| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | package org.apache.commons.imaging.formats.psd; | |
| 18 | ||
| 19 | import org.apache.commons.imaging.util.Debug; | |
| 20 | ||
| 21 | public class PsdConstants { | |
| 22 | static final ImageResourceType fImageResourceTypes[]; | |
| 23 | ||
| 24 | public String getDescription(final int id) { | |
| 25 |
3
1. getDescription : changed conditional boundary → NO_COVERAGE 2. getDescription : Changed increment from 1 to -1 → NO_COVERAGE 3. getDescription : negated conditional → NO_COVERAGE |
for (final ImageResourceType fImageResourceType : fImageResourceTypes) { |
| 26 |
1
1. getDescription : negated conditional → NO_COVERAGE |
if (fImageResourceType.ID == id) { |
| 27 |
1
1. getDescription : mutated return of Object value for org/apache/commons/imaging/formats/psd/PsdConstants::getDescription to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return fImageResourceType.Description; |
| 28 | } | |
| 29 | } | |
| 30 |
1
1. getDescription : mutated return of Object value for org/apache/commons/imaging/formats/psd/PsdConstants::getDescription to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return "Unknown"; |
| 31 | } | |
| 32 | ||
| 33 | static { | |
| 34 | ImageResourceType temp[] = null; | |
| 35 | ||
| 36 | try { | |
| 37 | temp = new ImageResourceType[] { | |
| 38 | new ImageResourceType( | |
| 39 | 0x03E8, | |
| 40 | 1000, | |
| 41 | " Contains five 2 byte values: number of channels, rows, columns, depth, and mode."), | |
| 42 | new ImageResourceType(0x03E9, 1001, | |
| 43 | "Optional. Macintosh print manager print info record."), | |
| 44 | new ImageResourceType(0x03EB, 1003, | |
| 45 | " Contains the indexed color table."), | |
| 46 | new ImageResourceType(0x03ED, 1005, | |
| 47 | "ResolutionInfo structure. See Appendix A in Photoshop SDK Guide.pdf."), | |
| 48 | new ImageResourceType(0x03EE, 1006, | |
| 49 | "Names of the alpha channels as a series of Pascal strings."), | |
| 50 | new ImageResourceType(0x03EF, 1007, | |
| 51 | "DisplayInfo structure. See Appendix A in Photoshop SDK Guide.pdf ."), | |
| 52 | new ImageResourceType(0x03F0, 1008, | |
| 53 | "Optional. The caption as a Pascal string."), | |
| 54 | new ImageResourceType( | |
| 55 | 0x03F1, | |
| 56 | 1009, | |
| 57 | "Border information. Contains a fixed-number for the border width, and 2 bytes for border units (1=inches, 2=cm, 3=points, 4=picas, 5=columns)."), | |
| 58 | new ImageResourceType(0x03F2, 1010, | |
| 59 | "Background color. See the Colors additional file information."), | |
| 60 | new ImageResourceType( | |
| 61 | 0x03F3, | |
| 62 | 1011, | |
| 63 | "Print flags. A series of one byte boolean values (see Page Setup dialog): labels, crop marks, color bars, registration marks, negative, flip, interpolate, caption."), | |
| 64 | new ImageResourceType(0x03F4, 1012, | |
| 65 | "Grayscale and multichannel halftoning information."), | |
| 66 | new ImageResourceType(0x03F5, 1013, | |
| 67 | "Color halftoning information."), | |
| 68 | new ImageResourceType(0x03F6, 1014, | |
| 69 | "Duotone halftoning information."), | |
| 70 | new ImageResourceType(0x03F7, 1015, | |
| 71 | "Grayscale and multichannel transfer function."), | |
| 72 | new ImageResourceType(0x03F8, 1016, | |
| 73 | "Color transfer functions."), | |
| 74 | new ImageResourceType(0x03F9, 1017, | |
| 75 | "Duotone transfer functions."), | |
| 76 | new ImageResourceType(0x03FA, 1018, | |
| 77 | "Duotone image information."), | |
| 78 | new ImageResourceType(0x03FB, 1019, | |
| 79 | "Two bytes for the effective black and white values for the dot range."), | |
| 80 | new ImageResourceType(0x03FC, 1020, "Obsolete."), | |
| 81 | new ImageResourceType(0x03FD, 1021, "EPS options."), | |
| 82 | new ImageResourceType( | |
| 83 | 0x03FE, | |
| 84 | 1022, | |
| 85 | "Quick Mask information. 2 bytes containing Quick Mask channel ID, 1 byte boolean indicating whether the mask was initially empty."), | |
| 86 | new ImageResourceType(0x03FF, 1023, "Obsolete."), | |
| 87 | new ImageResourceType( | |
| 88 | 0x0400, | |
| 89 | 1024, | |
| 90 | "Layer state information. 2 bytes containing the index of target layer. 0=bottom layer."), | |
| 91 | new ImageResourceType(0x0401, 1025, | |
| 92 | "Working path (not saved). See path resource format later in this chapter."), | |
| 93 | new ImageResourceType( | |
| 94 | 0x0402, | |
| 95 | 1026, | |
| 96 | "Layers group information. 2 bytes per layer containing a group ID for the dragging groups. Layers in a group have the same group ID."), | |
| 97 | new ImageResourceType(0x0403, 1027, "Obsolete."), | |
| 98 | new ImageResourceType( | |
| 99 | 0x0404, | |
| 100 | 1028, | |
| 101 | "IPTC-NAA record. This contains the File Info... information. See the IIMV4.pdf document."), | |
| 102 | new ImageResourceType(0x0405, 1029, | |
| 103 | "Image mode for raw format files."), | |
| 104 | new ImageResourceType(0x0406, 1030, | |
| 105 | "JPEG quality. Private."), | |
| 106 | new ImageResourceType( | |
| 107 | 0x0408, | |
| 108 | 1032, | |
| 109 | "Grid and guides information. See grid and guides resource format later in this chapter."), | |
| 110 | new ImageResourceType(0x0409, 1033, | |
| 111 | "Thumbnail resource. See thumbnail resource format later in this chapter."), | |
| 112 | new ImageResourceType( | |
| 113 | 0x040A, | |
| 114 | 1034, | |
| 115 | "Copyright flag. Boolean indicating whether image is copyrighted. Can be set via Property suite or by user in File Info..."), | |
| 116 | new ImageResourceType( | |
| 117 | 0x040B, | |
| 118 | 1035, | |
| 119 | "URL. Handle of a text string with uniform resource locator. Can be set via Property suite or by user in File Info..."), | |
| 120 | new ImageResourceType(0x040C, 1036, | |
| 121 | "Thumbnail resource. See thumbnail resource format later in this chapter."), | |
| 122 | new ImageResourceType( | |
| 123 | 0x040D, | |
| 124 | 1037, | |
| 125 | "Global Angle. 4 bytes that contain an integer between 0..359 which is the global lighting angle for effects layer. If not present assumes 30."), | |
| 126 | new ImageResourceType( | |
| 127 | 0x040E, | |
| 128 | 1038, | |
