)'))
assert vm.fromscheme(scm) == 1048566
bm = Benchmark(title="string-append and substring performance", repeat=10)
for backend in helper.BACKENDS:
vm = helper.VM(backend=backend)
vm.eval(vm.compile(code))
bm.measure(backend, call_trial, vm)
helper.report(bm.report())
from benchmark import Benchmark
import helper
helper.load_backends()
code = """
(define (tak x y z)
(if (not (< y x))
z
(tak (tak (- x 1) y z)
(tak (- y 1) z x)
(tak (- z 1) x y))))
"""
def call_tak(vm):
for case in [(7, (18, 12, 6)), (15, (30, 15, 9)), (10, (33, 15, 9)),
(15, (40, 15, 9))]:
scm = vm.apply(vm.get("tak"), [vm.toscheme(x) for x in case[1]])
assert vm.fromscheme(scm) == case[0]
bm = Benchmark(title="tak benchmark", repeat=1)
for backend in helper.BACKENDS:
vm = helper.VM(backend=backend)
vm.eval(vm.compile(code))
bm.measure(backend, call_tak, vm)
helper.report(bm.report())
"download": t3 - t2,
"write_to_fs": t1 - t0,
}
def upload_and_download(samples=30, chunksize=None, name="hub"):
"""
Uploads dataset into S3 and then downlods using hub package
"""
ds = generate_dataset([(samples, 256, 256), (samples, 256, 256)],
chunksize=1)
t1 = time.time()
ds = ds.store(f"{BUCKET}/transfer/upload")
t2 = time.time()
ds.store("/tmp/download")
t3 = time.time()
return {"name": name, "upload": t2 - t1, "download": t3 - t2}
if __name__ == "__main__":
samples = 64
chunksize = None
import hub
hub.init(processes=True, n_workers=8, threads_per_worker=1)
r1 = upload_and_download(samples, chunksize=chunksize)
r2 = aws_cli_copy(samples, chunksize=chunksize)
report([r1, r2])
def send_story_report(story_to_read):
item = story_to_read
reported_by = session['username']
report_reason = request.form["reason"]
report(item, report_reason, story_to_read, reported_by)
return redirect(url_for("admin_page"))
from helper import report
"""
Daily report
- positions
- balance
- Margin balance
- Unrealized PNL
"""
if __name__ == '__main__':
report()
