bump 2.1.0 (#891)

* style: add python lint & pre-commit

* style: use pre-commit to lint fe codes

* fix: show raw shape of tensor in high-dimensional chart

* feat: implement random sampling in high-dimensional chart

* feat: add fog in scatter chart

* feat: focus hovered point in high-dimensional chart

* chore: hide unfulfilled features

* chore: update dependencies

* fix: fix lost import

* style: fix style lint

* chore: fix typo

* bump 2.1.0

.eslint_format.hook

-#!/bin/bash
-
-set -e
-
-(cd frontend && npm run lint)
-RESULT=$?
-
-[ $RESULT -ne 0 ] && exit 1
-exit 0

.flake8

 [flake8]
-max-line-length = 120
+extend-exclude = venv,build,dist,frontend,visualdl/proto/record_pb2.py,visualdl/server/dist
\ No newline at end of file
+max-line-length = 120
+max-doc-length = 120
+max-complexity = 15

.github/workflows/lint.yml

@@ -32,7 +32,7 @@ jobs:
           python-version: '3.8'
       - name: Install requirements
         run: |
-          echo "TODO"
+          pip install --disable-pip-version-check flake8
       - name: Lint
         run: |
-          echo "TODO"
+          flake8

.pre-commit-config.yaml

--   repo: https://github.com/pre-commit/mirrors-yapf.git
-    sha: v0.16.0
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.4.0
     hooks:
-    -   id: yapf
-        files: \.py$
-
--   repo: https://github.com/pre-commit/pre-commit-hooks
-    sha: a11d9314b22d8f8c7556443875b731ef05965464
+      - id: check-added-large-files
+      - id: check-case-conflict
+      - id: check-executables-have-shebangs
+      - id: check-merge-conflict
+      - id: check-json
+      - id: check-toml
+      - id: check-yaml
+      - id: check-symlinks
+      - id: destroyed-symlinks
+  - repo: https://gitlab.com/pycqa/flake8
+    rev: 3.8.4
     hooks:
-    -   id: check-merge-conflict
-    -   id: check-symlinks
-    -   id: end-of-file-fixer
-    -   id: trailing-whitespace
-    -   id: detect-private-key
-    -   id: check-symlinks
-    -   id: check-added-large-files
-
-
--   repo: local
+      - id: flake8
+        alias: be
+        exclude: ^frontend/
+  - repo: local
     hooks:
-    -   id: python-format-checker
-        name: python-format-checker
-        description: Format python files using PEP8 standard
-        entry: flake8
-        language: system
-        files: \.(py)$
-
--   repo: local
+      - id: fe
+        name: lint-staged
+        entry: cd frontend && lint-staged
+        language: node
+        files: ^frontend/
+        pass_filenames: false
+        description: lint frontend code by lint-staged
+  - repo: meta
     hooks:
-    -   id: eslint-format-checker
-        name: eslint-format-checker
-        description: Format files with ESLint.
-        entry: bash ./.eslint_format.hook
-        language: system
+      - id: check-hooks-apply
+      - id: check-useless-excludes

demo/components/audio_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 from visualdl import LogWriter
 from scipy.io import wavfile
 

demo/components/high_dimensional_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 from visualdl import LogWriter
 
 

demo/components/histogram_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 from visualdl import LogWriter
 import numpy as np
 

demo/components/image_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 import numpy as np
 from PIL import Image
 from visualdl import LogWriter

demo/components/pr_curve_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 from visualdl import LogWriter
 import numpy as np
 

demo/components/roc_curve_test.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 # coding=utf-8
+
 from visualdl import LogWriter
 import numpy as np
 
@@ -21,7 +23,7 @@ with LogWriter("./log/roc_curve_test/train") as writer:
         labels = np.random.randint(2, size=100)
         predictions = np.random.rand(100)
         writer.add_roc_curve(tag='roc_curve',
-                            labels=labels,
-                            predictions=predictions,
-                            step=step,
-                            num_thresholds=5)
+                             labels=labels,
+                             predictions=predictions,
+                             step=step,
+                             num_thresholds=5)

demo/components/scalar_test.py

@@ -12,6 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
+# coding=utf-8
+
 from visualdl import LogWriter
 
 if __name__ == '__main__':
@@ -20,4 +23,3 @@ if __name__ == '__main__':
         for step in range(1000):
             writer.add_scalar(tag="acc", step=step, value=value[step])
             writer.add_scalar(tag="loss", step=step, value=1/(value[step] + 1))
-

frontend/.prettierignore

@@ -2,3 +2,4 @@ dist
 out
 wasm
 output
+license-header.js

frontend/README.md

@@ -39,7 +39,7 @@ To stop VisualDL server, just type
 visualdl stop
 ```
 
-For more usage infomation, please type
+For more usage information, please type
 
