Rules: At the Double, Forward to Victory, Inspiring Presence
Selections: 3. Battle Fury, 3. Teardrop of Grungni, General
Categories: DUARDIN, HERO, PRIEST, RUNELORD, DISPOSSESSED, ORDER, Leader, General
Artefact: Teardrop of Grungni, Command Trait: Battle Fury, Unit: Runelord, Unit Abilities: Rune Lore, Runes of Spellbreaking, Weapon: Forgehammer, Rune Staff
| Artefact | Artefact Details | Ref |
|---|---|---|
| Teardrop of Grungni | Once per battle, at the start of your shooting phase, pick 1 enemy unit within 6" of the bearer. That unit suffers D3 mortal wounds. In addition, if the target is a HERO or MONSTER, it must halve its Move characteristic in its next movement phase. |
| Command Trait | Command Trait Details | Ref |
|---|---|---|
| Battle Fury | Roll a dice after this general completes their attacks in the combat phase; on a 6 they can pile in and attack for a second time (do not roll again after resolving the second set of attacks). |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Runelord | 4" | 5 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Rune Lore | In your hero phase a Runelord can pray to the Ancestor Gods to imbue his allies’ weapons and armour with power. If he does so, pick a DISPOSSESSED unit within 16", select a power and roll a dice; on a 1 the Runelord has failed and nothing happens. On a roll of 2 or more the runes hammered into his allies’ wargear glow white-hot with rune magic and the power takes effect. A unit that is affected by a Rune Lore power cannot be picked again in the same phase. Ancestral Shield: Until your next hero phase, you can roll a dice whenever a model in this unit suffers a wound or a mortal wound. On a 6, that wound or mortal wound is ignored. Forgefire: Until your next hero phase, increase the Rend characteristics of the unit’s weapons by 1 (i.e. ‘-’ becomes -1, -1 becomes -2 and so on). | Order Official FAQs and errata, Version 1.4 p1 |
| Runes of Spellbreaking | A Runelord can attempt to unbind one enemy spell in the enemy hero phase as if he were a wizard. You can add 2 to any unbinding rolls for a Runelord. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Forgehammer | Melee | 1" | 2 | 4+ | 4+ | - | 1 | |
| Rune Staff | Melee | 1" | 1 | 4+ | 3+ | - | D3 |
Selections: 3. Teardrop of Grungni
Categories: DUARDIN, HERO, UNFORGED, DISPOSSESSED, ORDER, Leader
Artefact: Teardrop of Grungni, Unit: Unforged, Unit Abilities: Epic Deathblow, Nemesis, Runic Axes, The Bigger They Are..., Weapon: Runic Axes
| Artefact | Artefact Details | Ref |
|---|---|---|
| Teardrop of Grungni | Once per battle, at the start of your shooting phase, pick 1 enemy unit within 6" of the bearer. That unit suffers D3 mortal wounds. In addition, if the target is a HERO or MONSTER, it must halve its Move characteristic in its next movement phase. |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Unforged | 4" | 5 | 10 | 6+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Epic Deathblow | If an Unforged is slain in the combat phase, roll a dice before it is removed. On a roll of 4 or more, you can inflict D3 mortal wounds on the enemy unit that struck the fatal blow (inflict D6 mortal wounds instead if a CHAOS model struck the final blow). | |
| Nemesis | Attacks made by an Unforged inflict double Damage against CHAOS units. | |
| Runic Axes | The Unforged launches a deadly flurry of blows. You can re-roll all hit rolls of 1 for an Unforged. | |
| The Bigger They Are... | You can add 1 to any wound rolls for an Unforged if the target of the attack has a Wounds characteristic of more than 1. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Runic Axes | Melee | 1" | 6 | 3+ | 3+ | -1 | 1 |
Selections: 1. Heavy Metal Ingot
Categories: DUARDIN, HERO, UNFORGED, DISPOSSESSED, ORDER, Leader
Artefact: Heavy Metal Ingot, Unit: Unforged, Unit Abilities: Epic Deathblow, Nemesis, Runic Axes, The Bigger They Are..., Weapon: Runic Axes
| Artefact | Artefact Details | Ref |
|---|---|---|
| Heavy Metal Ingot | You can re-roll failed save rolls for attacks that target the bearer if the bearer has not made a move in the same turn. |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Unforged | 4" | 5 | 10 | 6+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Epic Deathblow | If an Unforged is slain in the combat phase, roll a dice before it is removed. On a roll of 4 or more, you can inflict D3 mortal wounds on the enemy unit that struck the fatal blow (inflict D6 mortal wounds instead if a CHAOS model struck the final blow). | |
| Nemesis | Attacks made by an Unforged inflict double Damage against CHAOS units. | |
| Runic Axes | The Unforged launches a deadly flurry of blows. You can re-roll all hit rolls of 1 for an Unforged. | |
| The Bigger They Are... | You can add 1 to any wound rolls for an Unforged if the target of the attack has a Wounds characteristic of more than 1. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Runic Axes | Melee | 1" | 6 | 3+ | 3+ | -1 | 1 |
Categories: DUARDIN, HERO, WARDEN KING, DISPOSSESSED, ORDER, Leader
Command Abilities: Ancestral Grudge, Unit: Warden King, Unit Abilities: Ancestor Shield, Oath Stone, Weapon: Rune Weapon
| Command Abilities | Command Ability Details | Ref |
|---|---|---|
| Ancestral Grudge | If a Warden King uses this ability, pick one enemy unit within 16". Until your next hero phase, you can add 1 to wound rolls for all attacks made by DISPOSSESSED models that target that unit. The same unit cannot be picked as the target of this command ability more than once in the same phase, | Grand Alliance: Order Errata, June 2018 |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Warden King | 4" | 5 | 8 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Ancestor Shield | You can re-roll all failed saves for a Warden King. | |
| Oath Stone | In the hero phase, a Warden King can stand atop his oath stone to increase the resolve of his followers. If he does so, he cannot move until his next hero phase, but all DISPOSSESSED units from your army within 18" in the battleshock phase may use the Warden King’s Bravery instead of their own. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Rune Weapon | Melee | 1" | 4 | 3+ | 3+ | -1 | D3 |
Selections: 6. Resounding Gromrilhorn
Categories: DUARDIN, HERO, WARDEN KING, DISPOSSESSED, ORDER, Leader
Artefact: Resounding Gromrilhorn, Command Abilities: Ancestral Grudge, Unit: Warden King, Unit Abilities: Ancestor Shield, Oath Stone, Weapon: Rune Weapon
| Artefact | Artefact Details | Ref |
|---|---|---|
| Resounding Gromrilhorn | Once per battle, at the start of your hero phase, the bearer can use this artefact. If they do so, add 2 to the Bravery characteristic of friendly DISPOSSESSED units until your next hero phase. |
| Command Abilities | Command Ability Details | Ref |
|---|---|---|
| Ancestral Grudge | If a Warden King uses this ability, pick one enemy unit within 16". Until your next hero phase, you can add 1 to wound rolls for all attacks made by DISPOSSESSED models that target that unit. The same unit cannot be picked as the target of this command ability more than once in the same phase, | Grand Alliance: Order Errata, June 2018 |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Warden King | 4" | 5 | 8 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Ancestor Shield | You can re-roll all failed saves for a Warden King. | |
| Oath Stone | In the hero phase, a Warden King can stand atop his oath stone to increase the resolve of his followers. If he does so, he cannot move until his next hero phase, but all DISPOSSESSED units from your army within 18" in the battleshock phase may use the Warden King’s Bravery instead of their own. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Rune Weapon | Melee | 1" | 4 | 3+ | 3+ | -1 | D3 |
Selections: 5. Piledriver Gauntlets
Categories: DUARDIN, HERO, WARDEN KING, DISPOSSESSED, ORDER, Leader
Artefact: Piledriver Gauntlets, Command Abilities: Ancestral Grudge, Unit: Warden King, Unit Abilities: Ancestor Shield, Oath Stone, Weapon: Rune Weapon
| Artefact | Artefact Details | Ref |
|---|---|---|
| Piledriver Gauntlets | At the start of the combat phase, you can declare that the bearer will strike the ground instead of attacking. If you do so, until the end of that combat phase subtract 1 from hit rolls for attacks made by enemy models that are within 6" of the bearer. |
| Command Abilities | Command Ability Details | Ref |
|---|---|---|
| Ancestral Grudge | If a Warden King uses this ability, pick one enemy unit within 16". Until your next hero phase, you can add 1 to wound rolls for all attacks made by DISPOSSESSED models that target that unit. The same unit cannot be picked as the target of this command ability more than once in the same phase, | Grand Alliance: Order Errata, June 2018 |
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Warden King | 4" | 5 | 8 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Ancestor Shield | You can re-roll all failed saves for a Warden King. | |
| Oath Stone | In the hero phase, a Warden King can stand atop his oath stone to increase the resolve of his followers. If he does so, he cannot move until his next hero phase, but all DISPOSSESSED units from your army within 18" in the battleshock phase may use the Warden King’s Bravery instead of their own. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Rune Weapon | Melee | 1" | 4 | 3+ | 3+ | -1 | D3 |
Selections: 10 Hammerers [140pts]
Categories: DUARDIN, HAMMERERS, DISPOSSESSED, ORDER, Battleline
Unit: Hammerers, Unit Abilities: Keeper of the Gate, Kingsguard, Weapon: Gromril Great Hammer
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Hammerers | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Keeper of the Gate | The leader of this unit is the Keeper of the Gate. A Keeper of the Gate makes 3 attacks rather than 2. | |
| Kingsguard | You do not need to take battleshock tests for this unit if it is within 16" of a DISPOSSESSED HERO from your army in the battleshock phase. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Gromril Great Hammer | Melee | 1" | 2 | 3+ | 3+ | -1 | 1 |
Selections: 10 Ironbreakers [140pts]
Categories: DUARDIN, IRONBREAKERS, DISPOSSESSED, ORDER, Battleline
Unit: Ironbreakers, Unit Abilities: Forge-proven Gromril Armour, Ironbeard, Weapon: Drakefire Pistol, Drakefire Pistol (Melee), Ironbreaker Axe or Hammer
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Ironbreakers | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Forge-proven Gromril Armour | When you make save rolls for this unit, ignore the enemy's Rend characteristic unless it is -2 or better. | |
| Ironbeard | The leader of this unit is an Ironbeard. An Ironbeard makes 3 attacks with an Ironbreaker Axe or Hammer instead of 2. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Drakefire Pistol | Missile | 8" | 1 | 4+ | 3+ | -1 | 1 | |
| Drakefire Pistol (Melee) | Melee | 1" | 1 | 4+ | 4+ | - | 1 | |
| Ironbreaker Axe or Hammer | Melee | 1" | 2 | 3+ | 4+ | - | 1 |
Selections: 10 Ironbreakers [140pts]
Categories: DUARDIN, IRONBREAKERS, DISPOSSESSED, ORDER, Battleline
Unit: Ironbreakers, Unit Abilities: Forge-proven Gromril Armour, Ironbeard, Weapon: Drakefire Pistol, Drakefire Pistol (Melee), Ironbreaker Axe or Hammer
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Ironbreakers | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Forge-proven Gromril Armour | When you make save rolls for this unit, ignore the enemy's Rend characteristic unless it is -2 or better. | |
| Ironbeard | The leader of this unit is an Ironbeard. An Ironbeard makes 3 attacks with an Ironbreaker Axe or Hammer instead of 2. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Drakefire Pistol | Missile | 8" | 1 | 4+ | 3+ | -1 | 1 | |
| Drakefire Pistol (Melee) | Melee | 1" | 1 | 4+ | 4+ | - | 1 | |
| Ironbreaker Axe or Hammer | Melee | 1" | 2 | 3+ | 4+ | - | 1 |
Selections: 10 Longbeards [100pts]
Categories: DUARDIN, LONGBEARDS, DISPOSSESSED, ORDER, Battleline
Unit: Longbeards, Unit Abilities: Old Grumblers
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Longbeards | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Old Grumblers | In your hero phase, this unit will complain about something in a suitably duardin manner. When they do so, pick one of the grumbling listed. This affect lasts until your next hero phase. 'I thought duardin were made of sterner stuff': Roll a dice each time a DISPOSSESSED model from your army flees whilst within 8" of this unit; on a 5 or more that model stands firm under the Longbeards' stern gaze and does not flee. 'Who does this beardling think he is?': Friendly Dispossessed Heroes within 8" of this unit are treated as if they were your general when working out the range of command abilities. 'Grots are weedier these days!': You can re-roll wound rolls of 1 for DISPOSSESSED models from your army that are within 8" of this unit when they attack in the combat phase. | Grand Alliance: Order Errata, June 2018 |
Selections: 10 Warriors [90pts]
Categories: DUARDIN, WARRIORS, DISPOSSESSED, ORDER, Battleline
Unit: Warriors, Unit Abilities: Resolute in Defence, Veteran
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Warriors | 4" | 1 | 6 | 5+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Resolute in Defence | You can re-roll failed wound rolls of 1 when attacking with a Warrior in your opponent’s combat phase. You can instead re-roll all failed wound rolls for a Warrior if its unit has 20 or more models when it attacks in your opponent’s combat phase. | |
| Veteran | The leader of this unit is the Veteran. A Veteran makes 2 attacks rather than 1. |
Selections: 10 Ironbreakers [140pts]
Categories: DUARDIN, IRONBREAKERS, DISPOSSESSED, ORDER, Other
Unit: Ironbreakers, Unit Abilities: Forge-proven Gromril Armour, Ironbeard, Weapon: Drakefire Pistol, Drakefire Pistol (Melee), Ironbreaker Axe or Hammer