| 129 | "Color samplers resource. See color samplers resource format later in this chapter."), | |
| 130 | new ImageResourceType( | |
| 131 | 0x040F, | |
| 132 | 1039, | |
| 133 | "ICC Profile. The raw bytes of an ICC format profile, see the ICC34.pdf and ICC34.h files from the Internation Color Consortium located in the documentation section."), | |
| 134 | new ImageResourceType(0x0410, 1040, | |
| 135 | "One byte for Watermark."), | |
| 136 | new ImageResourceType( | |
| 137 | 0x0411, | |
| 138 | 1041, | |
| 139 | "ICC Untagged. 1 byte that disables any assumed profile handling when opening the file. 1 = intentionally untagged."), | |
| 140 | new ImageResourceType( | |
| 141 | 0x0412, | |
| 142 | 1042, | |
| 143 | "Effects visible. 1 byte global flag to show/hide all the effects layer. Only present when they are hidden."), | |
| 144 | new ImageResourceType( | |
| 145 | 0x0413, | |
| 146 | 1043, | |
| 147 | "Spot Halftone. 4 bytes for version, 4 bytes for length, and the variable length data."), | |
| 148 | new ImageResourceType( | |
| 149 | 0x0414, | |
| 150 | 1044, | |
| 151 | "Document specific IDs, layer IDs will be generated starting at this base value or a greater value if we find existing IDs to already exceed it. It's purpose is to avoid the case where we add layers, flatten, save, open, and then add more layers that end up with the same IDs as the first set. 4 bytes."), | |
| 152 | new ImageResourceType(0x0415, 1045, | |
| 153 | "Unicode Alpha Names. 4 bytes for length and the string as a unicode string."), | |
| 154 | new ImageResourceType( | |
| 155 | 0x0416, | |
| 156 | 1046, | |
| 157 | "Indexed Color Table Count. 2 bytes for the number of colors in table that are actually defined"), | |
| 158 | new ImageResourceType(0x0417, 1047, | |
| 159 | "Tansparent Index. 2 bytes for the index of transparent color, if any."), | |
| 160 | new ImageResourceType(0x0419, 1049, | |
| 161 | "Global Altitude. 4 byte entry for altitude"), | |
| 162 | new ImageResourceType(0x041A, 1050, | |
| 163 | "Slices. See description later in this chapter"), | |
| 164 | new ImageResourceType(0x041B, 1051, | |
| 165 | "Workflow URL. Unicode string, 4 bytes of length followed by unicode string."), | |
| 166 | new ImageResourceType( | |
| 167 | 0x041C, | |
| 168 | 1052, | |
| 169 | "Jump To XPEP. 2 bytes major version, 2 bytes minor version, 4 bytes count. Following is repeated for count: 4 bytes block size, 4 bytes key, if key = 'jtDd' then next is a Boolean for the dirty flag otherwise it's a 4 byte entry for the mod date."), | |
| 170 | new ImageResourceType( | |
| 171 | 0x041D, | |
| 172 | 1053, | |
| 173 | "Alpha Identifiers. 4 bytes of length, followed by 4 bytes each for every alpha identifier."), | |
| 174 | new ImageResourceType( | |
| 175 | 0x041E, | |
| 176 | 1054, | |
| 177 | "URL List. 4 byte count of URLs, followed by 4 byte long, 4 byte ID, and unicode string for each count."), | |
| 178 | new ImageResourceType( | |
| 179 | 0x0421, | |
| 180 | 1057, | |
| 181 | "Version Info. 4 byte version, 1 byte HasRealMergedData, unicode string of writer name, unicode string of reader name, 4 bytes of file version."), | |
| 182 | new ImageResourceType( | |
| 183 | 0x07D0 - 0x0BB6, | |
| 184 | 2000 - 2998, | |
| 185 | "Path Information (saved paths). See path resource format later in this chapter."), | |
| 186 | new ImageResourceType(0x0BB7, 2999, | |
| 187 | "Name of clipping path. See path resource format later in this chapter."), | |
| 188 | new ImageResourceType( | |
| 189 | 0x2710, | |
| 190 | 10000, | |
| 191 | "Print flags information. 2 bytes version (=1), 1 byte center crop marks, 1 byte (=0), 4 bytes bleed width value, 2 bytes bleed width scale."), }; | |
| 192 | } catch (final Exception e) { | |
| 193 | Debug.debug(PsdConstants.class, e); | |
| 194 | } | |
| 195 | fImageResourceTypes = temp; | |
| 196 | } | |
| 197 | } | |
Mutations | ||
| 25 |
1.1 2.2 3.3 |
|
| 26 |
1.1 |
|
| 27 |
1.1 |
|
| 30 |
1.1 |


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Susan Granger's review of 'THE WATERBOY" (Touchstone Pictures)
Adam Sandler summarized this and his whole string of lightweight movies ("The Wedding Singer," "Billy Madison," "Happy Gilmore") when he said, "We're just having fun, and I hope everyone has fun right along with us." And there's something funny and endearing about Adam Sandler, even if his moronic movies are simply variations on each other and he always plays the nerdy, hapless hero. This time, he's a seemingly dim-witted, socially inept 31 year-old from the swamps of Louisiana who works as a lowly water boy, although he loves dispensing H2O to dehydrated athletes and truly believes that it's life's greatest calling. His over-protective mother, Kathy Bates, has home-schooled him in the bayou, so his only contact with his peers is his job, where the jocks rib him relentlessly and his coach won't let him fight back. Then, one day, he gets a new coach, Henry Winkler, who consults "The Idiot's Guide to Coaching." After years of holding in his fury, Sandler's finally allowed to release his pent-up Cajun rage, and he's suddenly transformed into the most devastating tackle on the team. Problem is: he has to go to college at the same time - behind his mother's back. And Kathy Bates is hilarious, cookin' snakes 'n' biscuits 'n' 'gators, shootin' off her mouth, and muggin' in front of the TV cameras at a game. Fairuza Balk is amusing, too, as his wacko, knife-wielding, jailbird girl-friend. Directed by Frank Coraci, written by Tim Herlihy and Adam Sandler, the comedy is primarily visual, and the zaniest bits are often at the edge of the main action - like the depressed, unkempt, bourbon-drinking cheerleaders on the loser football team. On the Granger Movie Gauge of 1 to 10, "The Waterboy" is a silly, fumbling 3, delivering a bucketful of laughs.
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|
OmniUnit
OmniUnit is a modern C++ header only library to represent physical units
|
OmniUnit is a HEADER ONLY library for modern C++.
Strongly typed values are heavily recommended by the C++ creators themself in order to avoid ambiguities and hidden bugs.