 ```bash
 visualdl -h

frontend/lerna.json

@@ -2,7 +2,7 @@
     "packages": [
         "packages/*"
     ],
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "npmClient": "yarn",
     "useWorkspaces": true,
     "command": {

frontend/package.json

@@ -38,15 +38,14 @@
         "version": "yarn format && git add -A"
     },
     "devDependencies": {
-        "@typescript-eslint/eslint-plugin": "4.10.0",
-        "@typescript-eslint/parser": "4.10.0",
-        "eslint": "7.15.0",
-        "eslint-config-prettier": "7.0.0",
+        "@typescript-eslint/eslint-plugin": "4.11.0",
+        "@typescript-eslint/parser": "4.11.0",
+        "eslint": "7.16.0",
+        "eslint-config-prettier": "7.1.0",
         "eslint-plugin-license-header": "0.2.0",
         "eslint-plugin-prettier": "3.3.0",
         "eslint-plugin-react": "7.21.5",
         "eslint-plugin-react-hooks": "4.2.0",
-        "husky": "4.3.6",
         "lerna": "3.22.1",
         "lint-staged": "10.5.3",
         "prettier": "2.2.1",
@@ -57,10 +56,5 @@
     "engines": {
         "node": ">=10",
         "npm": ">=6"
-    },
-    "husky": {
-        "hooks": {
-            "pre-commit": "lint-staged"
-        }
     }
 }

frontend/packages/cli/package.json

 {
     "name": "@visualdl/cli",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -34,14 +34,14 @@
         "dist"
     ],
     "dependencies": {
-        "@visualdl/server": "2.0.9",
+        "@visualdl/server": "2.1.0-1",
         "open": "7.3.0",
         "ora": "5.1.0",
-        "pm2": "4.5.0",
+        "pm2": "4.5.1",
         "yargs": "16.2.0"
     },
     "devDependencies": {
-        "@types/node": "14.14.14",
+        "@types/node": "14.14.16",
         "@types/yargs": "15.0.12",
         "cross-env": "7.0.3",
         "ts-node": "9.1.1",

frontend/packages/core/package.json

 {
     "name": "@visualdl/core",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -35,13 +35,13 @@
     ],
     "dependencies": {
         "@tippyjs/react": "4.2.0",
-        "@visualdl/netron": "2.0.9",
-        "@visualdl/wasm": "2.0.9",
+        "@visualdl/netron": "2.1.0-1",
+        "@visualdl/wasm": "2.1.0-1",
         "bignumber.js": "9.0.1",
         "d3": "6.3.1",
         "d3-format": "2.0.0",
         "echarts": "4.9.0",
-        "echarts-gl": "1.1.1",
+        "echarts-gl": "1.1.2",
         "eventemitter3": "4.0.7",
         "file-saver": "2.0.5",
         "i18next": "19.8.4",
@@ -68,8 +68,8 @@
         "react-toastify": "6.2.0",
         "redux": "4.0.5",
         "styled-components": "5.2.1",
-        "swr": "0.3.9",
-        "three": "0.123.0",
+        "swr": "0.3.11",
+        "three": "0.124.0",
         "tippy.js": "6.2.7",
         "umap-js": "1.3.3"
     },
@@ -93,7 +93,7 @@
         "@types/file-saver": "2.0.1",
         "@types/jest": "26.0.19",
         "@types/loadable__component": "5.13.1",
-        "@types/lodash": "4.14.165",
+        "@types/lodash": "4.14.166",
         "@types/mime-types": "2.1.0",
         "@types/nprogress": "0.2.0",
         "@types/numeric": "1.2.1",
@@ -101,20 +101,20 @@
         "@types/react-dom": "17.0.0",
         "@types/react-helmet": "6.1.0",
         "@types/react-rangeslider": "2.2.3",
-        "@types/react-redux": "7.1.12",
+        "@types/react-redux": "7.1.14",
         "@types/react-router-dom": "5.1.6",
-        "@types/snowpack-env": "2.3.2",
-        "@types/styled-components": "5.1.5",
-        "@visualdl/mock": "2.0.9",
+        "@types/snowpack-env": "2.3.3",
+        "@types/styled-components": "5.1.7",
+        "@visualdl/mock": "2.1.0-1",
         "babel-plugin-styled-components": "1.12.0",
         "dotenv": "8.2.0",
-        "enhanced-resolve": "5.4.0",
+        "enhanced-resolve": "5.4.1",
         "express": "4.17.1",
         "fs-extra": "9.0.1",
         "html-minifier": "4.0.0",
         "http-proxy-middleware": "1.0.6",
         "jest": "26.6.3",
-        "snowpack": "2.18.4",
+        "snowpack": "2.18.5",
         "typescript": "4.0.5",
         "yargs": "16.2.0"
     },

frontend/packages/core/src/components/HighDimensionalPage/ChartOperations.tsx

@@ -77,7 +77,7 @@ const ChartOperations: FunctionComponent<ChartOperationsProps> = ({onReset}) =>
 
     return (
         <Operations>
-            <Tippy content={t('high-dimensional:selection')} placement="bottom" theme="tooltip">
+            {/* <Tippy content={t('high-dimensional:selection')} placement="bottom" theme="tooltip">
                 <a>
                     <span>
                         <Icon type="selection" />
@@ -90,7 +90,7 @@ const ChartOperations: FunctionComponent<ChartOperationsProps> = ({onReset}) =>
                         <Icon type="three-d" />
                     </span>
                 </a>
-            </Tippy>
+            </Tippy> */}
             <Tippy content={t('high-dimensional:reset-zoom')} placement="bottom" theme="tooltip">
                 <a onClick={() => onReset?.()}>
                     <span>

frontend/packages/core/src/components/HighDimensionalPage/HighDimensionalChart.tsx