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Ironbreakers | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Forge-proven Gromril Armour | When you make save rolls for this unit, ignore the enemy's Rend characteristic unless it is -2 or better. | |
| Ironbeard | The leader of this unit is an Ironbeard. An Ironbeard makes 3 attacks with an Ironbreaker Axe or Hammer instead of 2. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Drakefire Pistol | Missile | 8" | 1 | 4+ | 3+ | -1 | 1 | |
| Drakefire Pistol (Melee) | Melee | 1" | 1 | 4+ | 4+ | - | 1 | |
| Ironbreaker Axe or Hammer | Melee | 1" | 2 | 3+ | 4+ | - | 1 |
Selections: 10 Irondrakes [180pts]
Categories: DUARDIN, IRONDRAKES, DISPOSSESSED, ORDER, Other
Unit: Irondrakes, Unit Abilities: Blaze Away, Forge-proven Gromril Armour, Ironwarden, Weapon: Drakefire Pistol, Drakefire Pistol (Melee), Drakeguns, Mailed Fist
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Irondrakes | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Blaze Away | You can add 1 to the Attacks characteristic of this unit’s missile weapons if it has at least 10 models and is more than 3" from of any enemy units. | Grand Alliance: Order Errata, June 2018 |
| Forge-proven Gromril Armour | When you make save rolls for this unit, ignore the enemy's Rend characteristic unless it is -2 or better. | |
| Ironwarden | The leader of this unit is an Ironwarden. You can add 1 to the hit rolls for an Ironwarden shooting a Drakegun. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Drakefire Pistol | Missile | 8" | 1 | 4+ | 3+ | -1 | 1 | |
| Drakefire Pistol (Melee) | Melee | 1" | 1 | 4+ | 4+ | - | 1 | |
| Drakeguns | Missile | 16" | 1 | 3+ | 3+ | -1 | 1 | |
| Mailed Fist | Melee | 1" | 1 | 4+ | 5+ | - | 1 |
Selections: 10 Irondrakes [180pts]
Categories: DUARDIN, IRONDRAKES, DISPOSSESSED, ORDER, Other
Unit: Irondrakes, Unit Abilities: Blaze Away, Forge-proven Gromril Armour, Ironwarden, Weapon: Drakefire Pistol, Drakefire Pistol (Melee), Drakeguns, Mailed Fist
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Irondrakes | 4" | 1 | 7 | 4+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Blaze Away | You can add 1 to the Attacks characteristic of this unit’s missile weapons if it has at least 10 models and is more than 3" from of any enemy units. | Grand Alliance: Order Errata, June 2018 |
| Forge-proven Gromril Armour | When you make save rolls for this unit, ignore the enemy's Rend characteristic unless it is -2 or better. | |
| Ironwarden | The leader of this unit is an Ironwarden. You can add 1 to the hit rolls for an Ironwarden shooting a Drakegun. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Drakefire Pistol | Missile | 8" | 1 | 4+ | 3+ | -1 | 1 | |
| Drakefire Pistol (Melee) | Melee | 1" | 1 | 4+ | 4+ | - | 1 | |
| Drakeguns | Missile | 16" | 1 | 3+ | 3+ | -1 | 1 | |
| Mailed Fist | Melee | 1" | 1 | 4+ | 5+ | - | 1 |
Selections: 10 Quarellers [120pts]
Categories: DUARDIN, QUARRELLERS, DISPOSSESSED, ORDER, Other
Unit: Quarrellers, Unit Abilities: Veteran, Volley Fire, Weapon: Duardin Crossbow, Ranger's Axe
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Quarrellers | 4" | 1 | 6 | 5+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Veteran | The leader of this unit is the Veteran. You can add 1 to hit rolls for a Veteran when he fires his Duardin Crossbow. | |
| Volley Fire | You can add 1 to the Attacks characteristic of this unit’s missile weapons if it has at least 20 models and is more than 3" from any enemy units. | Grand Alliance: Order Errata, June 2018 |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Duardin Crossbow | Missile | 20" | 1 | 4+ | 4+ | - | 1 | |
| Ranger's Axe | Melee | 1" | 1 | 4+ | 4+ | - | 1 |
Selections: 10 Quarellers [120pts]
Categories: DUARDIN, QUARRELLERS, DISPOSSESSED, ORDER, Other
Unit: Quarrellers, Unit Abilities: Veteran, Volley Fire, Weapon: Duardin Crossbow, Ranger's Axe
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Quarrellers | 4" | 1 | 6 | 5+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Veteran | The leader of this unit is the Veteran. You can add 1 to hit rolls for a Veteran when he fires his Duardin Crossbow. | |
| Volley Fire | You can add 1 to the Attacks characteristic of this unit’s missile weapons if it has at least 20 models and is more than 3" from any enemy units. | Grand Alliance: Order Errata, June 2018 |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Duardin Crossbow | Missile | 20" | 1 | 4+ | 4+ | - | 1 | |
| Ranger's Axe | Melee | 1" | 1 | 4+ | 4+ | - | 1 |
Selections: 10 Thunderers [120pts]
Categories: DUARDIN, THUNDERERS, DISPOSSESSED, ORDER, Other
Unit: Thunderers, Unit Abilities: Precision Fire, Veteran, Weapon: Duardin Handgun, Duardin Handgun (Melee)
| Unit | Move | Wounds | Bravery | Save | Ref |
|---|---|---|---|---|---|
| Thunderers | 4" | 1 | 6 | 5+ |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Precision Fire | You can add 1 to all hit rolls for a Thunderer if its unit has 20 or more models and there are no enemy models within 3". | |
| Veteran | The leader of this unit is the Veteran. You can add 1 to hit rolls for a Veteran when he fires a Duardin Handgun. |
| Weapon | Type | Range | Attacks | To Hit | To Wound | Rend | Damage | Ref |
|---|---|---|---|---|---|---|---|---|
| Duardin Handgun | Missile | 16" | 1 | 4+ | 3+ | -1 | 1 | |
| Duardin Handgun (Melee) | Melee | 1" | 1 | 4+ | 5+ | - | 1 |
Categories: Battalion
Battalion Abilities: Ancient Grudges, Stubborn to the End
| Battalion Abilities | Battalion Ability Details | Ref |
|---|---|---|
| Ancient Grudges | You can re-roll all hit rolls of 1 for models in a Grudgebound War Throng. | |
| Stubborn to the End | If you roll a 1, 2 or 3 when taking a battleshock test for a unit in a Grudgebound War Throng, that unit stubbornly refuses to yield and is treated as having passed the battleshock test irrespective of any penalties on their Bravery or the number of casualties they have suffered that turn. |
Categories: Battalion
Battalion Abilities: Ancient Grudges, Stubborn to the End
| Battalion Abilities | Battalion Ability Details | Ref |
|---|---|---|
| Ancient Grudges | You can re-roll all hit rolls of 1 for models in a Grudgebound War Throng. | |
| Stubborn to the End | If you roll a 1, 2 or 3 when taking a battleshock test for a unit in a Grudgebound War Throng, that unit stubbornly refuses to yield and is treated as having passed the battleshock test irrespective of any penalties on their Bravery or the number of casualties they have suffered that turn. |
Selections: Allegiance: Dispossessed
Categories: Allegiance
Battle Trait: Grudgebound, Stubborn to the End
| Battle Trait | Battle Trait Details | Ref |
|---|---|---|
| Grudgebound | After set-up is complete, but before the battle begins, choose or roll for a grudge from the table. The rules for that grudge apply to all friendly DISPOSSESSED units for the duration of the battle. | |
| Stubborn to the End | If the unmodified roll for a battleshock test for a friendly DISPOSSESSED unit is 1, 2 or 3, that unit is treated as having passed the battleshock test irrespective of any modifiers to the battleshock test or their Bravery characteristic. |
Selections: Allegiance: Dispossessed
Categories: Allegiance
Battle Trait: Grudgebound, Stubborn to the End
| Battle Trait | Battle Trait Details | Ref |
|---|---|---|
| Grudgebound | After set-up is complete, but before the battle begins, choose or roll for a grudge from the table. The rules for that grudge apply to all friendly DISPOSSESSED units for the duration of the battle. | |
| Stubborn to the End | If the unmodified roll for a battleshock test for a friendly DISPOSSESSED unit is 1, 2 or 3, that unit is treated as having passed the battleshock test irrespective of any modifiers to the battleshock test or their Bravery characteristic. |
Selections: 2000 Points - Battlehost
Categories: Game Options, Battlehost
Categories: ENDLESS SPELL, AZYR, CHRONOMANTIC COGS, Malign Sorcery
Spell: Summon Chronomatic Cogs, Unit Abilities: Mechanisms of Time
| Spell | Casting Value | Description | Ref |
|---|---|---|---|
| Summon Chronomatic Cogs | 7 | If successfully cast, set up a Chronomantic Cogs model wholly within 12" of the caster. |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Mechanisms of Time | In their controlling player’s hero phase, a single Wizard within 9" of this model may manipulate the cogs to increase or decrease the flow of time. They may do this in the same phase as the Chronomantic Cogs are set up. If they do so, choose one of the effects opposite. The effect lasts until their next hero phase, or until an enemy Wizard chooses to manipulate the cogs. Speed Up Time: Add 2" to the Move characteristic of all units on the battlefield. In addition, add 2 to charge rolls for all units on the battlefield. Slow Down Time: The wizard manipulating the cogs can cast 1 additional spell in this hero phase. In addition, re-roll failed save rolls for that wizard. |
Categories: ENDLESS SPELL, HYSH, PRISMATIC PALISADE, Malign Sorcery
Spell: Summon Prismatic Palisade, Unit Abilities: Blinding Light, Dazzling Brilliance, Empowered by Hysh
| Spell | Casting Value | Description | Ref |
|---|---|---|---|
| Summon Prismatic Palisade | 5 | If successfully cast, set up a Prismatic Palisade model wholly within 18" of the caster. |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Blinding Light | At the start of each turn, roll a dice for each unit within 6" of this model. On a 5+ subtract 1 from hit rolls for attacks made by that unit until the end of the turn. | |
| Dazzling Brilliance | A model cannot see another model if an imaginary straight line, 1mm wide, drawn from the centre of its base to the centre of the other model’s base passes over this model. | |
| Empowered by Hysh | If your battle is taking place in the Realm of Light, add 1 to rolls made to determine if a unit is affected by this model’s Blinding Light ability. |
Categories: ENDLESS SPELL, SOULSCREAM BRIDGE, SHYISH, Malign Sorcery
Spell: Summon Soulscream Bridge, Unit Abilities: Deathly Passage, Empowered by Shyish, Nightmarish Construct
| Spell | Casting Value | Description | Ref |
|---|---|---|---|
| Summon Soulscream Bridge | 6 | If successfully cast, set up the first Soulscream Bridge model wholly within 6" of the caster, and then set up the second Soulscream Bridge model wholly within 12" of the first. |
| Unit Abilities | Ability Details | Ref |
|---|---|---|
| Deathly Passage | At the start of your movement phase, friendly units wholly within 6" of one Soulscream Bridge model from this endless spell can travel across the Soulscream Bridge. If they do so, remove that unit from the battlefield and set it up again wholly within 6" of the other Soulscream Bridge model from this endless spell, more than 9" from any enemy units. That unit cannot make a normal move that phase. | |
| Empowered by Shyish | If your battle is taking place in the Realm of Death, the second Soulscream Bridge model can be set up wholly within 24" of the first, instead of within 12" of the first. | |
| Nightmarish Construct | Subtract 1 from the Bravery characteristic of enemy units while they are within 6" of a Soulscream Bridge model. This ability has no effect on DEATH units. |
Selections: Battle: Ghur
Categories: Realm of Battle
Spell: Bestial Spirit, Cower, Flock of Doom, Impenetrable Hide, Primal Hunter, The Amber Spear
| Spell | Casting Value | Description | Ref |
|---|---|---|---|
| Bestial Spirit | 6 | If successfully cast, pick an enemy unit within 18" of the caster that is visible to them. That unit suffers D3 mortal wounds. In addition, if the unit suffers 3 mortal wounds from this spell, subtract 1 from its Bravery characteristic until your next hero phase. | Malign Sorcery p73 |
| Cower | 6 | If successfully cast, pick an enemy MONSTER within 12" of the caster that is visible to them and roll 2D6. If the result is higher than that MONSTER ’s Bravery characteristic, it cannot make a charge move in your opponent’s next turn. | Malign Sorcery p73 |
| Flock of Doom | 6 | If successfully cast, pick an enemy unit within 18" of the caster that is visible to them and roll 12 dice. For each 6+ that enemy unit suffers 1 mortal wound. | Malign Sorcery p73 |
| Impenetrable Hide | 6 | If successfully cast, you can re-roll failed save rolls for the caster until the start of your next hero phase. | Malign Sorcery p73 |
| Primal Hunter | 8 | If successfully cast, pick a friendly HERO within 12" of the caster that is visible to them. Re-roll failed charge rolls and hit rolls for that HERO until your next hero phase. | Malign Sorcery p73 |
| The Amber Spear | 6 | If successfully cast, pick a point on the battlefield within 12" of the caster that is visible to them and draw an imaginary straight line 1mm wide between that point and the closest part of the caster. Each unit other than the caster that has models passed across by this line suffers 1 mortal wound. | Malign Sorcery p73 |
At the Double: You can use this command ability after you make a run roll for a friendly unit that is within 6" of a friendly HERO, or 12" of a friendly HERO that is a general.  (Core Rules p3)
Forward to Victory: You can use this command ability after you make a charge roll for a friendly unit that is within 6" of a friendly HERO, or 12" of a friendly HERO that is a general. If you do so, re-roll the charge roll. (Core Rules p3)
Inspiring Presence: You can use this command ability at the start of the battleshock phase. If you do so, pick a friendly unit that is within 6" of friendly HERO, or 12" of a friendly HERO that is a general. That unit does not have to take battleshock tests in that phase. (Core Rules p3)
Created with BattleScribe


