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Merge pull request #173 from sanderland/ownershiphint

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Ownership hint
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sanderland authored and GitHub committed 2020-08-26 11:00:52 +02:00
2 parents b9cc06849f 3dff117355
commit 8901dfe25a
4 files changed
+65 -28
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katrain/KataGo/analysis_config.cfg
+11 -3
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@@ -80,15 +80,23 @@ maxVisits = 500
# But there's no substitute for experimenting and seeing what's best for your hardware and your usage case.
# Keep in mind that the number of threads you want doesn't necessarily have much to do with how many cores you
# have on your system, and could easily exceed the number of cores. GPU batching is (usually) the dominant consideration.
numAnalysisThreads = 8
numSearchThreadsPerAnalysisThread = 8
numSearchThreads = 8
# nnMaxBatchSize is the max number of positions to send to a single GPU at once. Generally, it should be the case that:
# (number of GPUs you will use * nnMaxBatchSize) >= (numSearchThreads * num-analysis-threads)
# That way, when each threads tries to request a GPU eval, your batch size summed across GPUs is large enough to handle them
# all at once. However, it can be sensible to set this a little smaller if you are limited on GPU memory,
# too large a number may fail if the GPU doesn't have enough memory.
nnMaxBatchSize = 96
nnMaxBatchSize = 64
# Eigen-specific settings--------------------------------------
# These only apply when using the Eigen (pure CPU) version of KataGo.
# This is the number of CPU threads for evaluating the neural net on the Eigen backend.
# It defaults to min(numAnalysisThreads * numSearchThreadsPerAnalysisThread, numCPUCores).
# numEigenThreadsPerModel = X
# Uncomment and set these smaller if you ONLY are going to use the analysis engine for smaller boards (or plan to
# run multiple instances, with some instances only handling smaller boards). It should improve performance.
@@ -104,7 +112,7 @@ nnMaxBatchSize = 96
# Other General GPU Settings-------------------------------------------------------------------------------
# Cache up to 2 ** this many neural net evaluations in case of transpositions in the tree.
nnCacheSizePowerOfTwo = 19
nnCacheSizePowerOfTwo = 20
# Size of mutex pool for nnCache is 2 ** this
nnMutexPoolSizePowerOfTwo = 16
# Randomize board orientation when running neural net evals?
katrain/KataGo/katago
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katrain/gui/badukpan.py
+42 -16
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@@ -10,14 +10,14 @@ from kivy.core.window import Window
from kivy.graphics.context_instructions import Color
from kivy.graphics.vertex_instructions import Ellipse, Line, Rectangle
from kivy.metrics import dp
from kivy.properties import BooleanProperty, ListProperty, ObjectProperty, NumericProperty
from kivy.properties import BooleanProperty, ListProperty, NumericProperty, ObjectProperty
from kivy.uix.dropdown import DropDown
from kivy.uix.widget import Widget
from kivymd.app import MDApp
from kivymd.uix.boxlayout import MDBoxLayout
from kivymd.uix.floatlayout import MDFloatLayout
from katrain.core.constants import MODE_PLAY, OUTPUT_DEBUG
from katrain.core.constants import MODE_PLAY, OUTPUT_DEBUG, STATUS_TEACHING
from katrain.core.game import Move
from katrain.core.lang import i18n
from katrain.core.utils import evaluation_class, var_to_grid
@@ -63,8 +63,7 @@ class BadukPanWidget(Widget):
self.draw_hover_contents()
def on_touch_down(self, touch):
self.animating_pv = None # any click kills PV from label/move
self.draw_hover_contents()
self.set_animating_pv(None, None) # any click kills PV from label/move
if "button" in touch.profile and touch.button != "left":
return
self.check_next_move_ghost(touch)
@@ -89,13 +88,11 @@ class BadukPanWidget(Widget):
if near_move:
self.set_animating_pv(near_move[0][0], near_move[0][1])
else:
self.animating_pv = None
self.draw_hover_contents()
self.set_animating_pv(None, None) # any click kills PV from label/move
if inside and self.animating_pv is not None:
d_sq = (pos[0] - self.animating_pv[3][0]) ** 2 + (pos[1] - self.animating_pv[3][1])
if d_sq > 2 * self.stone_size ** 2: # move too far from where it was activated
self.animating_pv = None
self.draw_hover_contents()
self.set_animating_pv(None, None) # any click kills PV from label/move
self.last_mouse_pos = pos
def play_stone_sound(self, *_args):
@@ -307,19 +304,40 @@ class BadukPanWidget(Widget):
self.draw_stone(1, y, "B", innercol=STONE_COLORS["W"], evalcol=evalcol)
self.draw_stone(2, y, "W", evalcol=evalcol, evalscale=y / (board_size_y - 1))
self.draw_stone(3, y, "W", innercol=STONE_COLORS["B"], evalcol=evalcol)
# self.draw_stone(4, y, evalcol=[*evalcol[:3], 0.5], scale=0.8)
# ownership - allow one move out of date for smooth animation
ownership = current_node.ownership or (current_node.parent and current_node.parent.ownership)
if katrain.analysis_controls.ownership.active and ownership:
