hvy

import numpy as np
from chainer import Variable
from chainer import functions as F

# Pixel shuffle used in sub-pixel convolutions, in Chainer
# https://arxiv.org/pdf/1609.05158v2.pdf
#
# Example:
# Scaling factor: 3
# In shape: (1, 9, 4, 4)

hvy

from chainer import Variable
from chainer import links as L
import numpy as np


# Compare single-channel Convolution2D with Deconvolution2D
h = 128
w = 128
x = np.arange(h * w, dtype=np.float32)
x = x.reshape(1, 1, h, w)

hvy

import argparse

import numpy

import chainer
import chainer.functions as F
import chainer.links as L
from chainer import training
from chainer.training import extensions

hvy

# https://github.com/python/cpython/blob/master/Lib/profile.py
def _show(self, prof, filename, sort):
        if filename is not None:
            # NOTE(hvy): Replace environment variables similar to how
            # nvprof does by e.g. replacing out_%q{MV2_COMM_WORLD_RANK} with
            # out_1, out_2, etc. depending on the value of the variable
            # MV2_COMM_WORLD_RANK
            import re
            if re.search(r'\%q{(.*?)\}', filename) is not None:
                filename = re.sub(r'\%q{(.*?)\}',

hvy

Started by upstream project "chainer/chainer_pr" build number 333
originally caused by:
 GitHub pull request #6441 of commit 87e4eb6f662973b13d7b565c55a6ad71982fb283, no merge conflicts.
Building remotely on gpcl-gpu205 (mn1-p100 sakura11) in workspace /home/jenkins-external-slave/workspace/chainer/chainer_pr/TEST/CHAINERX_misc/label/mn1-p100
using credential 40bb97f1-7bf9-4f59-b66e-8d81d634b1a9
Wiping out workspace first.
Cloning the remote Git repository
Cloning repository [email protected]:chainer/chainer-test.git
 > git init /home/jenkins-external-slave/workspace/chainer/chainer_pr/TEST/CHAINERX_misc/label/mn1-p100 # timeout=10
Fetching upstream changes from [email protected]:chainer/chainer-test.git

hvy

"""
Optuna example that optimizes a simple quadratic function in parallel using `joblib` allowing
arbitrary arguments to the objective function.

Run the example as follows.

    $ python quadratic_joblib_simple.py

If you need to rerun the example and thus delete previous studies, you can use the Optuna CLI.

hvy

## Add `_` prefix to the names of private interfaces.

Interfaces in `optuna`, i.e. submodules, classes and attributes are either public, private for internal use in `optuna` or private for internal use within a parcitular class. Private interfaces are not part of the public API and are not expected to be directly used by the library user. They are only meant for internal use in `optuna`. This reserves them for future changes and allows modifications without breaking compatibility. It is therefore important to clearly communciate whether an interfaces is public or private and `optuna` distinigushes between them as follows.

Reference: https://docs.python.org/3/tutorial/classes.html#private-variables.

### Good

```python
def public_function():  # Used by users.

hvy

import logging
import threading
import time

import joblib
import tqdm


class TqdmLoggingHandler(logging.StreamHandler):
    def emit(self, record):

hvy

from collections import OrderedDict
import time

from matplotlib import pyplot as plt
import optuna
from optuna import samplers
from optuna.storages import RDBStorage
from optuna.storages import RedisStorage

hvy

"""
Plots importances evaluated by fANOVA (AutoML.org) and Fanova (sklearn based implementation).

1. Loads data from csv containing parameter configuration-objective value pairs.
2. Loads search space definitions from csv.
3. Evaluates all single and pairwise importances between parameters.
4. Repeats evaluation N times (with different random seeds).
5. Plots the average over N evaluations.
"""
import argparse