@@ -14,12 +14,12 @@
  * limitations under the License.
  */
 
-import type {CalculateParams, CalculateResult, Reduction} from '~/resource/high-dimensional';
+import type {CalculateParams, CalculateResult, Reduction, Shape} from '~/resource/high-dimensional';
 import React, {useCallback, useEffect, useImperativeHandle, useLayoutEffect, useMemo, useRef, useState} from 'react';
 import ScatterChart, {ScatterChartRef} from '~/components/ScatterChart';
 
 import ChartOperations from '~/components/HighDimensionalPage/ChartOperations';
-import type {InfoData} from '~/worker/high-dimensional/tsne';
+import type {InfoData} from '~/worker/high-dimensional/calculate';
 import type {WithStyled} from '~/utils/style';
 import {rem} from '~/utils/style';
 import styled from 'styled-components';
@@ -67,12 +67,14 @@ const Chart = styled.div`
 type HighDimensionalChartProps = {
     vectors: Float32Array;
     labels: string[];
+    shape: Shape;
     dim: number;
     is3D: boolean;
     reduction: Reduction;
     perplexity: number;
     learningRate: number;
     neighbors: number;
+    focusedIndices?: number[];
     highlightIndices?: number[];
     onCalculate?: () => unknown;
     onCalculated?: (data: CalculateResult) => unknown;
@@ -91,12 +93,14 @@ const HighDimensionalChart = React.forwardRef<HighDimensionalChartRef, HighDimen
         {
             vectors,
             labels,
+            shape,
             dim,
             is3D,
             reduction,
             perplexity,
             learningRate,
             neighbors,
+            focusedIndices,
             highlightIndices,
             onCalculate,
             onCalculated,
@@ -113,8 +117,6 @@ const HighDimensionalChart = React.forwardRef<HighDimensionalChartRef, HighDimen
         const [width, setWidth] = useState(0);
         const [height, setHeight] = useState(0);
 
-        const points = useMemo(() => Math.floor(vectors.length / dim), [vectors, dim]);
-
         useLayoutEffect(() => {
             const c = chartElement.current;
             if (c) {
@@ -251,11 +253,11 @@ const HighDimensionalChart = React.forwardRef<HighDimensionalChartRef, HighDimen
                     <div className="info">
                         {t('high-dimensional:points')}
                         {t('common:colon')}
-                        {points}
+                        {shape[0]}
                         <span className="sep"></span>
                         {t('high-dimensional:data-dimension')}
                         {t('common:colon')}
-                        {dim}
+                        {shape[1]}
                     </div>
                     <ChartOperations onReset={() => chart.current?.reset()} />
                 </Toolbar>
@@ -268,7 +270,8 @@ const HighDimensionalChart = React.forwardRef<HighDimensionalChartRef, HighDimen
                         labels={labels}
                         is3D={is3D}
                         rotate={reduction !== 'tsne'}
-                        highlightIndices={highlightIndices ?? []}
+                        focusedIndices={focusedIndices}
+                        highlightIndices={highlightIndices}
                     />
                 </Chart>
             </Wrapper>

frontend/packages/core/src/components/HighDimensionalPage/LabelSearchResult.tsx

@@ -63,19 +63,20 @@ const List = styled.ul`
 
 type LabelSearchResultProps = {
     list: string[];
+    onHovered?: (index?: number) => unknown;
 };
 
-const LabelSearchResult: FunctionComponent<LabelSearchResultProps> = ({list}) => {
+const LabelSearchResult: FunctionComponent<LabelSearchResultProps> = ({list, onHovered}) => {
     const {t} = useTranslation('high-dimensional');
 
     if (!list.length) {
         return <Empty>{t('high-dimensional:search-empty')}</Empty>;
     }
     return (
-        <List>
+        <List onMouseLeave={() => onHovered?.()}>
             {list.map((label, index) => (
                 <li key={index}>
-                    <a>{label}</a>
+                    <a onMouseEnter={() => onHovered?.(index)}>{label}</a>
                 </li>
             ))}
         </List>

frontend/packages/core/src/components/SamplePage/SampleChart.tsx

@@ -198,7 +198,7 @@ const SampleChart: FunctionComponent<SampleChartProps> = ({
 
     // clear cache if tag or run changed
     useEffect(() => {
-        Object.values(cached.current).forEach(({timer}) => clearTimeout(timer));
+        Object.values(cached.current).forEach(({timer}) => window.clearTimeout(timer));
         cached.current = {};
     }, [tag, run]);
 