C++ stantard has taken this recommendation into account by implementing std::chrono::duration to represent duration.
It is not enough.
OmniUnit requires fully supported C++17 (at least gcc/g++ 7.2 or Visual Studio 2017 with the option /constexpr).
To get the library, clone the latest revision :
git clone http://bitbucket.org/stabax/omniunit.git
Then copy the include/omniunit folder into your project folder and simply include the desired header files in your sources, and start using the features.
See the full documentation here : http://stabax.org/doc/omniunit. If the servers are down, open omniunit/doc/html/index.html.
#include "omniunit/omniunit.hh" #include <iostream> int main() { //a and b represent 3000 meters in different ways omni::Millimeter a(3000000); omni::Kilometer b(3); omni::CentimeterPerSecond c = a / stb::second(3); //OK, LENGTH/DURATION returns a SPEED. std::cout << c.count() << '\n'; //prints 100000 omni::Gram d = c; //ERROR, this doesn't compile because "d" is of dimension MASS and "c" is of dimension SPEED omni::Inch e = omni::MilliMeter(5.2) + omni::Angstrom(124.347); //OK, all conversions are done implicitly omni::Joule kineticEnergy = 0.5 * omni::Ton(10) * omni::pow<2>(c); //OK return 0; }
/* Copyright (c) 2019, Denis Tosetto All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of Denis Tosetto nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
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@* * Copyright 2017 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import utils.ImplicitDateFormatter._ @import views.html.templates.main_template @import views.helpers.{ObligationStatusHelper} @import views.html.helpers.sidebarHelper @import views.helpers.ObligationsPage @import views.helpers.ObligationRenderHelper.renderObligations @import models.{BusinessIncome, PropertyIncome} @(bizObs: ObligationsResponseModel, propObs: ObligationsResponseModel)(implicit request: Request[_], messages: Messages, appConfig: config.AppConfig, user: auth.MtdItUser, sources: models.IncomeSourcesModel, serviceInfo: Html) @sidebar = { @sidebarHelper(ObligationsPage, sources) } @allObligationsErrored = {
@messages("obligations.error.p1")
@messages("obligations.error.p2")
} @main_template(title = messages("obligations.title"), bodyClasses = None, sidebarLinks = Some(sidebar), user = Some(user)) {@messages("obligations.info")
@renderObligations(bizObs, BusinessIncome) @renderObligations(propObs, PropertyIncome) } }


TorchDynamo Deep Dive¶
Before you read this section, read torch.compiler.
TorchDynamo is a Python-level Just-In-Time (JIT) compiler designed to make unmodified PyTorch programs faster. TorchDynamo hooks into the frame evaluation API in CPython (PEP 523) to dynamically modify Python bytecode right before it is executed. It rewrites Python bytecode to extract sequences of PyTorch operations into an FX Graph which is then compiled with a customizable backend. It creates this FX Graph through bytecode analysis and is designed to mix Python execution with compiled backends to get the best of both worlds — usability and performance.
TorchDynamo makes it easy to experiment with different compiler
backends to make PyTorch code faster with a single line decorator
torch._dynamo.optimize()
which is wrapped for convenience by torch.compile()
The following diagram demonstrates how PyTorch works with torch.compile
and without it:
TorchInductor is one of the backends supported by TorchDynamo Graph into Triton for GPUs or C++/OpenMP for CPUs. We have a training performance dashboard that provides performance comparison for different training backends. You can read more in the TorchInductor post on PyTorch dev-discuss.
For an in-depth overview, read the sections below, watch the deep-dive video, and check out the dev-discuss topics.
TorchDynamo Internals¶
Author: Jason Ansel and Kaichao You
This section will go over some of the TorchDynamo internals and will demonstrate how TorchDynamo works under the hood.
What is a guard?¶
TorchDynamo operates just-in-time and specializes graphs based on
dynamic properties. Below is a basic example of how to use TorchDynamo.
One can decorate a function or a method using torchdynamo.optimize
to enable
TorchDynamo optimization:
from typing import List
import torch
from torch import _dynamo as torchdynamo
def my_compiler(gm: torch.fx.GraphModule, example_inputs: List[torch.Tensor]):
print("my_compiler() called with FX graph:")
gm.graph.print_tabular()
return gm.forward # return a python callable
@torchdynamo.optimize(my_compiler)
def toy_example(a, b):
x = a / (torch.abs(a) + 1)
if b.sum() < 0:
b = b * -1
return x * b
for _ in range(100):
toy_example(torch.randn(10), torch.randn(10))
For example, the first graph above has the following guards:
GUARDS:
- local 'a' TENSOR_MATCH
- local 'b' TENSOR_MATCH
- global 'torch' FUNCTION_MATCH
If any of those guards fail, the graph will be recaptured and
recompiled. The interesting guard type there is TENSOR_MATCH
, which
checks the following torch.Tensor
properties:
Python class of the tensor (tensor subclassing, etc)
dtype
device
requires_grad
dispatch_key (with thread-local includes/excludes applied)
ndim
sizes*
strides*
The full specialization mode allows the backend compiler to assume an entirely static graph. Unfortunately, most backends require this. Operators which return dynamic shapes will trigger a graph break when not in dynamic shape mode.
What is Dynamo doing?¶
If you want to understand better what TorchDynamo is doing, you can set:
import torch._dynamo.config
import logging
torch._dynamo.config.log_level = logging.INFO
torch._dynamo.config.output_code = True
This code triggers useful (but spammy) printouts.