ownership_grid = var_to_grid(ownership, (board_size_x, board_size_y))
rsz = self.grid_size * 0.2
for y in range(board_size_y - 1, -1, -1):
for x in range(board_size_x):
ix_owner = "B" if ownership_grid[y][x] > 0 else "W"
if ix_owner != (has_stone.get((x, y), -1)):
Color(*STONE_COLORS[ix_owner][:3], abs(ownership_grid[y][x]))
Rectangle(pos=(self.gridpos_x[x] - rsz / 2, self.gridpos_y[y] - rsz / 2), size=(rsz, rsz))
if (
current_node.children
and katrain.controls.status_state[1] == STATUS_TEACHING
and current_node.children[-1].auto_undo
and current_node.children[-1].ownership
): # loss
loss_grid = var_to_grid(
[a - b for a, b in zip(current_node.children[-1].ownership, ownership)],
(board_size_x, board_size_y),
)
for y in range(board_size_y - 1, -1, -1):
for x in range(board_size_x):
loss = max(0, (-1 if current_node.children[-1].move.player == "B" else 1) * loss_grid[y][x])
if loss > 0:
Color(*EVAL_COLORS[self.trainer_config["theme"]][1][:3], loss)
Rectangle(
pos=(self.gridpos_x[x] - rsz / 2, self.gridpos_y[y] - rsz / 2), size=(rsz, rsz)
)
else:
ownership_grid = var_to_grid(ownership, (board_size_x, board_size_y))
for y in range(board_size_y - 1, -1, -1):
for x in range(board_size_x):
ix_owner = "B" if ownership_grid[y][x] > 0 else "W"
if ix_owner != (has_stone.get((x, y), -1)):
Color(*STONE_COLORS[ix_owner][:3], abs(ownership_grid[y][x]))
Rectangle(
pos=(self.gridpos_x[x] - rsz / 2, self.gridpos_y[y] - rsz / 2), size=(rsz, rsz)
)
policy = current_node.policy
if (
@@ -515,11 +533,19 @@ class BadukPanWidget(Widget):
draw_text(pos=board_coords, text=str(i + 1), font_size=self.grid_size * sizefac / 1.45, font_name="Roboto")
def set_animating_pv(self, pv, node):
if pv == None:
self.animating_pv = None
if node is not None and (
not self.animating_pv or not (self.animating_pv[0] == pv and self.animating_pv[1] == node)
):
self.animating_pv = (pv, node, time.time(), self.last_mouse_pos)
if self.katrain.controls.status_state[1] == STATUS_TEACHING and self.katrain.analysis_controls.ownership.active:
self.draw_board_contents() # loss visualization
else:
self.draw_hover_contents()
def show_pv_from_comments(self, pv_str):
self.set_animating_pv(pv_str[1:].split(" "), self.katrain.controls.active_comment_node.parent)
katrain/gui/popups.py
+12 -9
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@@ -445,17 +445,19 @@ class ConfigPopup(QuickConfigGui):
KATAGOS = {
"win": {
"Official OpenCL v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-gpu-opencl-windows-x64.zip",
"Official OpenCL v1.6.0 (32 bit)": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-gpu-opencl-windows-x32-dont-use-unless-actually-32bit-windows.zip",
"Official CUDA v1.6.0 (New NVIDIA cards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-gpu-cuda10.2-windows-x64.zip",
"Eigen AVX2 (Modern CPUs) v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-cpu-eigen-avx2-windows-x64.zip",
"Eigen (CPU, Non-optimized) v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-cpu-eigen-windows-x64.zip",
"OpenCL v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-gpu-opencl-windows-x64.zip",
"OpenCL v1.6.1 (32 bit)": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-gpu-opencl-windows-x32-dont-use-unless-actually-32bit-windows.zip",
"CUDA v1.6.1 (New NVIDIA cards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-gpu-cuda10.2-windows-x64.zip",
"Eigen AVX2 (Modern CPUs) v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-cpu-eigen-avx2-windows-x64.zip",
"Eigen (CPU, Non-optimized) v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-cpu-eigen-windows-x64.zip",
"OpenCL v1.6.1 (bigger boards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.1%2Bbs29/katago-v1.6.1+bs29-gpu-opencl-windows-x64.zip",
},
"linux": {
"Official OpenCL v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-gpu-opencl-linux-x64.zip",
"Official CUDA v1.6.0 (New NVIDIA cards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-gpu-cuda10.2-linux-x64.zip",
"Eigen AVX2 (Modern CPUs) v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-cpu-eigen-avx2-linux-x64.zip",
"Eigen (CPU, Non-optimized) v1.6.0": "https://github.com/lightvector/KataGo/releases/download/v1.6.0/katago-v1.6.0-cpu-eigen-linux-x64.zip",
"OpenCL v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-gpu-opencl-linux-x64.zip",
"CUDA v1.6.1 (New NVIDIA cards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-gpu-cuda10.2-linux-x64.zip",
"Eigen AVX2 (Modern CPUs) v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-cpu-eigen-avx2-linux-x64.zip",
"Eigen (CPU, Non-optimized) v1.6.1": "https://github.com/lightvector/KataGo/releases/download/v1.6.1/katago-v1.6.1-cpu-eigen-linux-x64.zip",
"OpenCL v1.6.1 (bigger boards)": "https://github.com/lightvector/KataGo/releases/download/v1.6.1%2Bbs29/katago-v1.6.1+bs29-gpu-opencl-linux-x64.zip",
},
}
@@ -525,6 +527,7 @@ class ConfigPopup(QuickConfigGui):
if f.lower().endswith("dll"):
with open(os.path.join(os.path.split(path)[0], f), "wb") as fout:
fout.write(zipObj.read(f))
os.remove(tmp_path)
else:
os.rename(tmp_path, path)
self.katrain.log(f"Download of katago binary {binary} model complete -> {path}", OUTPUT_INFO)