@@ -211,7 +211,7 @@ const SampleChart: FunctionComponent<SampleChartProps> = ({
         const url = getUrl(type, step, run.label, tag, wallTime);
         cached.current[step] = {
             src: url,
-            timer: setTimeout(() => {
+            timer: window.setTimeout(() => {
                 ((s: number) => delete cached.current[s])(step);
             }, cache)
         };
@@ -227,10 +227,10 @@ const SampleChart: FunctionComponent<SampleChartProps> = ({
             // first load, return immediately
             cacheSrc();
         } else {
-            timer.current = setTimeout(cacheSrc, 500);
+            timer.current = window.setTimeout(cacheSrc, 500);
             return () => {
                 if (timer.current != null) {
-                    clearTimeout(timer.current);
+                    window.clearTimeout(timer.current);
                     timer.current = null;
                 }
             };

frontend/packages/core/src/components/ScatterChart/Component.tsx

@@ -36,7 +36,8 @@ export type ScatterChartProps = {
     labels: string[];
     is3D: boolean;
     rotate?: boolean;
-    highlightIndices: number[];
+    focusedIndices?: number[];
+    highlightIndices?: number[];
 };
 
 export type ScatterChartRef = {
@@ -44,7 +45,7 @@ export type ScatterChartRef = {
 };
 
 const ScatterChart = React.forwardRef<ScatterChartRef, ScatterChartProps & WithStyled>(
-    ({width, height, data, labels, is3D, rotate, highlightIndices, className}, ref) => {
+    ({width, height, data, labels, is3D, rotate, focusedIndices, highlightIndices, className}, ref) => {
         const theme = useTheme();
 
         const element = useRef<HTMLDivElement>(null);
@@ -77,7 +78,11 @@ const ScatterChart = React.forwardRef<ScatterChartRef, ScatterChartProps & WithS
         }, [data, labels]);
 
         useEffect(() => {
-            chart.current?.setHighLightIndices(highlightIndices);
+            chart.current?.setFocusedPointIndices(focusedIndices ?? []);
+        }, [focusedIndices]);
+
+        useEffect(() => {
+            chart.current?.setHighLightIndices(highlightIndices ?? []);
         }, [highlightIndices]);
 
         useEffect(() => {

frontend/packages/core/src/components/ScatterChart/ScatterChart.ts

@@ -103,11 +103,15 @@ export default class ScatterChart {
     static ORBIT_ANIMATION_ROTATION_CYCLE_IN_SECONDS = 2;
     static NUM_POINTS_FOG_THRESHOLD = 5000;
 
-    static POINT_COLOR_NO_SELECTION = 0x7e7e7e;
-    static POINT_COLOR_HOVER = 0x2932e1;
+    static POINT_COLOR_DEFAULT = new THREE.Color(0x7e7e7e);
+    static POINT_COLOR_HOVER = new THREE.Color(0x2932e1);
+    static POINT_COLOR_HIGHLIGHT = new THREE.Color(0x2932e1);
+    static POINT_COLOR_FOCUS = new THREE.Color(0x2932e1);
 
     static POINT_SCALE_DEFAULT = 1.0;
     static POINT_SCALE_HOVER = 1.2;
+    static POINT_SCALE_HIGHLIGHT = 1.0;
+    static POINT_SCALE_FOCUS = 1.2;
 
     static PERSP_CAMERA_INIT_POSITION: Point3D = [0.45, 0.9, 1.6];
     static ORTHO_CAMERA_INIT_POSITION: Point3D = [0, 0, 4];
@@ -124,6 +128,7 @@ export default class ScatterChart {
     private renderer: THREE.WebGLRenderer;
     private camera: THREE.OrthographicCamera | THREE.PerspectiveCamera;
     private controls: OrbitControls;
+    private fog: THREE.Fog;
     private pickingTexture: THREE.WebGLRenderTarget;
     private geometry: THREE.BufferGeometry;
     private renderMaterial: THREE.ShaderMaterial | null = null;
@@ -134,6 +139,7 @@ export default class ScatterChart {
     private scaleFactors: Float32Array | null = null;
     private axes: THREE.AxesHelper | null = null;
     private points: THREE.Points | null = null;
+    private focusedPointIndices: number[] = [];
     private hoveredPointIndices: number[] = [];
     private label: ScatterChartLabel;
     private highLightPointIndices: number[] = [];
@@ -163,6 +169,7 @@ export default class ScatterChart {
         this.camera = this.initCamera();
         this.renderer = this.initRenderer();
         this.controls = this.initControls();
+        this.fog = this.initFog();
         this.pickingTexture = this.initRenderTarget();
         this.geometry = this.createGeometry();
 
@@ -190,7 +197,6 @@ export default class ScatterChart {
         const light = new THREE.PointLight(16772287, 1, 0);
         light.name = 'light';
         scene.add(light);
-        scene.fog = new THREE.Fog(0xffffff);
         return scene;
     }
 
@@ -255,6 +261,10 @@ export default class ScatterChart {
         return controls;
     }
 