For example, the printouts for the first graph in the toy_example
are:
__compiled_fn_0 <eval_with_key>.1
opcode name target args kwargs
------------- ------- ------------------------------------------------------ ---------------- --------
placeholder a a () {}
placeholder b b () {}
call_function abs_1 <built-in method abs of type object at 0x7f9ca082f8a0> (a,) {}
call_function add <built-in function add> (abs_1, 1) {}
call_function truediv <built-in function truediv> (a, add) {}
call_method sum_1 sum (b,) {}
call_function lt <built-in function lt> (sum_1, 0) {}
output output output ((truediv, lt),) {}
ORIGINAL BYTECODE toy_example example.py 9
10 0 LOAD_FAST 0 (a)
2 LOAD_GLOBAL 0 (torch)
4 LOAD_METHOD 1 (abs)
6 LOAD_FAST 0 (a)
8 CALL_METHOD 1
10 LOAD_CONST 1 (1)
12 BINARY_ADD
14 BINARY_TRUE_DIVIDE
16 STORE_FAST 2 (x)
11 18 LOAD_FAST 1 (b)
20 LOAD_METHOD 2 (sum)
22 CALL_METHOD 0
24 LOAD_CONST 2 (0)
26 COMPARE_OP 0 (<)
28 POP_JUMP_IF_FALSE 38
12 30 LOAD_FAST 1 (b)
32 LOAD_CONST 3 (-1)
34 BINARY_MULTIPLY
36 STORE_FAST 1 (b)
13 >> 38 LOAD_FAST 2 (x)
40 LOAD_FAST 1 (b)
42 BINARY_MULTIPLY
44 RETURN_VALUE
MODIFIED BYTECODE
9 0 LOAD_GLOBAL 3 (__compiled_fn_0)
2 LOAD_FAST 0 (a)
4 LOAD_FAST 1 (b)
6 CALL_FUNCTION 2
8 UNPACK_SEQUENCE 2
10 STORE_FAST 2 (x)
12 POP_JUMP_IF_FALSE 24
14 LOAD_GLOBAL 4 (__resume_at_30_1)
16 LOAD_FAST 1 (b)
18 LOAD_FAST 2 (x)
20 CALL_FUNCTION 2
22 RETURN_VALUE
>> 24 LOAD_GLOBAL 5 (__resume_at_38_2)
26 LOAD_FAST 1 (b)
28 LOAD_FAST 2 (x)
30 CALL_FUNCTION 2
32 RETURN_VALUE
GUARDS:
- local 'a' TENSOR_MATCH
- local 'b' TENSOR_MATCH
- global 'torch' FUNCTION_MATCH
At the top you can see the FX graph. Next, you see the original bytecode of the function, followed by the modified bytecode generated by TorchDynamo. Finally, you see the guards which we covered above.
In the modified bytecode, __compiled_fn_0
is the return value of
my_compiler()
(the compiled graph). __resume_at_30_1
and
__resume_at_38_2
are both generated continuation functions that pick
up execution after a graph break (at bytecode offsets 30 and 38). Each
of these functions take the form:
__resume_at_<offset>:
... restore stack state if needed ...
JUMP_ABSOLUTE <offset> into toy_example
... original bytecode of toy_example ...
By generating this resume_at function, we force the remainder of the function to be executed in a new Python frame which recursively triggers TorchDynamo to restart its capture once execution reaches that point for the first time.
How to inspect artifacts generated by TorchDynamo?¶
To inspect the artifacts generated by TorchDynamo, there is an API torch._dynamo.eval_frame._debug_get_cache_entry_list that retrieves compiled code and guards out of a function’s __code__ object. A compiled function can have several cache entries, and each cache entry consists a generated function to check guards, and a types.CodeType object to keep the code to be executed if the guarding conditions are satisfied.
from torch._dynamo.eval_frame import _debug_get_cache_entry_list
cache_entries = _debug_get_cache_entry_list(toy_example._torchdynamo_orig_callable.__code__)
guard, code = cache_entries[0]
# the guard takes an input frame, and tells whether a re-compilation should be triggered.
import inspect
print(inspect.getfullargspec(guard))
# if you know python bytecode, you can understand the following code.
import dis
dis.dis(guard)
dis.dis(code)
The compiled bytecode, printed by dis.dis(code), will call the result of the backend compiler function which is stored inside a global variable such as __compiled_fn_0 in the module containing the original function.
The generated bytecodes are roughly equivalent to the following Python (converted manually for illustration purposes).
def compiled_example(a, b):
# behind the scene, pytorch C code checks the guarding condition
# if all guard fails, trigger re-compile
# else, run the compiled code
# after some setup work, the code finally looks like the following
x, b_sum_less_than_0 = __compiled_fn_0._torchdynamo_orig_callable(a, b)
# the condition test on tensor value leads to graph break here
# we use python interpreter to select the branch
# depending on the value, the rest graph is either `__resume_at_30_1`
# or `__resume_at_38_2`
if b_sum_less_than_0:
return __resume_at_30_1(b, x)
return __resume_at_38_2(b, x)
def __resume_at_38_2(b, x):
return x * b
def __resume_at_30_1(b, x):
b = b * -1
return x * b
def fn(a, b):
x = a / (torch.abs(a) + 1)
lt = b.sum() < 0
return x, lt
__compiled_fn_0._torchdynamo_orig_callable = fn
Note that we pass a simple my_compiler function as the backend compiler, therefore the subgraph code __resume_at_38_2, __resume_at_30_1, and __compiled_fn_0._torchdynamo_orig_callable remain python code. However, if we use other backends like the built-in inductor, the subgraph code will be compiled CUDA kernels for GPU or C++ code for CPU.


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Locked bindings get a [L]
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Note that printing a package namespace (see ns_env()
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import quandl
import pandas_datareader.data as web
import datetime
import pandas as pd
import sklearn
import numpy as np
from collections import defaultdict
from IPython.display import display
import scipy as sp
from operator import methodcaller
import time
#set reload
%reload_ext autoreload
%autoreload 1
# evaluate usage
pd.options.mode.chained_assignment = None # default='warn'
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
""""
usage of this API key is monitored
don't use this key for any other work, neither make it available on the web by any means
if you would like to access the same API for a different project,
create an account in quandl.com (it is free) and generate your own API key
"""
quandl.ApiConfig.api_key = "1513txcURR4fYyP5VDU3"
ibx50 = ['ABEV3','BBAS3','BBDC3','BBDC4','BBSE3','BRFS3','BRKM5','BRML3','BVMF3',
'CCRO3','CIEL3','CMIG4','CPFE3','CSAN3','CSNA3','CTIP3','EGIE3','EMBR3',
'ENBR3','EQTL3','ESTC3','FIBR3','GGBR4','GOAU4','HYPE3','ITSA4','ITUB4',
'JBSS3','KLBN1','KROT3','LAME4','LREN3','MRVE3','MULT3','NATU3','PCAR4',
'PETR3','PETR4','QUAL3','RADL3','RUMO3','SBSP3','SMLE3','SUZB5','UGPA3',
'USIM5','VALE3','VALE5','VIVT4','WEGE3']
Given a simple trading strategy: buy stock X, hold for N days, sell it once it reaches V% valuation. We will the optimal parameters for N (span, or number of days you hold the asset in the portfolio) and V (expected valuation before sell). For simplification, the stop loss will be optimized by the trading agent, and not used in the classification problem.