| unsigned int PVR_Texture_Header::dwAlphaBitMask |
| unsigned int PVR_Texture_Header::dwBBitMask |
| unsigned int PVR_Texture_Header::dwBitCount |
| unsigned int PVR_Texture_Header::dwGBitMask |
| unsigned int PVR_Texture_Header::dwHeaderSize |
| unsigned int PVR_Texture_Header::dwHeight |
height of surface to be created
| unsigned int PVR_Texture_Header::dwMipMapCount |
number of mip-map levels requested
| unsigned int PVR_Texture_Header::dwNumSurfs |
the number of surfaces present in the pvr
| unsigned int PVR_Texture_Header::dwpfFlags |
| unsigned int PVR_Texture_Header::dwPVR |
magic number identifying pvr file
| unsigned int PVR_Texture_Header::dwRBitMask |
| unsigned int PVR_Texture_Header::dwTextureDataSize |
| unsigned int PVR_Texture_Header::dwWidth |
此結構(structure) 文件是由下列檔案中產生:
- C:/innovation/GovernmentEngine/EpicForceEngine/MagnumEngineLib/MagnumCore/PVRTexLoad.h


I have been working at Cyngn Inc. for that past 1 and half years as a perception software engieer on various projects revolving around Computer Vision.
I did my Master's in Computer Vision at Carnegie Mellon University. My passion for Computer Vision started when I was introduced to classical Image Processing techniques during my undergraduate sophomore. Starting from then, I have constantly involved myself in many pet projects and real projects!
I did my undergraduate junior year internship at Texas Instruments, Bangalore, India. It was the first true transition into pure Computer Vision. I got introduced to multi-view geometry by Zisserman which is one book that I cherish! I got to develop an algorithm to segment the road in street scenes. I used homography with modification which I published and patented.
Besides my technical indulgences, I enjoy playing tennis and landspace photography.
Company: Samsung Research America
Lab: Think Tank Team
Location: Mountain View, CA
role: Intern
My project was focused on developing dataset and network for estimating human pose from an untraditional sensor. From a high-level perspective, I developed domain adaptation algorithms to leverage existing data. I also developed pose estimation network and trained the same.
Company: Texas Instruments
Team: ADAS SW
Location: Bangalore, India
role: Intern
My task was to detect ground plane from monocular images. I used homography as a tool for plane detection. I improved the technique by making the ground plane the dominant plane by developing an algorithm that chooses an ROI where the dominant plane is the ground plane. Since the motion is not exactly a rotation, the algorithm takes care of patches on the road such as the lane markings.
role: author
Replicated the papers Is object localization for free? and WSDDN for understanding weak supervision based object detection
role: author
Worked on reconstructing intersection from a single stationary camera using a combination of Deep Learning techniques, non-linear optimization and tracking
role: author
Implemented Inverse Compositional Lucas Kanade algorithm with basis to perform object tracking.
role: author
Created a tool to perform background blur, background replacement using stereo images or consecutive images in video.
role: author
Intelligent Inpainting is a Computer Vision application developed in C++. It takes a single image and a user click. The click is intented to select a person on the input image. Then the application intelligently crops that person out of the image by filling with the background.
role: author
Developed a SfM application in C++ from scratch. The project provided good opportunity to understand multi-view geometry.
role: author
An android application that uses camera to search for sudoku in its view and solves it upon detecting one.
role: author
Trion the shape shifting alien has fallen from his spaceship. Help him get back to the ship by swiping your way around the galaxy. Try and keep him within the screen. If he falls out of the screen, he's dead. So swipe wisely!!! And have fun.!
role: author
This project is focused on developing an algorithm that quickly adapts to a dynamic environment with sparse reward structure. While a sparse reward environment is a quite challenging setting, a combination with a dynamic environment makes it even more challenging and such a setting is realistic too.
Shyam Jagannathan, Kumar Desappan, Pramod Swami, Manu Mathew, Soyeb Nagori, Kedar Chitnis, Yogesh Marathe, Suriya Narayanan and Anshu Jain:
Efficient object detection and classification on low power embedded systems
2017 IEEE International Conference on Consumer Electronics (ICCE)
Suriya Narayanan and Nagendra Gulur:
Understanding the performance benefit of asynchronous data transfers in OpenCL programs executing on media processors
IEEE 22nd International Conference on High Performance Computing (HiPC), 2015.
Suriya Narayanan and Prashanth Viswanath:
Improved Ground Plane detection in real time systems using homography
ICCE 2014
Sandeep Nital David, Sachin P Santosh and Suriya Narayanan:
Control Strategy for power flow management in a PV system supplying electrical loads in an air-conditioned bus
IEEE International Conference on Power Signals Control and Computations (EPSCICON), 2014.
Suriya Narayanan and Prashanth Viswanath:
Ground plane detection US<PHONE_NUMBER>3 A1
The idea of this pet project is to experiment with the effectiveness of LSTM and GRU for action recognition over averaged classification score (averaged over a certain set of frames).
Coded various Q networks such as linear Q, non-linear Q, deep Q networks to train an agent for playing atari games
Coded A2C algorithm to train an agent for playing atari games
Developed the ID3 training algorithm in python from scratch.
Developed a fully connected network in python from scratch. The code contained portions for feed-forward propogation and backward propogation.
Developed a computer vision application that tracks the eye ball movement and controls the mouse pointer accordingly. OpenCV 2.0 was used for Image Processing and Qt was used for user interface development.


