1.6.1

katrain/KataGo/analysis_config.cfg

@@ -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/gui/badukpan.py

@@ -10,7 +10,7 @@ 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
@@ -308,26 +308,36 @@ class BadukPanWidget(Widget):
             # 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
                 if (
                     current_node.children
                     and katrain.controls.status_state[1] == STATUS_TEACHING
-                    and self.animating_pv
                     and current_node.children[-1].auto_undo
                     and current_node.children[-1].ownership
-                ):
-                    ownership_grid = var_to_grid(
+                ):  # 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),
                     )
 
-                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))
+                    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 (
@@ -531,8 +541,8 @@ class BadukPanWidget(Widget):
         ):
             self.animating_pv = (pv, node, time.time(), self.last_mouse_pos)
 
-        if self.katrain.controls.status_state[1] == STATUS_TEACHING:
-            self.draw_board_contents()
+        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()
 

katrain/gui/popups.py

@@ -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)