# prep data
%aimport data_transform
%aimport simulator
start_date='2002-1-1'
end_date='2014-12-31'
market_df = data_transform.download_market_data(start_date=start_date, end_date=end_date)
# do this in a grid search, simple way first, then switch to GA.
# don't have head to do GA now
# define a group of stocks in which the algorithm will be tested
stocks= ['ABEV3', 'BBDC4', 'ITUB4', 'PETR4', 'VALE5'] # represents around 25% of IBOV
# create dictionary with results
results = []
avg = lambda x:sum(x)/len(x)
for span in np.arange(1,20,1):
for profit in np.arange(.01,0.1,.005):
means = []
deviations = []
ratios = []
for symbol in stocks:
score_mean, score_std, y_ratio = data_transform.score_classifier(symbol, market_df,
start_date, end_date, span=span, profit=profit)
# print("symbol {}: {:.2f}, {:.2f}, {:.2f}".format(symbol, score_mean, score_std, y_ratio))
means.append(score_mean)
deviations.append(score_std)
ratios.append(y_ratio)
result = (span, profit, avg(means), avg(deviations), avg(ratios))
print("span {}, profit {:.3f}: mean {:.2f}, std {:.2f}, y_ratio {:.2f}".format(*result))
results.append(result)
df = pd.DataFrame(results, columns=['Span', 'Profit', 'Precision_mean', 'Precision_std', 'Y_ratio'])
df['Precision_95'] = df['Precision_mean'] - 2*df['Precision_std']
df['Profit_per_day'] = df['Profit'] / df['Span']
df.describe()
# plt.rcParams['figure.figsize']=(10,80)
sns.lmplot('Precision_95', 'Profit_per_day', data=df, fit_reg=False, scatter_kws={'alpha':0.4}, size=10)
sns.plt.xticks(np.arange(.5,1,.05))
sns.plt.yticks(np.arange(0,.11,.002))
sns.plt.xlim(.5,);
sns.plt.ylim(0,.015);
Precision decreases when profit per day increases. Yes, there are variations, but it might more due to randomness (noise) than to a pattern. Let's look at how precision is related to the y_ratio, meaning the number of times the strategy worked divided by the total number of days, If y_ratio is 50%, it means every other day the strategy would have triggered a positive return.
# plt.rcParams['figure.figsize']=(10,80)
sns.lmplot('Y_ratio', 'Profit_per_day', data=df, fit_reg=False, scatter_kws={'alpha':0.4}, size=10)
sns.plt.xticks(np.arange(0,1,.05))
sns.plt.yticks(np.arange(0,.11,.005));
# sns.plt.xlim(0,);
sns.plt.ylim(0,.1);
That is an interesting curve, although not so surprising, since the profit per day is also a log curve. Let's see how y_ratio affects precision
# plt.rcParams['figure.figsize']=(10,80)
sns.lmplot('Y_ratio', 'Precision_95', data=df, fit_reg=False, scatter_kws={'alpha':0.6}, size=10)
sns.plt.xticks(np.arange(0,1,.05))
sns.plt.yticks(np.arange(0,1,.05))
sns.plt.xlim(0,.85);
sns.plt.ylim(0,.9);
Precision increases when y_ration increses, but the sudden increase is more or less at the .2 point.
So if I pick a point with y_ratio about .3 (3 in 10), I can get aim for a Precision_95 of 80%, which is pretty high, and a profit per day of around 1%.
A profit per day of 1%, given 80% precision, should have a net return of 0.8%. That multiplied by 20 gives around a 16% return per month - pretty high, if it can be used to trade consistently.
Let's first select the optimal point and then backtest this strategy.
# how to select the optimal strategy?
# is the one with the highest precision_95 * profit_per_day
df['Net_profit'] = df['Precision_95'] * df['Profit_per_day']
df.describe()
I've calculated the mas next profit as 0.8%, and the table shows 0.83%, very close. What is this data point?
df.iloc[df['Net_profit'].idxmax()]
# That is not what I'm looking for. Because I need to consider losing money as well as getting
# What if I calculate loss?
# It will be 1-precision * profit
# That should adjust my model
df['Net_loss'] = (df['Precision_95']-1)*df['Profit_per_day']
df['Net_result'] = df['Net_profit'] + df['Net_loss']
df.describe()
# second try - maximize net result
df.iloc[df['Net_result'].argmax()]
# that is more like I was expecting. An algorithm with a 70% precision, given a 95% confidence interval.
# Span of 10 days
# Expected profit of 9%
# What if I use this parameters to play the market? How far can I get?
We will extend the model to simulate an actual scenario, where the operator have multiple stocks available. We will start by defining a set of stocks to operate. To make the comparison easier, we will only operate with the stocks belonging to the index IBV50, which contains the 50 most relevant stocks in Brazilian Market by traded volume.
%aimport data_transform
%aimport simulator
start_date='2002-1-1'
end_date='2016-12-31'
market_df = data_transform.download_market_data(start_date=start_date, end_date=end_date)
# create analysts
stocks= ['ABEV3', 'BBDC4', 'ITUB4', 'PETR4', 'VALE5'] # represents around 25% of IBOV
# top10_stocks= ['ABEV3','ITUB4','BBDC4' ,'BBAS3','ITSA4','PETR4','VALE5', 'CIEL3', 'BBSE3', 'BRFS3']
analysts = []
span = 10
profit = .09
end_date_train = '2014-12-31'
start_date_test = '2015-01-01'
for symbol in stocks:
clf, scaler, pca, score = data_transform.gen_classifier(symbol, market_df,
start_date, end_date_train, span=span, profit=profit)