{% extends 'layouts/application.html' %}
{% from 'macros/helpers.html' import sprite %}
{% import "items/playgrounds/playground.html" as pg %}
{% block content %}
Playground
Card
{{ pg.playground(
img='http://placehold.it/387x138',
user_logo='http://placehold.it/66x66',
username='FanTeam',
user_desc='Качественный сайт по Daily Fantasy Sports с большим количеством лиг, доступный игрокам из СНГ.',
rel='9',
support='8',
pl_count='6.4k',
stars_count='5',
forum_count='354'
)}}
Head
{% include "items/playgrounds/playground-head.html" %}
Info
{% include "items/playgrounds/playground-info.html" %}
Expert
{% include "items/playgrounds/playground-expert.html" %}
Deposit and lang
{% include "items/playgrounds/playground-deposit-and-lang.html" %}
Review
{% include "items/playgrounds/playground-review.html" %}
{% endblock %}


| Class | Description |
|---|---|
| Msvc2005CCompiler |
Adapter for the Microsoft(r) C/C++ 8 Optimizing Compiler
|
| MsvcCCompiler |
Adapter for the Microsoft(r) C/C++ Optimizing Compiler
|
| MsvcCompatibleCCompiler |
An abstract base class for compilers that are basically command line
compatible with Microsoft(r) C/C++ Optimizing Compiler
|
| MsvcCompatibleLibrarian |
Abstract base adapter for librarians with command line options compatible
with the Microsoft(r) Library Manager
|
| MsvcCompatibleLinker |
Abstract base class for linkers that try to mimic the command line arguments
for the Microsoft (r) Incremental Linker
|
| MsvcLibrarian |
Adapter for the Microsoft (r) Library Manager
|
| MsvcLinker |
Adapter for the Microsoft (r) Incremental Linker
|
| MsvcMessageCompiler |
Adapter for the Microsoft (r) Windows 32 Message Compiler
|
| MsvcMIDLCompiler |
Adapter for the Microsoft (r) MIDL Compiler
|
| MsvcProcessor |
A add-in class for Microsoft Developer Studio processors
|
| MsvcProjectWriter |
Writes a Microsoft Visual Studio 97 or Visual Studio 6 project file.
|
| MsvcResourceCompiler |
Adapter for the Microsoft (r) Windows 32 Resource Compiler
|
| VisualStudioNETProjectWriter |
Writes a Visual Studio.NET project file.
|
Copyright © 2005-2016 NAR Maven Plugin developers. All Rights Reserved.


2 Kings 4:9
And she said unto her husband, Behold now, I perceive that this is an holy man of God, which passeth by us continually.


P2P
Wanna Chat..?
Get a Room
Tried Skype, Hangout, etc.. but got frustrated because of slow internet connection...?
No installation required.
No sign up.
No strings attached.
Simply create a chat room and share the link to get connected.


Full-stack developer, team-project leader, SOA Architect, Entrepanuer
Visible Universe, Milky Way, Solar System, Earth, Middle East, Israel, Tel-Aviv, Kiryat Shalom
Full-stack developer with over 20 years hands on development. Skilled in various languages and programming stacks, including .Net, PHP, nodejs/js, JAVA technologies. Committed & quickly adapting into projects and team, talented, quick learner & experience over multitude fields, technologies and architectures. Inventing, researching, architect, and leadership is in my DNA. Highly motivated and proven experience in leading development teams and projects for large software web-based systems. Skilled & knowledgeable in networking, server administration (win & nix) & wide variety of libraries, open source technologies and development environments.
Senior Full-Stack, Software Developer, Architect, Leader
Employment Duration: 4 yrs 2 mos
Senior Software Developer and Leader of Three Application Teams
Location Israel, Netanya
Commtouch, former leader of web based email & today anti-spam service, providing the service as integrated to the largest ISP. Team leader of Commtouch’s main project, Customized Web-based email that was services over 20 million users worldwide.
My job entailed:
Team Leader
Company Name Bank Leumi (Keshev)
Dates Employed 1997 – 1999
Employment Duration 2 yrs
Leading a team of internet developers, building and improving the banks promotional website. ASP, JAVA and other technologies
The Open University of Israel
Degree Name BS (seminar missing)
Field Of Study Mathematics and Computer Science
Grade 85
Dates attended or expected graduation 1997 – 2004
Algorithms
Databases
Advanced Math & Statistics
NP & Complex Problems
Networking
Operating Systems - Unix & C++
Artificial Intelligence
Multiple Languages: Assembly, Pascal, C/C++, Java, ADA
Issuing authority Udacity
Issued date and, if applicable, expiration date of the certification or license Issued Nov 2019
No Expiration Date
Credential Identifier Credential ID PL6EF6D2
See credential
freeCodeCamp
JavaScript Algorithms and Data Structures Certification
Issuing authority freeCodeCamp
Issued date and, if applicable, expiration date of the certification or license Issued Oct 2019
No Expiration Date
Credential Identifier Credential ID fccf59801d1-fd75-4b26-8ab3-32e357082f42
See credential
freeCodeCamp
Responsive Web Design Certification
Issuing authority freeCodeCamp
Issued date and, if applicable, expiration date of the certification or license Issued Oct 2019 No Expiration Date
Credential Identifier Credential ID fccf59801d1-fd75-4b26-8ab3-32e357082f42
See credential
Code School
shaping-up-with-angular-js
Issuing authorityCode School
Books
Resturants


4,425 for Call to Bar Nov 28 - The Nation Newspaper
By John Austin Unachukwu
The Council of Legal Education will on November 28 and 29 call 4,425 successful students of the Nigerian Law School to the Nigerian Bar.
They were successful in the ‘Bar Final Examinations’ conducted in August 2019.
Read Also: Nigerian Law School releases Bar final exam results
A statement by the Director-General of the NLS, Prof. Isa Chiroma (SAN), said the successful candidates would be called to Bar in Abuja between November 26 and 28. Chiroma said of the 5,689 students who took the examinations, 4,425 were successful, 319 had conditional pass, while 894 failed.
Of the successful candidates, Chiroma said 2.58 per cent had First Class, 13.03 per cent had Second Class Upper while 5.61 per cent of the students had conditional pass, and 15.71 per cent failed.


{% extends "base.html" %} {% block breadcrumbs %}{% endblock %} {% block content %}
That page does not exist.


Redesign QoS on SteelHead and SteelCentral Controller for greater flexibility and improved simplicity.
2014
The QoS feature of the SteelHead was being re-implemented and so it was due for a redesign. QoS is extremely complex and the design process was long. Through extensive UX research and design, I proposed a new mental model for QoS in the SteelHead. The engineering team involved liked it so much, they changed the underlying implementation to match the UX proposed mental model. Also, a new paradigm of mass configuration was introduced to SteelCentral Controller for this feature. The entire project was an incredible success.
QoS is an enormously complex feature. The first step in the process was to fully understand how QoS works, what its intended to do, and what is needed to make it do that. I learned everything from the HFSC algorithm, QoS classes, deep packet inspection, latency priority, minimum and maximum bandwidth, etc. It got to the point where the questions I asked of the engineers couldn't be answered without looking into their source code.
After learning everything there is to know about how QoS works, it was time to speak with network administrators to see how they actually use it. I went onsite at several companies in Illinois, Montreal, and the UK. The user researcher and I also conducted remote interviews of many more firms. We learned what they used QoS for, what issues they had with the current version of QoS, and what they wanted to do with the QoS feature in the future.
QoS needs to know the speeds of every network connection in the system. It needs to know this so it can adequately divide up resources. Network administrators have hundreds, or even thousands of locations. And each location can have multiple network connections. So I created an entire concept around this called 'Sites.' Each site has any number of uplinks (network connections) and each uplink has upstream and downstream bandwidths associated with them. This gives the QoS system the information it needs on bandwidth restrictions across the entire network.
QoS systems usually have the concept of classes. Classes are sort of like buckets. The network administrator puts certain applications into certain buckets, then the system treats each bucket with a certain level of importance. The most important thing to remember about these buckets, is that giving one more resources, necessarily gives the others less. Also, putting all traffic into an important bucket may not be desirable. QoS works by prioritizing important traffic over less important traffic. If all traffic is marked as important, it can't do that. Concerns like this were common from network administrators. I attempted to produce UI's that could show some of this information in a visual way, but in the end, we settled for a fairly simple tree visualization. A few slides after this, there are some concepts I made for visually showing class information.
QoS classes are like buckets you put Apps into that then get managed by the QoS system. Rules are the mechanism by which the network administrator puts apps into the classes. Because SteelHead has incredibly powerful Deep Packet Inspection (DPI) technology. Specifying apps is very easy. Users can search for commonly known app names, as opposed to intricate IP address and port mappings. Also, our team pre-grouped the apps into about 8 groups. Each group contains approximately 800 applications. The rules can be specified with an individual app or an individual app group. This makes configuring QoS extremely fast.
QoS profiles are how you connect QoS Classes and Rules and Sites. The SteelCentral Controller has a birds-eye view of all the SteelHeads on a customer's network. We designed the profiles UI to take advantage of this extra knowledge. We did this by having the network administrator choose a source and destination site, or group of sites, that each profile applies to. With this information, the SteelCentral Controller knows how to distribute the QoS Profiles to all appliances automatically. This simplification makes QoS configuration far more declarative. This is something we strive for. We call it 'intent' based management. Where the network administrator specifies what they want, rather than how to make it happen. This is an incredibly powerful paradigm for the new QoS feature.
As with all products and features, not everything the design team makes, makes it into the product. Sometimes they're features that are not needed, sometimes they are too complex, and sometimes they are just way too cool. Below are some experiments that I made that never shipped.
Setting the min and max bandwidth allocations for a QoS class is kind of a guessing game. Set the numbers and see how it goes. In order to alleviate this, I attempted to create some mockups with configurations that would advise the user of issues with the classes and tried to summarize their congestion over time in a visual way.
Uplink Variations are a system where the network admin could select different QoS Class min and max assignments based on the Uplink that was being used. This is important when one or more network connections fail at a site. In those conditions, critical traffic needs a higher priority.