+    private initFog() {
+        return new THREE.Fog(this.background);
+    }
+
     private initRenderTarget() {
         const renderCanvasSize = new THREE.Vector2();
         this.renderer.getSize(renderCanvasSize);
@@ -355,17 +365,23 @@ export default class ScatterChart {
         const count = this.data.length;
         const colors = new Float32Array(count * 3);
         let dst = 0;
-        const color = new THREE.Color(ScatterChart.POINT_COLOR_NO_SELECTION);
-        const hoveredColor = new THREE.Color(ScatterChart.POINT_COLOR_HOVER);
         for (let i = 0; i < count; i++) {
-            if (i === this.hoveredPointIndices[0] || this.highLightPointIndices.includes(i)) {
-                colors[dst++] = hoveredColor.r;
-                colors[dst++] = hoveredColor.g;
-                colors[dst++] = hoveredColor.b;
+            if (this.hoveredPointIndices.includes(i)) {
+                colors[dst++] = ScatterChart.POINT_COLOR_HOVER.r;
+                colors[dst++] = ScatterChart.POINT_COLOR_HOVER.g;
+                colors[dst++] = ScatterChart.POINT_COLOR_HOVER.b;
+            } else if (this.focusedPointIndices.includes(i)) {
+                colors[dst++] = ScatterChart.POINT_COLOR_FOCUS.r;
+                colors[dst++] = ScatterChart.POINT_COLOR_FOCUS.g;
+                colors[dst++] = ScatterChart.POINT_COLOR_FOCUS.b;
+            } else if (this.highLightPointIndices.includes(i)) {
+                colors[dst++] = ScatterChart.POINT_COLOR_HIGHLIGHT.r;
+                colors[dst++] = ScatterChart.POINT_COLOR_HIGHLIGHT.g;
+                colors[dst++] = ScatterChart.POINT_COLOR_HIGHLIGHT.b;
             } else {
-                colors[dst++] = color.r;
-                colors[dst++] = color.g;
-                colors[dst++] = color.b;
+                colors[dst++] = ScatterChart.POINT_COLOR_DEFAULT.r;
+                colors[dst++] = ScatterChart.POINT_COLOR_DEFAULT.g;
+                colors[dst++] = ScatterChart.POINT_COLOR_DEFAULT.b;
             }
         }
         return colors;
@@ -375,8 +391,12 @@ export default class ScatterChart {
         const count = this.data.length;
         const scaleFactor = new Float32Array(count);
         for (let i = 0; i < count; i++) {
-            if (i === this.hoveredPointIndices[0]) {
+            if (this.hoveredPointIndices.includes(i)) {
                 scaleFactor[i] = ScatterChart.POINT_SCALE_HOVER;
+            } else if (this.focusedPointIndices.includes(i)) {
+                scaleFactor[i] = ScatterChart.POINT_SCALE_FOCUS;
+            } else if (this.highLightPointIndices.includes(i)) {
+                scaleFactor[i] = ScatterChart.POINT_SCALE_HIGHLIGHT;
             } else {
                 scaleFactor[i] = ScatterChart.POINT_SCALE_DEFAULT;
             }
@@ -441,21 +461,26 @@ export default class ScatterChart {
     }
 
     private updateHoveredLabels() {
-        if (this.hoveredPointIndices[0] == null || !this.camera || !this.positions) {
+        if (!this.camera || !this.positions) {
+            return;
+        }
+
+        const indices = this.focusedPointIndices.length ? this.focusedPointIndices : this.hoveredPointIndices;
+        if (!indices.length) {
             this.label.clear();
             return;
         }
+
         const dpr = window.devicePixelRatio || 1;
         const w = this.width;
         const h = this.height;
-        const index = this.hoveredPointIndices[0];
-        const pi = index * 3;
-        // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
-        const point = new THREE.Vector3(this.positions![pi], this.positions![pi + 1], this.positions![pi + 2]);
-        const pv = new THREE.Vector3().copy(point).project(this.camera);
-        const coord: Point2D = [((pv.x + 1) / 2) * w * dpr, -(((pv.y - 1) / 2) * h) * dpr];
-        const labels = [
-            {
+        const labels = indices.map(index => {
+            const pi = index * 3;
+            // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
+            const point = new THREE.Vector3(this.positions![pi], this.positions![pi + 1], this.positions![pi + 2]);
+            const pv = new THREE.Vector3().copy(point).project(this.camera);
+            const coord: Point2D = [((pv.x + 1) / 2) * w * dpr, -(((pv.y - 1) / 2) * h) * dpr];
+            return {
                 text: this.labels[index] ?? '',
                 fontSize: 40,
                 fillColor: '#000',
@@ -463,12 +488,75 @@ export default class ScatterChart {
                 opacity: 1,
                 x: coord[0] + 4,
                 y: coord[1]
-            }
-        ];
+            };
+        });
 