# need to fix this back_test data... why 2014-06-30?
data = data_transform.prep_backtest_data(symbol, market_df,
'2014-6-30', end_date, base=60)
analysts.append(simulator.Analyst(symbol, data, clf, scaler, pca, score))
# create operator
bt_start_date = start_date_test
bt_end_date = end_date
trading_days = list(data_transform.get_stock_data('PETR4', bt_start_date, bt_end_date).index)
span = span
profit = profit
loss = -profit
scores = []
for idx in range(5):
op = simulator.Operator((span, profit, loss), analysts, capital=100000,
start_date=bt_start_date, end_date=bt_end_date, op_days=trading_days)
op.run()
scores.append(op.capital / 100000.0 - 1)
print("Span: {}, Profit: {:.2f}, Loss: {:.2f}, Return: {:.2f}".format(
span,profit,loss, sum(scores)/len(scores)))
print(op.capital)
for operation in op.operations:
operation.report()
import pandas_datareader.data as web
df = web.DataReader('^BVSP', 'yahoo', bt_start_date, bt_end_date)
df.ix[-1, 'Adj Close']/df.ix[0, 'Adj Close'] - 1
%aimport simulator
def extract_attrs(op):
return {
'symbol': op.symbol,
'price': op.price,
'qty': op.qty,
'start_date': op.start_date,
'end_date': op.end_date,
'span': op.days_left,
'gain_loss': op.gain_loss
}
operations = list(map(lambda x:extract_attrs(x), op.operations))
df_op = pd.DataFrame(operations)
df_op = df_op.set_index(['start_date'])
df_op.head()
df_op['amount'] = df_op['price'] * df_op['qty']
df_op['return'] = df_op['amount'] / 100000
df_op = df_op[df_op['amount']>1]
# plot for results
plt.rcParams['figure.figsize']=(12,6)
df_op[df_op['return']>0.1].plot(y='return')
# plot for IBOV
stocks= ['ABEV3.SA', 'BBDC4.SA', 'ITUB4.SA', 'PETR4.SA', 'VALE5.SA', '^BVSP' ]
df_plot = df_op['return']
df_plot.index.rename('date', inplace=True)
for symbol in stocks:
df_stock = web.DataReader(symbol, 'yahoo', bt_start_date, bt_end_date)
df_stock[symbol] = df_stock['Adj Close'] / df_stock.ix['2015-01-02', 'Adj Close']
df_stock = df_stock.reindex(index=df_plot.index)
df_plot = pd.concat([df_stock[symbol], df_plot], axis=1).dropna()
# colors = ["windows blue", "amber", "greyish", "faded green", "dusty purple", 'pink']
sns.palplot(sns.color_palette("colorblind", 7))
# sns.palplot(sns.xkcd_palette(colors))
sns.set(style='whitegrid')
plt.rcParams['figure.figsize']=(12,6)
df_plot.plot()
# compare variances
# plot for IBOV
stocks= ['^BVSP' ]
df_op['daily_return'] = df_op['amount'] / df_op['amount'].shift(1)
df_plot = df_op['daily_return']
df_plot.index.rename('date', inplace=True)
for symbol in stocks:
df_stock = web.DataReader(symbol, 'yahoo', bt_start_date, bt_end_date)
df_stock[symbol] = df_stock['Adj Close'] / df_stock['Adj Close'].shift(1)
df_stock = df_stock.reindex(index=df_plot.index)
df_plot = pd.concat([df_stock[symbol], df_plot], axis=1)
df_plot = df_plot.dropna();
df_plot.plot(kind='scatter', x='^BVSP', y='daily_return')
plt.vlines(1, 0.8, 1.2, color='red')
plt.hlines(1, .94, 1.06, color='red')
plt.yticks(np.arange(.8,1.2,.02));
plt.xticks(np.arange(.94,1.06,.02));
plt.xlim(df_plot['^BVSP'].min()-.01,df_plot['^BVSP'].max()+.01)
plt.ylim(df_plot['daily_return'].min()-.01,df_plot['daily_return'].max()+.01)
# draw vertical line from (70,100) to (70, 250)
# plt.plot([0, 1], [2, 1], 'k-', lw=2)
# draw diagonal line from (70, 90) to (90, 200)
# plt.plot([70, 90], [90, 200], 'k-')
import imp
plt = imp.reload(plt)
sns.distplot(df_plot['daily_return'])
plt2.xticks(np.arange(.7,1.3,0.02));
# easy - this is not daily_return, but rather a distribution of the returns
# since the strategy is to sell when it reaches 9% valuation or devaluation, it makes sense


about-me
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describe-instance-information
[--instance-information-filter-list <value>]
[--filters <value>]
[--cli-input-json <value>]
[--starting-token <value>]
[--page-size <value>]
[--max-items <value>]
[--generate-cli-skeleton <value>]
--instance-information-filter-list (list)
One or more filters. Use a filter to return a more specific list of instances.
Shorthand Syntax:
key=string,valueSet=string,string ...
JSON Syntax:
[
{
"key": "InstanceIds"|"AgentVersion"|"PingStatus"|"PlatformTypes"|"ActivationIds"|"IamRole"|"ResourceType"|"AssociationStatus",
"valueSet": ["string", ...]
}
...
]
One or more filters. Use a filter to return a more specific list of instances.
Shorthand Syntax:
Key=string,Values=string,string ...
JSON Syntax:
[
{
"Key": "string",
"Values": ["string", ...]
}
...
]
--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.
A token to specify where to start paginating. This is the next-token from a previously truncated response.
The size of each page.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a next-token will be provided in the output that you can use to resume pagination. This next-token response element should not be used directly outside of the AWS CLI.
--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.
To describe instance information
This example shows details of each of your instances.
Command:
aws ssm describe-instance-information
Output:
{
"InstanceInformationList": [
{
"IsLatestVersion": true,
"LastSuccessfulAssociationExecutionDate":<PHONE_NUMBER>.0,
"ComputerName": "ip-172-31-44-222.us-west-2.compute.internal",
"PingStatus": "Online",
"InstanceId": "i-0cb2b964d3e14fd9f",
"IPAddress": "<IP_ADDRESS>",
"AssociationStatus": "Success",
"LastAssociationExecutionDate":<PHONE_NUMBER>.0,
"ResourceType": "EC2Instance",
"AgentVersion": "2.0.672.0",
"PlatformVersion": "2016.09",
"AssociationOverview": {
"InstanceAssociationStatusAggregatedCount": {
"Success": 1
}
},
"PlatformName": "Amazon Linux AMI",
"PlatformType": "Linux",
"LastPingDateTime":<PHONE_NUMBER>.758
}
]
}
To describe information about a specific instance
This example shows details of instance i-0cb2b964d3e14fd9f.
Command:
aws ssm describe-instance-information --instance-information-filter-list "key=InstanceIds,valueSet=i-0cb2b964d3e14fd9f"
InstanceInformationList -> (list)
The instance information list.
(structure)
Describes a filter for a specific list of instances.
InstanceId -> (string)
The instance ID.PingStatus -> (string)
Connection status of the SSM agent.LastPingDateTime -> (timestamp)
The date and time when agent last pinged Systems Manager service.AgentVersion -> (string)
The version of the SSM agent running on your Linux instance.IsLatestVersion -> (boolean)
Indicates whether latest version of the SSM agent is running on your instance.PlatformType -> (string)
The operating system platform type.PlatformName -> (string)
The name of the operating system platform running on your instance.PlatformVersion -> (string)
The version of the OS platform running on your instance.ActivationId -> (string)
The activation ID created by Systems Manager when the server or VM was registered.IamRole -> (string)
The Amazon Identity and Access Management (IAM) role assigned to EC2 instances or managed instances.RegistrationDate -> (timestamp)
The date the server or VM was registered with AWS as a managed instance.ResourceType -> (string)
The type of instance. Instances are either EC2 instances or managed instances.Name -> (string)
The name of the managed instance.IPAddress -> (string)
The IP address of the managed instance.ComputerName -> (string)
The fully qualified host name of the managed instance.AssociationStatus -> (string)
The status of the association.LastAssociationExecutionDate -> (timestamp)
The date the association was last executed.LastSuccessfulAssociationExecutionDate -> (timestamp)
The last date the association was successfully run.AssociationOverview -> (structure)
Information about the association.
DetailedStatus -> (string)
Detailed status information about the aggregated associations.InstanceAssociationStatusAggregatedCount -> (map)
The number of associations for the instance(s).
key -> (string)
value -> (integer)
NextToken -> (string)
The token to use when requesting the next set of items. If there are no additional items to return, the string is empty.