Thank you for taking time out to visit my site. I am a graduate from UCF's Full Stack Web Development Program and currently living in Orlando, FL.
Creating websites, working with databases, learning new technoligies, and solving hard technical problems are some of my biggest passions. It's just something I love.
To learn more about what I can do or for any qustions just click the connect button below or any of the social media icons.
Contact
Developed a CRM System for a small call center of 60 employees who are in charge of training car dealership sales reps, generating leads, setting appointments, outbound calling as mystery shoppers, creating dealer orders, taking payments, printing reports, and much more. Technologies used: HTML5, CSS3, JavaScript, Node.js, React, Express, MsSQL, jsPDF, html2canvas, Twitter Bootstrap.
Assist students currently enrolled in Trilogy’s Full Stack Web Development Program with concepts and technologies such as OOCP, JavaScript, Node.js, React, Express, mySQL, MongoDB, Git/GitHub, HTML, CSS, Twitter Bootstrap.
Responsible for communicating with customers and establishing realistic expectations and arrival times. Utilize proper tools and techniques to ensure efficient, timely, and quality installation service. Ensure required paperwork is completed and turned in as appropriate. Maintain a safe driving record in accordance with company policy. Provide exceptional customer service.
Computer Science applied to JavaScript Databases (MySQL, MongoDB) Server Side Development (Node.js, Express, MERN Stack) Browser Based Technologies (HTML, CSS, JavaScript, jQuery, Bootstrap) Deployment (Heroku, Git) PHP (Laravel, LAMP Stack) Quality Assurance (Writing Tests) Internet Marketing (Semantic HTML)
Business, Management, and Marketing. an understanding of organisational behaviour and structure; analytical and critical thinking; a creative approach to problem solving; decision-making; persuasive written and oral communication; self-reliance, initiative and the ability to manage time, projects and resources; appreciation of the causes and effects of economic and other external changes.
Connect a multitude of services – finance, analytics, external data providers, automation, business logic, etc.
Specialty in creating custom, user interfaces with the capability to step in at any stage of an application's user interface design. Desktop, Browser, or Mobile.
Helping user's create on online business presence with proven Social Media Marketing Stratigies, SEO, and Google Adword campaigns.


1.20.0 (Pending)¶
Incompatible Behavior Changes¶
Changes that are expected to cause an incompatibility if applicable; deployment changes are likely required
config: the
--bootstrap-version
CLI flag has been removed, Envoy has only been able to accept v3 bootstrap configurations since 1.18.0.contrib: the squash filter has been moved to contrib images.
contrib: the kafka broker filter has been moved to contrib images.
contrib: the RocketMQ proxy filter has been moved to contrib images.
contrib: the Postgres proxy filter has been moved to contrib images.
contrib: the MySQL proxy filter has been moved to contrib images.
ext_authz: fixed skipping authentication when returning either a direct response or a redirect. This behavior can be temporarily reverted by setting the
envoy.reloadable_features.http_ext_authz_do_not_skip_direct_response_and_redirect
runtime guard to false.
Minor Behavior Changes¶
Changes that may cause incompatibilities for some users, but should not for most
config: configuration files ending in .yml now load as YAML.
config: configuration file extensions now ignore case when deciding the file type. E.g., .JSON file load as JSON.
config: reduced log level for “Unable to establish new stream” xDS logs to debug. The log level for “gRPC config stream closed” is now reduced to debug when the status is
Ok
or has been retriable (DeadlineExceeded
,ResourceExhausted
, orUnavailable
) for less than 30 seconds.grpc: gRPC async client can be cached and shared accross filter instances in the same thread, this feature is turned off by default, can be turned on by setting runtime guard
envoy.reloadable_features.enable_grpc_async_client_cache
to true.http: correct the use of the
x-forwarded-proto
header and the:scheme
header. Where they differ (which is rare):scheme
will now be used for serving redirect URIs and cached content. This behavior can be reverted by setting runtime guardcorrect_scheme_and_xfp
to false.http: reject requests with #fragment in the URI path. The fragment is not allowed to be part of request URI according to RFC3986 (3.5), RFC7230 (5.1) and RFC 7540 (<IP_ADDRESS>). Rejection of requests can be changed to stripping the #fragment instead by setting the runtime guard
envoy.reloadable_features.http_reject_path_with_fragment
to false. This behavior can further be changed to the deprecated behavior of keeping the fragment by setting the runtime guardenvoy.reloadable_features.http_strip_fragment_from_path_unsafe_if_disabled
. This runtime guard must only be set to false when existing non-compliant traffic relies on #fragment in URI. When this option is enabled, Envoy request authorization extensions may be bypassed. This override and its associated behavior will be decommissioned after the standard deprecation period.http: set the default lazy headermap threshold to 3, which defines the minimal number of headers in a request/response/trailers required for using a dictionary in addition to the list. Setting the
envoy.http.headermap.lazy_map_min_size
runtime feature to a non-negative number will override the default value.http: stop processing pending H/2 frames if connection transitioned to a closed state. This behavior can be temporarily reverted by setting the
envoy.reloadable_features.skip_dispatching_frames_for_closed_connection
to false.listener: added the enable_reuse_port field and changed the default for reuse_port from false to true, as the feature is now well supported on the majority of production Linux kernels in use. The default change is aware of hot restart, as otherwise the change would not be backwards compatible between restarts. This means that hot restarting on to a new binary will retain the default of false until the binary undergoes a full restart. To retain the previous behavior, either explicitly set the new configuration field to false, or set the runtime feature flag
envoy.reloadable_features.listener_reuse_port_default_enabled
to false. As part of this change, the use of reuse_port for TCP listeners on both macOS and Windows has been disabled due to suboptimal behavior. See the field documentation for more information.
Bug Fixes¶
Changes expected to improve the state of the world and are unlikely to have negative effects
access log: fix
%UPSTREAM_CLUSTER%
when used in http upstream access logs. Previously, it was always logging as an unset value.access log: fix
%UPSTREAM_CLUSTER%
when used in http upstream access logs. Previously, it was always logging as an unset value.aws request signer: fix the AWS Request Signer extension to correctly normalize the path and query string to be signed according to AWS’ guidelines, so that the hash on the server side matches. See AWS SigV4 documentaion.
cluster: delete pools when they’re idle to fix unbounded memory use when using PROXY protocol upstream with tcp_proxy. This behavior can be temporarily reverted by setting the
envoy.reloadable_features.conn_pool_delete_when_idle
runtime guard to false.dynamic forward proxy: fixing a validation bug where san and sni checks were not applied setting http_protocol_options via typed_extension_protocol_options.
ext_authz: fix the ext_authz filter to correctly merge multiple same headers using the ‘,’ as separator in the check request to the external authorization service.
hcm: remove deprecation for xff_num_trusted_hops and forbid mixing ip detection extensions with old related knobs.
http: limit use of deferred resets in the http2 codec to server-side connections. Use of deferred reset for client connections can result in incorrect behavior and performance problems.
listener: fixed an issue on Windows where connections are not handled by all worker threads.
xray: fix the AWS X-Ray tracer bug where span’s error, fault and throttle information was not reported properly as per the AWS X-Ray documentation. Before this fix, server error was reported under ‘annotations’ section of the segment data.
Removed Config or Runtime¶
Normally occurs at the end of the deprecation period
http: removed
envoy.reloadable_features.http_upstream_wait_connect_response
runtime guard and legacy code paths.http: removed
envoy.reloadable_features.allow_preconnect
runtime guard and legacy code paths.listener: removed
envoy.reloadable_features.disable_tls_inspector_injection
runtime guard and legacy code paths.ocsp: removed
envoy.reloadable_features.check_ocsp_policy deprecation
runtime guard and legacy code paths.ocsp: removed
envoy.reloadable_features.require_ocsp_response_for_must_staple_certs deprecation
and legacy code paths.quic: removed
envoy.reloadable_features.prefer_quic_kernel_bpf_packet_routing
runtime guard.
New Features¶
access_log: added METADATA token to handle all types of metadata (DYNAMIC, CLUSTER, ROUTE).
bootstrap: added inline_headers in the bootstrap to make custom inline headers bootstrap configurable.
contrib: added new contrib images which contain contrib extensions.
grpc reverse bridge: added a new option to support streaming response bodies when withholding gRPC frames from the upstream.
http: added string_match in the header matcher.
http: added support for max_requests_per_connection for both upstream and downstream connections.
http: sanitizing the referer header as documented here. This feature can be temporarily turned off by setting runtime guard
envoy.reloadable_features.sanitize_http_header_referer
to false.jwt_authn: added support for Jwt Cache and its size can be specified by jwt_cache_size.
listener: new listener metric
downstream_cx_transport_socket_connect_timeout
to track transport socket timeouts.rbac: added destination_port_range for matching range of destination ports.
thrift_proxy: added support for mirroring requests.
Deprecated¶
api: the matcher field has been deprecated in favor of matcher in order to break a build dependency.
cluster: max_requests_per_connection is deprecated in favor of max_requests_per_connection.
http: the HeaderMatcher fields exact_match, safe_regex_match, prefix_match, suffix_match and contains_match are deprecated by string_match.
listener: reuse_port has been deprecated in favor of enable_reuse_port. At the same time, the default has been changed from false to true. See above for more information.


@* * Copyright 2021 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 models.forms.DecisionFormData @( formData: Form[DecisionFormData], value: Boolean = true, inputClass: Option[String] = None, hint: Option[String] = None )(implicit messages: Messages)


18649 - FMEA
18649 <semester>
Group x - Student names and andrewIds
Failure Modes and Effects Analysis
Ref #
Unit
Failiure Mode
Local Effects
System Effects
Remedial Action
Requirements Affected
...