         this.label.render(labels);
     }
 
+    private updateLight() {
+        const light = this.scene.getObjectByName('light') as THREE.PointLight;
+        const cameraPos = this.camera.position;
+        const lightPos = cameraPos.clone();
+        lightPos.x += 1;
+        lightPos.y += 1;
+        light.position.set(lightPos.x, lightPos.y, lightPos.z);
+    }
+
+    private updateFog() {
+        const fog = this.fog;
+
+        fog.color = new THREE.Color(this.background);
+
+        if (this.is3D && this.positions) {
+            const cameraPos = this.camera.position;
+            const cameraTarget = this.controls.target;
+
+            let shortestDist = Number.POSITIVE_INFINITY;
+            let furthestDist = 0;
+
+            const camToTarget = new THREE.Vector3().copy(cameraTarget).sub(cameraPos);
+            const camPlaneNormal = new THREE.Vector3().copy(camToTarget).normalize();
+
+            const n = this.positions.length / 3;
+            let src = 0;
+            const p = new THREE.Vector3();
+            const camToPoint = new THREE.Vector3();
+            for (let i = 0; i < n; i++) {
+                p.x = this.positions[src++];
+                p.y = this.positions[src++];
+                p.z = this.positions[src++];
+
+                camToPoint.copy(p).sub(cameraPos);
+                const dist = camPlaneNormal.dot(camToPoint);
+                if (dist < 0) {
+                    continue;
+                }
+
+                furthestDist = dist > furthestDist ? dist : furthestDist;
+                shortestDist = dist < shortestDist ? dist : shortestDist;
+            }
+
+            const multiplier =
+                2 - Math.min(n, ScatterChart.NUM_POINTS_FOG_THRESHOLD) / ScatterChart.NUM_POINTS_FOG_THRESHOLD;
+
+            fog.near = shortestDist;
+            fog.far = furthestDist * multiplier;
+        } else {
+            fog.near = Number.POSITIVE_INFINITY;
+            fog.far = Number.POSITIVE_INFINITY;
+        }
+
+        if (this.points) {
+            const material = this.points.material as THREE.ShaderMaterial;
+            material.uniforms.fogColor.value = fog.color;
+            material.uniforms.fogNear.value = fog.near;
+            material.uniforms.fogFar.value = fog.far;
+        }
+
+        this.scene.fog = fog;
+    }
+
     private bindEventListeners() {
         this.canvas?.addEventListener('mousemove', this.onMouseMoveBindThis);
     }
@@ -498,55 +586,13 @@ export default class ScatterChart {
     }
 
     private render() {
-        const light = this.scene.getObjectByName('light') as THREE.PointLight;
-        const cameraPos = this.camera.position;
-        const lightPos = cameraPos.clone();
-        lightPos.x += 1;
-        lightPos.y += 1;
-        light.position.set(lightPos.x, lightPos.y, lightPos.z);
-
-        // TODO: remake fog
-        // const fog = this.scene.fog as THREE.Fog | null;
-        // if (fog) {
-        //     if (this.is3D) {
-        //         const cameraTarget = this.controls.target ?? new THREE.Vector3();
-        //         let shortestDist = Number.POSITIVE_INFINITY;
-        //         let furthestDist = 0;
-        //         const camToTarget = new THREE.Vector3().copy(cameraTarget).sub(cameraPos);
-        //         const camPlaneNormal = new THREE.Vector3().copy(camToTarget).normalize();
-
-        //         const camToPoint = new THREE.Vector3();
-        //         this.data.forEach(d => {
-        //             camToPoint.copy(new THREE.Vector3(...d)).sub(cameraPos);
-        //             const dist = camPlaneNormal.dot(camToPoint);
-        //             if (dist < 0) {
-        //                 return;
-        //             }
-        //             furthestDist = dist > furthestDist ? dist : furthestDist;
-        //             shortestDist = dist < shortestDist ? dist : shortestDist;
-        //         });
-        //         const multiplier =
-        //             2 -
-        //             Math.min(this.data.length, ScatterChart.NUM_POINTS_FOG_THRESHOLD) /
-        //                 ScatterChart.NUM_POINTS_FOG_THRESHOLD;
-        //         fog.near = shortestDist;
-        //         fog.far = furthestDist * multiplier;
-        //     } else {
-        //         fog.near = Number.POSITIVE_INFINITY;
-        //         fog.far = Number.POSITIVE_INFINITY;
-        //     }
-        //     console.log(fog.near, fog.far, fog.color);
-        //     if (this.points) {
-        //         const material = this.points.material as THREE.ShaderMaterial;
-        //         material.uniforms.fogColor.value = fog.color;
-        //         material.uniforms.fogNear.value = fog.near;
-        //         material.uniforms.fogFar.value = fog.far;
-        //     }
-        // }
+        this.updateLight();
+        this.updateFog();
 
         this.updateHoveredPoints();
         this.updateHoveredLabels();
         this.updatePointsAttribute();
+
         if (this.pickingMaterial) {
             if (this.axes) {
                 this.scene.remove(this.axes);
@@ -659,6 +705,7 @@ export default class ScatterChart {
 
     setLabels(labels: string[]) {
         this.labels = labels;
+        this.render();
     }
 
     setHighLightIndices(highLightIndices: number[]) {
@@ -666,6 +713,11 @@ export default class ScatterChart {
         this.render();
     }
 