SMH - THORNTON, - 1st June, 1921, at her residence, "Auburn", 55 Ebley St, Waverley, MARY ANN, widow of the late William Edward Thornton, Dearly loved mother of William, Harriett, Charles, Harold, Robert, Elizabeth, Esther, Mary, Thomas & Alice, aged 74 years. Home papers please copy.
FUNERAL - THORNTON - The rels & friends of the late Mrs. MARY ANN THORNTON are kindly invited to attend her Funeral; to leave her late residence, Auburn, 55 Ebley St, Waverley, This afternoon, at 2 o'clock, for Waverley Cemetery.
THORNTON - The rels & friends of Mr.& Mrs.H.Witt & family, Mr.& Mrs.W.Flynn & family, Mr.& Mrs.L.Nathan & family, Mr.& Mrs.W.Thornton, Mr.& Mrs.H.Thornton, Mr.& Mrs.R.Thornton & family, & of Charles, Thomas, Elizabeth & Alice Thornton, are kindly invited to attend the Funeral of their beloved Mother & Grandmother, Mary Ann Thornton to leave her residence, Ebley St, Waverley, this Thursday Afternoon, at 2 o'clock, for Waverley Cemetery.
THORNTON - The rels & friends of Mrs.Esther Chapman & family are kindly invited to attend the Funeral of her dearly loved Sister & their Aunt, Mary Ann Thornton leave residence at Waverley, this Thursday afternoon, for Waverley Cemetery.


--- layout: page title: News group: navigation weight: 40 parent: news js: news.js css: news.css permalink: /news/ published: false --- {% include navigation/news_chooser.html %} {% assign posts_collate = site.posts %}


This is a password-less application you can use to update your contact information for the LFA. We would like a non-Langara email address and mobile phone number (optional) to reach you in the unlikely event that members are unable to access the employer's email system.
There are 4 steps to the procedure which you should be able to complete in less than 10 minutes. You will need access to your Langara email, your personal email, and your mobile phone (optional).
We are currently unable to automatically validate Yahoo! email addresses. Please use another email provider if possible. If you absolutely must use a Yahoo! email address, send an email from your Yahoo! account with your mobile phone number in the subject line to<EMAIL_ADDRESS>and CC: your Langara email address and we will update it manually.


Buses to Colchester:
Buses to Wivenhoe:
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We examine infrastructure!
- maximize B2C systems
- envisioneer dynamic action-items
- enable open-source technologies
- engage wireless e-tailers
- recontextualize bricks-and-clicks partnerships
- leverage mission-critical infrastructures
- incubate enterprise technologies
- recontextualize strategic models
- recontextualize cross-platform schemas
- target enterprise niches
- brand frictionless metrics
- disintermediate out-of-the-box technologies
- deploy back-end platforms
- transition front-end vortals


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For delegators - 100% of the SBD received and 100% of the Curation rewards generated will go straight to our delegators (proportionate to the delegated amount).
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Operation Curation BotWant to join our whitelist?
We are a non-profit bot on a mission to help the community.
For delegators - 100% of the SBD received and 100% of the Curation rewards generated will go straight to our delegators (proportionate to the delegated amount).
For bidders - We operate on a unique algorithm that votes with a higher reward, thus ensuring higher profitability.
To receive a vote, the author must be whitelisted. Check out our list below!
If you'd like to delegate to Operation Curation Bot
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XMESSAGE(1) XMESSAGE(1) NAME xmessage - display a message or query in a window (X-based /bin/echo) SYNOPSIS xmessage [ -buttons label1[:value1],label2[:value2], ... ] [ options ] -file filename xmessage [ -buttons label1[:value1],label2[:value2], ... ] [ options ] message ... DESCRIPTION The xmessage program displays a window containing a message from the com‐ mand line, a file, or standard input. Along the lower edge of the mes‐ sage is row of buttons; clicking the left mouse button on any of these buttons will cause xmessage to exit. Which button was pressed is returned in the exit status and, optionally, by writing the label of the button to standard output. The program is typically used by shell scripts to display information to the user or to ask the user to make a choice. Unless a size is specified, xmessage sizes itself to fit the message, up to a maximum size. If the message is too big for the window, xmessage will display scroll bars. OPTIONS These are the command line options that xmessage understands. -buttons button,button,... This option will cause xmessage to create one button for each comma-separated button argument. The corresponding resource is buttons. Each button consists of a label optionally followed by a colon and an exit value. The label is the name of the Command button widget created and will be the default text displayed to the user. Since this is the name of the widget it may be used to change any of the resources associated with that button. The exit value will be returned by xmessage if that button is selected. The default exit value is 100 plus the button number. Buttons are numbered from the left starting with one. The default string if no -buttons option is given is okay:0. -default label Defines the button with a matching label to be the default. If not specified there is no default. The corresponding resource is defaultButton. Pressing Return anywhere in the xmessage window will activate the default button. The default button has a wider border than the others. -file filename File to display. The corresponding resource is file. A filename of `-' reads from standard input. If this option is not sup‐ plied, xmessage will display all non-option arguments in the style of echo. Either -file or a message on the command line should be provided, but not both. -print This will cause the program to write the label of the button pressed to standard output. Equivalent to setting the printValue resource to TRUE. This is one way to get feedback as to which button was pressed. -center Pop up the window at the center of the screen. Equivalent to setting the center resource to TRUE. -nearmouse Pop up the window near the mouse cursor. Equivalent to setting the nearMouse resource to TRUE. -timeout secs Exit with status 0 after secs seconds if the user has not clicked on a button yet. The corresponding resource is timeout. WIDGET HIERARCHY Knowing the name and position in the hierarchy of each widget is useful when specifying resources for them. In the following chart, the class and name of each widget is given. Xmessage (xmessage) Form form Text message Command (label1) Command (label2) . . . RESOURCES The program has a few top-level application resources that allow cus‐ tomizations that are specific to xmessage. file A String specifying the file to display. buttons A String specifying the buttons to display. See the -buttons command-line option. defaultButton A String specifying a default button by label. printValue A Boolean value specifying whether the label of the button pressed to exit the program is written to standard output. The default is FALSE. center A Boolean value specifying whether to pop up the window at the center of the screen. The default is FALSE. nearMouse A Boolean value specifying whether to pop up the window near the mouse cursor. The default is FALSE. timeout The number of seconds after which to exit with status 0. The default is 0, which means never time out. maxHeight (class Maximum) The maximum height of the text part of the window in pixels, used if no size was specified in the geometry. The default is 0, which means use 70% of the height of the screen. maxWidth (class Maximum) The maximum width of the text part of the window in pixels, used if no size was specified in the geometry. The default is 0, which means use 70% of the width of the screen. ACTIONS exit(value) exit immediately with an exit status of value (default 0). This action can be used with translations to provide alternate ways of exiting xmessage. default-exit() exit immediately with the exit status specified by the default button. If there is no default button, this action has no effect. EXIT STATUS If it detects an error, xmessage returns 1, so this value should not be used with a button. SEE ALSO X(7), echo(1), cat(1) AUTHORS Chris Peterson, MIT Project Athena Stephen Gildea, X Consortium X Version 11 xmessage 1.0.3 XMESSAGE(1)


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“Cyber bullying” is defined as a young person tormenting, threatening, harassing, or embarrassing another young person using the Internet or other technologies, like cell phones.