Library: MongoDB
Package: MongoDB
Header: Poco/MongoDB/KillCursorsRequest.h
Description
Class for creating an OP_KILL_CURSORS client request. This request is used to kill cursors, which are still open, returned by query requests.
Inheritance
Direct Base Classes: RequestMessage
All Base Classes: Message, RequestMessage
Member Summary
Member Functions: buildRequest, cursors
Inherited Functions: buildRequest, header, messageLength, send
Constructors
KillCursorsRequest
Creates a KillCursorsRequest.
Destructor
~KillCursorsRequest
virtual ~KillCursorsRequest();
Destroys the KillCursorsRequest.
Member Functions
cursors
std::vector < Int64 > & cursors();
The internal list of cursors.
buildRequest
void buildRequest(
BinaryWriter & writer
);
Variables
_cursors
std::vector < Int64 > _cursors;


Match Play. Red trails 3-5 to 7. Should Red double? If doubled, should White take?
pips Red=134 White=130
(CorrectAnswer= 0/0, ErrorScore= 0)
At 3-5 to 7 White’s alarm bells should be ringing. What is only a marginal double and trivial take for money is a massive drop at this score with gammons working optimally for Red.
If you took this one as White you have some serious soul-searching to do.
If you took this one as White you have some serious soul-searching to do.
Cube analysis 2-ply cubeless equity +0.328 (Money: +0.408) 0.628 0.245 0.007 - 0.372 0.095 0.004 Cubeful equities: 1. Double, pass +1.000 2. Double, take +1.332 (+0.332) 3. No double +0.826 (-0.174) Proper cube action: Double, pass


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This file cannot be viewed or edited in the INTO-CPS Application.
The file is compressed with ZIP. See more at
fmi-standard.org


Overview
Returns a record set in CSV format along with HTTP headers to indicate content type.
Request Arguments
| Name |
Type |
Description |
Required |
|
uid
|
Array
|
A list of bean ids.
|
False
|
|
filter
|
Array
|
The filter expression. More information on filter expressions can be found in /<module>/filter .
|
False
|
|
sample
|
Array
|
Indicates whether to download sample data.
|
False
|
Request Examples
Exporting Records by Specific IDs
{
"uid":"d43243c6-9b8e-2973-aee2-512d09bc34b4"
}
Exporting Records by a List of IDs
{
"uid":[
"d43243c6-9b8e-2973-aee2-512d09bc34b4",
"b3e87a3f-cd8f-7b86-467a-512d09e8d240"
]
}
Exporting Records Using a Filter
{
"filter":[
{
"name":"airline"
}
]
}
Exporting a Sample Result Set
{
"sample":true
}
Response Arguments
| Name |
Type |
Description |
|
<csv export>
|
String;
|
Returns the selected records in CSV format with the content headers.
|
Response
result: HTTP/1.1 200 OK
Date: Fri, 01 Mar 2013 04:05:55 GMT
Server: Apache/2.2.22 (Unix) DAV/2 PHP/5.3.17
X-Powered-By: PHP/5.3.17
Expires: Mon, 26 Jul 1997 05:00:00 GMT
Cache-Control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0
Pragma: cache
Content-Disposition: attachment; filename=Accounts.csv
Content-transfer-encoding: binary
Last-Modified: Fri, 01 Mar 2013 04:05:55 GMT
Cache-Control: post-check=0, pre-check=0
Content-Length: 1080
Connection: close
Content-Type: application/octet-stream; charset=UTF-8
"Name","ID","Website","Email Address","Office Phone","Alternate Phone","Fax","Billing Street","Billing City","Billing State","Billing Postal Code","Billing Country","Shipping Street","Shipping City","Shipping State","Shipping Postal Code","Shipping Country","Description","Type","Industry","Annual Revenue","Employees","SIC Code","Ticker Symbol","Parent Account ID","Ownership","Campaign ID","Rating","Assigned User Name","Assigned To","Team ID","Teams","Team Set ID","Date Created","Date Modified","Modified By","Created By","Deleted","Image","last_activity_date","Linkedin Company ID","Facebook Account","Twitter Account","Google Plus ID"
"Arts & Crafts Inc","d43243c6-9b8e-2973-aee2-512d09bc34b4","","","(052) 034-1853","","","777 West Filmore Ln","Santa Monica","CA","35354","USA","777 West Filmore Ln","Santa Monica","CA","35354","USA","","Customer","Transportation","","","","","","","","","sally","seed_sally_id","West","West","West","02/26/2013 07:12 pm","02/26/2013 07:12 pm","1","1","0","","02/26/2013 07:12 pm","","","",""
Change Log
| Version |
Change |
|
v10
|
Added /<module>/export POST endpoint.
|


Voith contracts to optimise Ethiopia’s hydropower potential
by Nicolette Pombo-van ZylTechnology group Voith has signed a comprehensive service and operations consultancy contract for Gilgel Gibe II hydropower plant in Ethiopia.
A focal aspect of the two-year service and operations consultancy contract is the optimisation of the energy production of the hydropower plant, which has a current output of 420MW.
Read more on hydropower here
The agreement was signed during the G20 Investment Summit on November 19 in Berlin, Germany.
Voith’s scope of supply comprises the modernisation of the maintenance systems, the implementation of digital solutions and the knowledge transfer through special training programmes. All local activities are exclusively provided by Ethiopian Voith experts.
“Together with the plant operator Ethiopian Electric Power we want to utilise the whole potential of the hydropower plant Gilgel Gibel II. We succeed in this by reducing unplanned downtimes and failures to a minimum,” says Mark Claessen, Managing Director Voith Hydro East Africa.
“A stable and sustainable energy supply is the foundation for social and economic development in Ethiopia and many other African countries,” he added.
With a hydropower potential of 45,000MW, Ethiopia has one of the largest hydropower resources on the African continent. Since 2011, the country supports the development of renewable energy and wants to become an energy hub for East Africa in the medium term.
Read more
Modernisation to give Nangbeto hydropower plant another 30 years
Reliable energy supply in Africa
The hydropower plant Gilgel Gibel II is located about 300km south-east of the Ethiopian capital Addis Abeba.
Voith supplied four Pelton turbines and generators as well as the entire mechanical and electrical equipment and also trained the plant operator staff.
Before Gilgel Gibe II went into operation, only 15% of Ethiopia’s villages were connected to the power grid. Now, half of the rural settlements are supplied with power. In total, Ethiopian hydropower plants with Voith technology supply up to 900,000 households in the country with clean and sustainable electricity.
The agreement was signed by the Ethiopian Minister of Water, Irrigation and Electricity Dr Seleshi Bekele and Mark Claessen, Managing Director Voith Hydro East Africa in the attendance of Peter Altmaier, the German Federal Minister for Economics and Energy.
The investor summit took place within the G20-Initiative Compact with Africa. Twelve Heads of State of the African Compact partner countries as well as South Africa, acting as G20 partner of the initiative, were attending the summit.


Application resources¶
Previous sections in this guide have described how to load images, media and text documents using pyglet. Applications also usually have the need to load other data files: for example, level descriptions in a game, internationalised strings, and so on.
Programmers are often tempted to load, for example, an image required by their application with:
image = pyglet.image.load('logo.png')
This code assumes logo.png is in the current working directory. Unfortunately the working directory is not necessarily the same as the directory containing the application script files.
- Applications started from the command line can start from an arbitrary working directory.
- Applications bundled into an egg, Mac OS X package or Windows executable may have their resources inside a ZIP file.
- The application might need to change the working directory in order to work with the user’s files.
A common workaround for this is to construct a path relative to the script file instead of the working directory:
import os
script_dir = os.path.dirname(__file__)
path = os.path.join(script_dir, 'logo.png')
image = pyglet.image.load(path)
This, besides being tedious to write, still does not work for resources within ZIP files, and can be troublesome in projects that span multiple packages.
The pyglet.resource module solves this problem elegantly:
image = pyglet.resource.image('logo.png')
The following sections describe exactly how the resources are located, and how the behaviour can be customised.
Loading resources¶
Use the pyglet.resource module when files shipped with the application need to be loaded. For example, instead of writing:
data_file = open('file.txt')
use:
data_file = pyglet.resource.file('file.txt')
There are also convenience functions for loading media files for pyglet. The following table shows the equivalent resource functions for the standard file functions.
File function Resource function Type open pyglet.resource.file File-like object pyglet.image.load pyglet.resource.image Texture or TextureRegion pyglet.image.load pyglet.resource.texture Texture pyglet.image.load_animation pyglet.resource.animation Animation pyglet.media.load pyglet.resource.media Source pyglet.text.loadmimetype = text/plainpyglet.resource.text UnformattedDocument pyglet.text.loadmimetype = text/htmlpyglet.resource.html FormattedDocument pyglet.text.loadmimetype = text/vnd.pyglet-attributedpyglet.resource.attributed FormattedDocument pyglet.font.add_file pyglet.resource.add_font None
pyglet.resource.texture is for loading stand-alone textures, and would be required when using the texture for a 3D model.
pyglet.resource.image is optimised for loading sprite-like images that can have their texture coordinates adjusted. The resource module attempts to pack small images into larger textures (called an atlas) for efficient rendering (which is why the return type of this function can be TextureRegion).
Resource locations¶
Some resource files reference other files by name. For example, an HTML document can contain <img src="image.png" /> elements. In this case your application needs to locate image.png relative to the original HTML file.
Use pyglet.resource.location to get a Location object describing the location of an application resource. This location might be a file system directory or a directory within a ZIP file. The Location object can directly open files by name, so your application does not need to distinguish between these cases.
In the following example, a thumbnails.txt file is assumed to contain a list of image filenames (one per line), which are then loaded assuming the image files are located in the same directory as the thumbnails.txt file:
thumbnails_file = pyglet.resource.file('thumbnails.txt', 'rt')
thumbnails_location = pyglet.resource.location('thumbnails.txt')
for line in thumbnails_file:
filename = line.strip()
image_file = thumbnails_location.open(filename)
image = pyglet.image.load(filename, file=image_file)
# Do something with `image`...
This code correctly ignores other images with the same filename that might appear elsewhere on the resource path.
Specifying the resource path¶
By default, only the script home directory is searched (the directory containing the __main__ module). You can set pyglet.resource.path to a list of locations to search in order. This list is indexed, so after modifying it you will need to call pyglet.resource.reindex.
Each item in the path list is either a path relative to the script home, or the name of a Python module preceded with an ampersand (@). For example, if you would like to package all your resources in a res directory:
pyglet.resource.path = ['res']
pyglet.resource.reindex()
Items on the path are not searched recursively, so if your resource directory itself has subdirectories, these need to be specified explicitly:
pyglet.resource.path = ['res', 'res/images', 'res/sounds', 'res/fonts']
pyglet.resource.reindex()
The entries in the resource path always use forward slash characters as path separators even when the operating systems using a different character.
Specifying module names makes it easy to group code with its resources. The following example uses the directory containing the hypothetical gui.skins.default for resources:
pyglet.resource.path =<EMAIL_ADDRESS>'.']
pyglet.resource.reindex()
Multiple loaders¶
A Loader encapsulates a complete resource path and cache. This lets your application cleanly separate resource loading of different modules. Loaders are constructed for a given search path, and exposes the same methods as the global pyglet.resource module functions.
For example, if a module needs to load its own graphics but does not want to interfere with the rest of the application’s resource loading, it would create its own Loader with a local search path:
loader = pyglet.resource.Loader(['@' + __name__])
image = loader.image('logo.png')
This is particularly suitable for “plugin” modules.
You can also use a Loader instance to load a set of resources relative to some user-specified document directory. The following example creates a loader for a directory specified on the command line:
import sys
home = sys.argv[1]
loader = pyglet.resource.Loader(script_home=[home])
This is the only way that absolute directories and resources not bundled with an application should be used with pyglet.resource.
Saving user preferences¶
Because Python applications can be distributed in several ways, including within ZIP files, it is usually not feasible to save user preferences, high score lists, and so on within the application directory (or worse, the working directory).
The pyglet.resource.get_settings_path function returns a directory suitable for writing arbitrary user-centric data. The directory used follows the operating system’s convention:
- ~/.config/ApplicationName/ on Linux (depends on XDG_CONFIG_HOME environment variable).
- $HOME\Application Settings\ApplicationName on Windows
- ~/Library/Application Support/ApplicationName on Mac OS X
The returned directory name is not guaranteed to exist – it is the application’s responsibility to create it. The following example opens a high score list file for a game called “SuperGame” into the settings directory:
import os
dir = pyglet.resource.get_settings_path('SuperGame')
if not os.path.exists(dir):
os.makedirs(dir)
filename = os.path.join(dir, 'highscores.txt')
file = open(filename, 'wt')