+    setFocusedPointIndices(focusedPointIndices: number[]) {
+        this.focusedPointIndices = focusedPointIndices;
+        this.render();
+    }
+
     dispose() {
         this.removeEventListeners();
         this.label.dispose();

frontend/packages/core/src/pages/high-dimensional.tsx

@@ -21,6 +21,7 @@ import type {
     ParseParams,
     ParseResult,
     Reduction,
+    Shape,
     TSNEResult,
     UMAPResult
 } from '~/resource/high-dimensional';
@@ -180,6 +181,7 @@ const HighDimensional: FunctionComponent = () => {
     const [metadata, setMetadata] = useState<string[][]>([]);
     // dimension of data
     const [dim, setDim] = useState<number>(0);
+    const [rawShape, setRawShape] = useState<Shape>([0, 0]);
     const getLabelByLabels = useCallback(
         (value: string | undefined) => {
             if (value != null) {
@@ -272,6 +274,7 @@ const HighDimensional: FunctionComponent = () => {
         if (error) {
             showError(error);
         } else if (data) {
+            setRawShape(data.rawShape);
             setDim(data.dimension);
             setVectors(data.vectors);
             setLabels(data.labels);
@@ -339,6 +342,12 @@ const HighDimensional: FunctionComponent = () => {
         };
     }, [getLabelByLabels, searchResult.labelBy, searchResult.value]);
 
+    const [hoveredIndices, setHoveredIndices] = useState<number[]>([]);
+    const hoverSearchResult = useCallback(
+        (index?: number) => setHoveredIndices(index == null ? [] : [searchedResult.indices[index]]),
+        [searchedResult.indices]
+    );
+
     const detail = useMemo(() => {
         switch (reduction) {
             case 'pca':
@@ -385,11 +394,9 @@ const HighDimensional: FunctionComponent = () => {
                     <Field label={t('high-dimensional:select-label')}>
                         <FullWidthSelect list={labels} value={labelBy} onChange={setLabelBy} />
                     </Field>
-                    {metadataFile && (
-                        <Field label={t('high-dimensional:select-color')}>
-                            <FullWidthSelect />
-                        </Field>
-                    )}
+                    {/* <Field label={t('high-dimensional:select-color')}>
+                        <FullWidthSelect />
+                    </Field> */}
                     <Field>
                         <FullWidthButton rounded outline type="primary" onClick={() => setUploadModal(true)}>
                             {t('high-dimensional:upload-data')}
@@ -416,7 +423,7 @@ const HighDimensional: FunctionComponent = () => {
                 </AsideSection>
             </RightAside>
         ),
-        [t, dataPath, reduction, dimension, metadataFile, labels, labelBy, embeddingList, selectedEmbeddingName, detail]
+        [t, dataPath, reduction, dimension, labels, labelBy, embeddingList, selectedEmbeddingName, detail]
     );
 
     const leftAside = useMemo(
@@ -438,12 +445,12 @@ const HighDimensional: FunctionComponent = () => {
                 </AsideSection>
                 <AsideSection className="search-result">
                     <Field>
-                        <LabelSearchResult list={searchedResult.metadata} />
+                        <LabelSearchResult list={searchedResult.metadata} onHovered={hoverSearchResult} />
                     </Field>
                 </AsideSection>
             </LeftAside>
         ),
-        [labels, searchResult.value, searchedResult.metadata, t]
+        [hoverSearchResult, labels, searchResult.value, searchedResult.metadata, t]
     );
 
     return (
@@ -456,12 +463,14 @@ const HighDimensional: FunctionComponent = () => {
                         ref={chart}
                         vectors={vectors}
                         labels={labelByLabels}
+                        shape={rawShape}
                         dim={dim}
                         is3D={is3D}
                         reduction={reduction}
                         perplexity={perplexity}
                         learningRate={learningRate}
                         neighbors={neighbors}
+                        focusedIndices={hoveredIndices}
                         highlightIndices={searchedResult.indices}
                         onCalculate={calculate}
                         onCalculated={calculated}

frontend/packages/core/src/resource/high-dimensional/index.ts

@@ -23,6 +23,7 @@ export type {
     PCAParams,
     PCAResult,
     Reduction,
+    Shape,
     TSNEParams,
     TSNEResult,
     UMAPParams,

frontend/packages/core/src/resource/high-dimensional/parser.ts

@@ -14,7 +14,14 @@
  * limitations under the License.
  */
 
-import type {MetadataResult, ParseFromBlobParams, ParseFromStringParams, ParseResult, VectorResult} from './types';
+import type {
+    MetadataResult,
+    ParseFromBlobParams,
+    ParseFromStringParams,
+    ParseResult,
+    Shape,
+    VectorResult
+} from './types';
 
 import {safeSplit} from '~/utils';
 
@@ -64,21 +71,65 @@ function alignItems<T>(data: T[][], dimension: number, defaultValue: T): T[][] {
     });
 }
 