The psychological and emotional outcomes of cyber bullying are similar to those of real-life bullying. The difference is, real-life bullying often ends when school ends. For cyber bullying, there is no escape. And, it’s getting worse. Read on to get the facts.
- Nearly 43% of kids have been bullied online. 1 in 4 has had it happen more than once.
- 70% of students report seeing frequent bullying online.
- Over 80% of teens use a cell phone regularly, making it the most common medium for cyber bullying.
- 68% of teens agree that cyber bullying is a serious problem.
- 81% of young people think bullying online is easier to get away with than bullying in person.
- 90% of teens who have seen social-media bullying say they have ignored it. 84% have seen others tell cyber bullies to stop.
- Only 1 in 10 victims will inform a parent or trusted adult of their abuse.
- Girls are about twice as likely as boys to be victims and perpetrators of cyber bullying.
- About 58% of kids admit someone has said mean or hurtful things to them online. More than 4 out 10 say it has happened more than once.
- About 75% have visited a website bashing another student.
- Bullying victims are 2 to 9 times more likely to consider committing suicide.
Prevent Cyberbullying
- Be Aware of What Your Kids are Doing Online
- Establish Rules about Technology Use
- Understand School Rules
Be Aware of What Your Kids are Doing Online
Talk with your kids about cyberbullying and other online issues regularly.
- Know the sites your kids visit and their online activities. Ask where they’re going, what they’re doing, and who they’re doing it with.
- Tell your kids that as a responsible parent you may review their online communications if you think there is reason for concern.
Installing parental control filtering software or monitoring programs are one option for monitoring your child’s online behavior, but do not rely solely on these tools.
- Have a sense of what they do online and in texts. Learn about the sites they like. Try out the devices they use.
- Ask for their passwords, but tell them you’ll only use them in case of emergency.
- Ask to “friend” or “follow” your kids on social media sites or ask another trusted adult to do so.
- Encourage your kids to tell you immediately if they, or someone they know, is being cyberbullied. Explain that you will not take away their computers or cell phones if they confide in you about a problem they are having.
Establish Rules about Technology Use
Establish rules about appropriate use of computers, cell phones, and other technology. For example, be clear about what sites they can visit and what they are permitted to do when they’re online. Show them how to be safe online.
Help them be smart about what they post or say. Tell them not to share anything that could hurt or embarrass themselves or others. Once something is posted, it is out of their control whether someone else will forward it.
Encourage kids to think about who they want to see the information and pictures they post online. Should complete strangers see it? Real friends only? Friends of friends? Think about how people who aren’t friends could use it.
Tell kids to keep their passwords safe and not share them with friends. Sharing passwords can compromise their control over their online identities and activities.
Understand School Rules
Some schools have developed policies on uses of technology that may affect the child’s online behavior in and out of the classroom. Ask the school if they have developed a policy.
Report Cyberbullying
When cyberbullying happens, it is important to document and report the behavior so it can be addressed.
- Steps to Take Immediately
- Report Cyberbullying to Online Service Providers
- Report Cyberbullying to Law Enforcement
- Report Cyberbullying to Schools
Steps to Take Immediately
- Don’t respond to and don’t forward cyberbullying messages.
- Keep evidence of cyberbullying. Record the dates, times, and descriptions of instances when cyberbullying has occurred. Save and print screenshots, emails, and text messages. Use this evidence to report cyberbullying to web and cell phone service providers.
- Block the person who is cyberbullying.
Report Cyberbullying to Online Service Providers
Cyberbullying often violates the terms of service established by social media sites and internet service providers.
- Review their terms and conditions or rights and responsibilities sections. These describe content that is or is not appropriate.
- Visit social media safety centers to learn how to block users and change settings to control who can contact you.
- Report cyberbullying to the social media site so they can take action against users abusing the terms of service.
Report Cyberbullying to Law Enforcement
When cyberbullying involves these activities it is considered a crime and should be reported to law enforcement:
- Threats of violence
- Child pornography or sending sexually explicit messages or photos
- Taking a photo or video of someone in a place where he or she would expect privacy
- Stalking and hate crimes
Some states consider other forms of cyberbullying criminal. Consult your state’s laws and law enforcement for additional guidance.
Report Cyberbullying to Schools
- Cyberbullying can create a disruptive environment at school and is often related to in-person bullying. The school can use the information to help inform prevention and response strategies.
- In many states, schools are required to address cyberbullying in their anti-bullying policy. Some state laws also cover off-campus behavior that creates a hostile school environment.


Remember that hackathons are like marathons. Some people go to compete but most people take part to better themselves and have fun. Whatever the reason is you're at a hackathon, make sure you're upholding the hacker spirit by collaborating with other teams, helping beginners, and having fun.
After hacking finishes, teams will show their projects each other and to the judges. You are required to present a demo of what you have built if you want to be considered for a prize. Pitches or presentations are discouraged. You are not judged on the quality of your pitch or the quality of your idea. As you are judged on what you built. You are encouraged to present what you have done even if your hack is broken or you weren’t able to finish. It's okay if you didn't finish your hack—that happens all the time! Completion is only one part of the judging criteria, so you might still do well. Also, demoing is not just about the competition. It's a chance to share with others what you learned and what you tried to build—that's what hacking's all about! For being courageous enough to demo, you'll receive a special MLH "I Demoed" sticker—it doesn't matter how good the demo is! In the case that you don't have anything to demo, you can give a presentation about what you tried and what you learned. Hearing what other people learned is interesting and inspiring for other attendees.
All hacks submitted for demos will be submitted through Devpost
When submitting your hack for judging you must choose which category you want to be entered into based on the composition of your project.
We will also have honorable mention prizes and prizes for other criteria at the judge’s discretion.
Teams will be judged on these four criteria. Judges will weigh the criteria equally. During judging, participants should try to describe what they did for each criterion in their project.
These criteria will guide judges but ultimately judges are free to make decisions based on their gut feeling of which projects are the most impressive and most deserving.
It's important to note that these judging criteria do not include:
So don't worry about coming up with the next big idea or building the next Facebook. You'll have plenty of time for that outside the hackathon. just focus on learning, having fun, and making new friends. At the end of the day the skills you learn and the friends you make might lead to the next big thing—but you don't have to do that to win a hackathon. Remember! The competition is just a part of the hackathon. To make the most out of the event, try something new, teach other people, and make new friends!
Happy Hacking from the MLH team and HackTheOzarks!


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