infinite loop
`Prev `__
I
`Next `__
--------------
**infinite loop**: n.
One that never terminates (that is, the machine
`*spin* <../S/spin.html>`__\ s or `*buzz* <../B/buzz.html>`__\ es
forever and goes `*catatonic* <../C/catatonic.html>`__). There is a
standard joke that has been made about each generation's exemplar of the
ultra-fast machine: “The Cray-3 is so fast it can execute an infinite
loop in under 2 seconds!”
--------------
+-----------------------------+----------------------------+--------------------------------------------+
| `Prev `__ | `Up <../I.html>`__ | `Next `__ |
+-----------------------------+----------------------------+--------------------------------------------+
| infinite | `Home <../index.html>`__ | Infinite-Monkey Theorem |
+-----------------------------+----------------------------+--------------------------------------------+


Seattle, WA 98105
I wish to be a translational designer and a researcher: bridging the gap between basic research and applied research. Making research more applicable and making real problems researchable.
I love reading, traveling, taking photographs, and (making and drinking) coffee!


This is a paragraph
I like cheese, pie, dog food, sausage, coffee, David, manure, cars, blah blah blah blah blah...
Howdy y'all dlskafj;dlsajfl;asjfl;dasjfl;adsjfl;adsjf;ldsafj


get your professional web design here at konnel web design. at very low rates
HTML5 Markup language is used to create sites and gives it a Structure
CSS stylesheet is used to design the web page makes it all beautiful and nice
for logo designs and all


Quiz on Buttons and Action Events
This is a practice quiz.
The results are not recorded anywhere and do not affect your grade.
The questions on this quiz might not appear
in any quiz or test that does count toward your grade.
Instructions:
For each question,
choose the single best answer.
Make your choice by clicking on its button.
You can change your answers at any time.
When the quiz is graded, the correct answers will appear in the box after each question.
|
|
(If you have just returned here from another page,
or have re-loaded this page, you will need to click again on
each of your choices for the grading program to work correctly.
You may want to press the "shift key" while clicking on reload to clear
the old answers.)
|


Please remember to give your client a unique name. You can click one of the following links and add your unique name after the "name=" in the query string and press enter to re-load the page with your unique name.
Button:
local
lab
cloud
Slider:
local
lab
cloud
String:
local
lab
cloud
Custom:
local
lab
cloud


Strategies¶
SMI¶
-
class
trust.strategies.smi.
SMI
(labeled_dataset, unlabeled_dataset, query_dataset, net, nclasses, args={})[source]¶ Bases:
trust.strategies.strategy.Strategy
This strategy implements the Submodular Mutual Information (SMI) selection paradigm discuss in the paper SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios 1. In this selection paradigm, points from the unlabeled dataset are chosen in such a way that the submodular mutual information between this set of points and a provided query set is maximized. Doing so allows a practitioner to select points from an unlabeled set that are SIMILAR to points that they have provided in a active learning query.
These submodular mutual information functions rely on formulating embeddings for the points in the query set and the unlabeled set. Once these embeddings are formed, one or more similarity kernels (depending on the SMI function used) are formed from these embeddings based on a similarity metric. Once these similarity kernels are formed, they are used in computing the value of each submodular mutual information function. Hence, common techniques for submodular maximization subject to a cardinality constraint can be used, such as the naive greedy algorithm, the lazy greedy algorithm, and so forth.
In this framework, we set the cardinality constraint to be the active learning selection budget; hence, a list of indices with a total length less than or equal to this cardinality constraint will be returned. Depending on the maximization configuration, one can ensure that the length of this list will be equal to the cardinality constraint.
Currently, five submodular mutual information functions are implemented: fl1mi, fl2mi, gcmi, logdetmi, and com. Each function is obtained by applying the definition of a submodular mutual information function using common submodular functions. Facility Location Mutual Information (fl1mi) models pairwise similarities of points in the query set to points in the unlabeled dataset AND pairwise similarities of points within the unlabeled datasets. Another variant of Facility Location Mutual Information (fl2mi) models pairwise similarities of points in the query set to points in the unlabeled dataset ONLY. Graph Cut Mutual Information (gcmi), Log-Determinant Mutual Information (logdetmi), and Concave-Over-Modular Mutual Information (com) are all obtained by applying the usual submodular function under this definition. For more information-theoretic discussion, consider referring to the paper Submodular Combinatorial Information Measures with Applications in Machine Learning 2.
- Parameters
labeled_dataset (torch.utils.data.Dataset) – The labeled dataset to be used in this strategy. For the purposes of selection, the labeled dataset is not used, but it is provided to fit the common framework of the Strategy superclass.
unlabeled_dataset (torch.utils.data.Dataset) – The unlabeled dataset to be used in this strategy. It is used in the selection process as described above. Importantly, the unlabeled dataset must return only a data Tensor; if indexing the unlabeled dataset returns a tuple of more than one component, unexpected behavior will most likely occur.
query_dataset (torch.utils.data.Dataset) – The query dataset to be used in this strategy. It is used in the selection process as described above. Notably, the query dataset should be labeled; hence, indexing the query dataset should return a data/label pair. This is done in this fashion to allow for gradient embeddings.
net (torch.nn.Module) – The neural network model to use for embeddings and predictions. Notably, all embeddings typically come from extracted features from this network or from gradient embeddings based on the loss, which can be based on hypothesized gradients or on true gradients (depending on the availability of the label).
nclasses (int) – The number of classes being predicted by the neural network.
args (dict) –
- A dictionary containing many configurable settings for this strategy. Each key-value pair is described below:
- ’batch_size’: int
The batch size used internally for torch.utils.data.DataLoader objects. Default: 1
- ’device’: string
The device to be used for computation. PyTorch constructs are transferred to this device. Usually is one of ‘cuda’ or ‘cpu’. Default: ‘cuda’ if a CUDA-enabled device is available; otherwise, ‘cpu’
- ’loss’: function
The loss function to be used in computations. Default: torch.nn.functional.cross_entropy
- ’smi_function’: string
The submodular mutual information function to use in optimization. Must be one of ‘fl1mi’, ‘fl2mi’, ‘gcmi’, ‘logdetmi’, ‘com’. REQUIRED
- ’optimizer’: string
The optimizer to use for submodular maximization. Can be one of ‘NaiveGreedy’, ‘StochasticGreedy’, ‘LazyGreedy’ and ‘LazierThanLazyGreedy’. Default: ‘NaiveGreedy’
- ’metric’: string
The similarity metric to use for similarity kernel computation. This can be either ‘cosine’ or ‘euclidean’. Default: ‘cosine’
- ’eta’: float
A magnification constant that is used in all but gcmi. It is used as a value of query-relevance vs diversity trade-off. Increasing eta tends to increase query-relevance while reducing query-coverage and diversity. Default: 1
- ’embedding_type’: string
The type of embedding to compute for similarity kernel computation. This can be either ‘gradients’ or ‘features’. Default: ‘gradients’
- ’gradType’: string
When ‘embedding_type’ is ‘gradients’, this defines the type of gradient to use. ‘bias’ creates gradients from the loss function with respect to the biases outputted by the model. ‘linear’ creates gradients from the loss function with respect to the last linear layer features. ‘bias_linear’ creates gradients from the loss function using both. Default: ‘bias_linear’
- ’layer_name’: string
When ‘embedding_type’ is ‘features’, this defines the layer within the neural network that is used to extract feature embeddings. Namely, this argument must be the name of a module used in the forward() computation of the model. Default: ‘avgpool’
- ’stopIfZeroGain’: bool
Controls if the optimizer should cease maximization if there is zero gain in the submodular objective. Default: False
- ’stopIfNegativeGain’: bool
Controls if the optimizer should cease maximization if there is negative gain in the submodular objective. Default: False
- ’verbose’: bool
Gives a more verbose output when calling select() when True. Default: False
-
select
(budget)[source]¶ Selects a set of points from the unlabeled dataset to label based on this strategy’s methodology.
- Parameters
budget (int) – Number of points to choose from the unlabeled dataset
- Returns
chosen – List of selected data point indices with respect to the unlabeled dataset
- Return type
list
SCG¶
-
class
trust.strategies.scg.
SCG
(labeled_dataset, unlabeled_dataset, private_dataset, net, nclasses, args={})[source]¶ Bases:
trust.strategies.strategy.Strategy
This strategy implements the Submodular Conditional Gain (SCG) selection paradigm discuss in the paper SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios 1. In this selection paradigm, points from the unlabeled dataset are chosen in such a way that the submodular conditional gain between this set of points and a provided private set is maximized. Doing so allows a practitioner to select points from an unlabeled set that are dissimilar to points provided in the private set.
These submodular conditional gain functions rely on formulating embeddings for the points in the unlabeled set and the private set. Once these embeddings are formed, similarity kernels are formed from these embeddings based on a similarity metric. Once these similarity kernels are formed, they are used in computing the value of each submodular conditional gain function. Hence, common techniques for submodular maximization subject to a cardinality constraint can be used, such as the naive greedy algorithm, the lazy greedy algorithm, and so forth.
In this framework, we set the cardinality constraint to be the active learning selection budget; hence, a list of indices with a total length less than or equal to this cardinality constraint will be returned. Depending on the maximization configuration, one can ensure that the length of this list will be equal to the cardinality constraint.
Currently, two submodular conditional gain functions are implemented: ‘flcg’, ‘gccg’, and ‘logdetcg’. Each function is obtained by applying the definition of a submodular conditional gain function using common submodular functions. For more information-theoretic discussion, consider referring to the paper Submodular Combinatorial Information Measures with Applications in Machine Learning 2.
- Parameters
labeled_dataset (torch.utils.data.Dataset) – The labeled dataset to be used in this strategy. For the purposes of selection, the labeled dataset is not used, but it is provided to fit the common framework of the Strategy superclass.
unlabeled_dataset (torch.utils.data.Dataset) – The unlabeled dataset to be used in this strategy. It is used in the selection process as described above. Importantly, the unlabeled dataset must return only a data Tensor; if indexing the unlabeled dataset returns a tuple of more than one component, unexpected behavior will most likely occur.
private_dataset (torch.utils.data.Dataset) – The private dataset to be used in this strategy. It is used in the selection process as described above. Notably, the private dataset should be labeled; hence, indexing the query dataset should return a data/label pair. This is done in this fashion to allow for gradient embeddings.
net (torch.nn.Module) – The neural network model to use for embeddings and predictions. Notably, all embeddings typically come from extracted features from this network or from gradient embeddings based on the loss, which can be based on hypothesized gradients or on true gradients (depending on the availability of the label).
nclasses (int) – The number of classes being predicted by the neural network.
args (dict) –
- A dictionary containing many configurable settings for this strategy. Each key-value pair is described below:
- ’batch_size’: int
The batch size used internally for torch.utils.data.DataLoader objects. Default: 1
- ’device’: string
The device to be used for computation. PyTorch constructs are transferred to this device. Usually is one of ‘cuda’ or ‘cpu’. Default: ‘cuda’ if a CUDA-enabled device is available; otherwise, ‘cpu’
- ’loss’: function
The loss function to be used in computations. Default: torch.nn.functional.cross_entropy
- ’scg_function’: string
The submodular mutual information function to use in optimization. Must be one of ‘flcmi’ or ‘logdetcmi’. REQUIRED
- ’optimizer’: string
The optimizer to use for submodular maximization. Can be one of ‘NaiveGreedy’, ‘StochasticGreedy’, ‘LazyGreedy’ and ‘LazierThanLazyGreedy’. Default: ‘NaiveGreedy’
- ’metric’: string
The similarity metric to use for similarity kernel computation. This can be either ‘cosine’ or ‘euclidean’. Default: ‘cosine’
- ’nu’: float
A parameter that governs the hardness of the privacy constraint. Default: 1.
- ’embedding_type’: string
The type of embedding to compute for similarity kernel computation. This can be either ‘gradients’ or ‘features’. Default: ‘gradients’
- ’gradType’: string
When ‘embedding_type’ is ‘gradients’, this defines the type of gradient to use. ‘bias’ creates gradients from the loss function with respect to the biases outputted by the model. ‘linear’ creates gradients from the loss function with respect to the last linear layer features. ‘bias_linear’ creates gradients from the loss function using both. Default: ‘bias_linear’
- ’layer_name’: string
When ‘embedding_type’ is ‘features’, this defines the layer within the neural network that is used to extract feature embeddings. Namely, this argument must be the name of a module used in the forward() computation of the model. Default: ‘avgpool’
- ’stopIfZeroGain’: bool
Controls if the optimizer should cease maximization if there is zero gain in the submodular objective. Default: False
- ’stopIfNegativeGain’: bool
Controls if the optimizer should cease maximization if there is negative gain in the submodular objective. Default: False
- ’verbose’: bool
Gives a more verbose output when calling select() when True. Default: False
-
select
(budget)[source]¶ Selects a set of points from the unlabeled dataset to label based on this strategy’s methodology.
- Parameters
budget (int) – Number of points to choose from the unlabeled dataset
- Returns
chosen – List of selected data point indices with respect to the unlabeled dataset
- Return type
list
SCMI¶
-
class
trust.strategies.scmi.
SCMI
(labeled_dataset, unlabeled_dataset, query_dataset, private_dataset, net, nclasses, args={})[source]¶ Bases:
trust.strategies.strategy.Strategy
This strategy implements the Submodular Conditional Mutual Information (SCMI) selection paradigm discuss in the paper SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios 1. In this selection paradigm, points from the unlabeled dataset are chosen in such a way that the submodular conditional mutual information between this set of points and a provided query set is maximized, conditioned on a private dataset. Doing so allows a practitioner to select points from an unlabeled set that are SIMILAR to points that they have provided in the query set while being dissimilar to points provided in the private set.
These submodular conditional mutual information functions rely on formulating embeddings for the points in the query set, the unlabeled set, and the private set. Once these embeddings are formed, similarity kernels are formed from these embeddings based on a similarity metric. Once these similarity kernels are formed, they are used in computing the value of each submodular conditional mutual information function. Hence, common techniques for submodular maximization subject to a cardinality constraint can be used, such as the naive greedy algorithm, the lazy greedy algorithm, and so forth.
In this framework, we set the cardinality constraint to be the active learning selection budget; hence, a list of indices with a total length less than or equal to this cardinality constraint will be returned. Depending on the maximization configuration, one can ensure that the length of this list will be equal to the cardinality constraint.
Currently, two submodular conditional mutual information functions are implemented: ‘flcmi’ and ‘logdetcmi’. Each function is obtained by applying the definition of a submodular conditional mutual information function using common submodular functions. For more information-theoretic discussion, consider referring to the paper Submodular Combinatorial Information Measures with Applications in Machine Learning 2.
- Parameters
labeled_dataset (torch.utils.data.Dataset) – The labeled dataset to be used in this strategy. For the purposes of selection, the labeled dataset is not used, but it is provided to fit the common framework of the Strategy superclass.
unlabeled_dataset (torch.utils.data.Dataset) – The unlabeled dataset to be used in this strategy. It is used in the selection process as described above. Importantly, the unlabeled dataset must return only a data Tensor; if indexing the unlabeled dataset returns a tuple of more than one component, unexpected behavior will most likely occur.
query_dataset (torch.utils.data.Dataset) – The query dataset to be used in this strategy. It is used in the selection process as described above. Notably, the query dataset should be labeled; hence, indexing the query dataset should return a data/label pair. This is done in this fashion to allow for gradient embeddings.
private_dataset (torch.utils.data.Dataset) – The private dataset to be used in this strategy. It is used in the selection process as described above. Notably, the private dataset should be labeled; hence, indexing the query dataset should return a data/label pair. This is done in this fashion to allow for gradient embeddings.
net (torch.nn.Module) – The neural network model to use for embeddings and predictions. Notably, all embeddings typically come from extracted features from this network or from gradient embeddings based on the loss, which can be based on hypothesized gradients or on true gradients (depending on the availability of the label).
nclasses (int) – The number of classes being predicted by the neural network.
args (dict) –
- A dictionary containing many configurable settings for this strategy. Each key-value pair is described below:
- ’batch_size’: int
The batch size used internally for torch.utils.data.DataLoader objects. Default: 1
- ’device’: string
The device to be used for computation. PyTorch constructs are transferred to this device. Usually is one of ‘cuda’ or ‘cpu’. Default: ‘cuda’ if a CUDA-enabled device is available; otherwise, ‘cpu’
- ’loss’: function
The loss function to be used in computations. Default: torch.nn.functional.cross_entropy
- ’scmi_function’: string
The submodular mutual information function to use in optimization. Must be one of ‘flcmi’ or ‘logdetcmi’. REQUIRED
- ’optimizer’: string
The optimizer to use for submodular maximization. Can be one of ‘NaiveGreedy’, ‘StochasticGreedy’, ‘LazyGreedy’ and ‘LazierThanLazyGreedy’. Default: ‘NaiveGreedy’
- ’metric’: string
The similarity metric to use for similarity kernel computation. This can be either ‘cosine’ or ‘euclidean’. Default: ‘cosine’
- ’eta’: float
A magnification constant that is used in all but gcmi. It is used as a value of query-relevance vs diversity trade-off. Increasing eta tends to increase query-relevance while reducing query-coverage and diversity. Default: 1
- ’nu’: float
A parameter that governs the hardness of the privacy constraint. Default: 1.
- ’embedding_type’: string
The type of embedding to compute for similarity kernel computation. This can be either ‘gradients’ or ‘features’. Default: ‘gradients’
- ’gradType’: string
When ‘embedding_type’ is ‘gradients’, this defines the type of gradient to use. ‘bias’ creates gradients from the loss function with respect to the biases outputted by the model. ‘linear’ creates gradients from the loss function with respect to the last linear layer features. ‘bias_linear’ creates gradients from the loss function using both. Default: ‘bias_linear’
- ’layer_name’: string
When ‘embedding_type’ is ‘features’, this defines the layer within the neural network that is used to extract feature embeddings. Namely, this argument must be the name of a module used in the forward() computation of the model. Default: ‘avgpool’
- ’stopIfZeroGain’: bool
Controls if the optimizer should cease maximization if there is zero gain in the submodular objective. Default: False
- ’stopIfNegativeGain’: bool
Controls if the optimizer should cease maximization if there is negative gain in the submodular objective. Default: False
- ’verbose’: bool
Gives a more verbose output when calling select() when True. Default: False
-
select
(budget)[source]¶ Selects a set of points from the unlabeled dataset to label based on this strategy’s methodology.
- Parameters
budget (int) – Number of points to choose from the unlabeled dataset
- Returns
chosen – List of selected data point indices with respect to the unlabeled dataset
- Return type
list
References¶
- 1(1,2,3)
Suraj Kothawade, Nathan Beck, Krishnateja Killamsetty, and Rishabh Iyer. Similar: submodular information measures based active learning in realistic scenarios. arXiv preprint arXiv:2107.00717, 2021.
- 2(1,2,3)
Rishabh Iyer, Ninad Khargoankar, Jeff Bilmes, and Himanshu Asanani. Submodular combinatorial information measures with applications in machine learning. In Algorithmic Learning Theory, 722–754. PMLR, 2021.


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| Version: | 0.2.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | rappdirs, dplyr, purrr, readr, dataone |
| Published: | 2018-09-10 |
| Author: | Joseph Stachelek [aut, cre] |
| Maintainer: | Joseph Stachelek <stachel2 at msu.edu> |
| BugReports: | https://github.com/jsta/nesRdata/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://github.com/jsta/nesRdata |
| NeedsCompilation: | no |
| Citation: | nesRdata citation info |
| Materials: | README NEWS |
| CRAN checks: | nesRdata results |
| Reference manual: | nesRdata.pdf |
| Package source: | nesRdata_0.2.0.tar.gz |
| Windows binaries: | r-devel: nesRdata_0.2.0.zip, r-release: nesRdata_0.2.0.zip, r-oldrel: nesRdata_0.2.0.zip |
| OS X binaries: | r-release: nesRdata_0.2.0.tgz, r-oldrel: nesRdata_0.2.0.tgz |
| Old sources: | nesRdata archive |
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