-function parseVectors(str: string, maxCount?: number, maxDimension?: number): VectorResult {
+// Fisher-Yates (aka Knuth) Shuffle
+function shuffleIndices(length: number) {
+    const indices = Array.from<number>({length}).map((_, i) => i);
+    let currentIndex = length;
+    while (currentIndex) {
+        const randomIndex = Math.floor(Math.random() * currentIndex);
+        currentIndex--;
+        const temporaryValue = indices[currentIndex];
+        indices[currentIndex] = indices[randomIndex];
+        indices[randomIndex] = temporaryValue;
+    }
+    return indices;
+}
+
+function shuffle(data: ParseResult, maxCount?: number, maxDimension?: number): ParseResult {
+    const {
+        count: originalCount,
+        dimension: originalDimension,
+        vectors: originalVectors,
+        metadata: originalMetadata
+    } = data;
+    const count = maxCount ? Math.min(originalCount, maxCount) : originalCount;
+    const dimension = maxDimension ? Math.min(originalDimension, maxDimension) : originalDimension;
+    const shuffledIndices = shuffleIndices(originalCount);
+    const shuffledDimensionIndices = shuffleIndices(originalDimension);
+    const vectors = new Float32Array(count * dimension);
+    const metadata: string[][] = [];
+    for (let c = 0; c < count; c++) {
+        const offset = shuffledIndices[c] * originalDimension;
+        if (dimension < originalDimension) {
+            for (let i = 0; i < dimension; i++) {
+                vectors[c + i] = originalVectors[offset + shuffledDimensionIndices[i]];
+            }
+        } else {
+            vectors.set(originalVectors.subarray(offset, offset + dimension), c * dimension);
+        }
+        metadata.push(originalMetadata[shuffledIndices[c]]);
+    }
+    return {
+        ...data,
+        count,
+        dimension,
+        vectors,
+        metadata
+    };
+}
+
+function parseVectors(str: string): VectorResult {
     if (!str) {
         throw new ParserError('Tenser file is empty', ParserError.CODES.TENSER_EMPTY);
     }
+    const rawShape: Shape = [0, 0];
     let vectors = split(str, Number.parseFloat);
-    // TODO: random sampling
-    if (maxCount) {
-        vectors = vectors.slice(0, maxCount);
-    }
-    let dimension = Math.min(...vectors.map(vector => vector.length));
-    if (maxDimension) {
-        dimension = Math.min(dimension, maxDimension);
-    }
+    rawShape[0] = vectors.length;
+    const dimension = Math.min(...vectors.map(vector => vector.length));
+    rawShape[1] = dimension;
     vectors = alignItems(vectors, dimension, 0);
     return {
+        rawShape,
         dimension,
         count: vectors.length,
         vectors: new Float32Array(vectors.flat())
@@ -132,6 +183,7 @@ function genMetadataAndLabels(metadata: string, count: number) {
 
 export function parseFromString({vectors: v, metadata: m, maxCount, maxDimension}: ParseFromStringParams): ParseResult {
     const result: ParseResult = {
+        rawShape: [0, 0],
         count: 0,
         dimension: 0,
         vectors: new Float32Array(),
@@ -139,14 +191,10 @@ export function parseFromString({vectors: v, metadata: m, maxCount, maxDimension
         metadata: []
     };
     if (v) {
-        const {dimension, vectors, count} = parseVectors(v, maxCount, maxDimension);
-        result.dimension = dimension;
-        result.vectors = vectors;
-        const metadataAndLabels = genMetadataAndLabels(m, count);
-        metadataAndLabels.metadata = metadataAndLabels.metadata.slice(0, count);
-        Object.assign(result, metadataAndLabels);
+        Object.assign(result, parseVectors(v));
+        Object.assign(result, genMetadataAndLabels(m, result.count));
     }
-    return result;
+    return shuffle(result, maxCount, maxDimension);
 }
 
 export async function parseFromBlob({
@@ -156,25 +204,20 @@ export async function parseFromBlob({
     maxCount,
     maxDimension
 }: ParseFromBlobParams): Promise<ParseResult> {
-    // TODO: random sampling
-    const [originalCount, originalDimension] = shape;
-    const originalVectors = new Float32Array(await v.arrayBuffer());
-    if (originalCount * originalDimension !== originalVectors.length) {
+    const [count, dimension] = shape;
+    const vectors = new Float32Array(await v.arrayBuffer());
+    if (count * dimension !== vectors.length) {
         throw new ParserError('Size of tensor does not match.', ParserError.CODES.SHAPE_MISMATCH);
     }
-    const count = maxCount ? Math.min(originalCount, maxCount) : originalCount;
-    const dimension = maxDimension ? Math.min(originalDimension, maxDimension) : originalDimension;
-    const vectors = new Float32Array(count * dimension);
-    for (let c = 0; c < count; c++) {
-        const offset = c * originalDimension;
-        vectors.set(originalVectors.subarray(offset, offset + dimension), c * dimension);
-    }
-    const metadataAndLabels = genMetadataAndLabels(m, originalCount);
-    metadataAndLabels.metadata = metadataAndLabels.metadata.slice(0, count);
-    return {
-        count,
-        dimension,
-        vectors,
-        ...metadataAndLabels
-    };
+    return shuffle(
+        {
+            rawShape: shape,
+            count,
+            dimension,
+            vectors,
+            ...genMetadataAndLabels(m, count)
+        },
+        maxCount,
+        maxDimension
+    );
 }

frontend/packages/core/src/resource/high-dimensional/tsne.ts

@@ -50,7 +50,7 @@
  * You can find the PDF [here](http://jmlr.csail.mit.edu/papers/volume9/vandermaaten08a/vandermaaten08a.pdf).
  */
 
-// cSpell:words Maaten Andrej Karpathy Karpathy's Guass randn xtod premult dists gainid
+// cSpell:words Maaten Andrej Karpathy Karpathy's randn xtod premult dists gainid
 
 export type tSNEOptions = {
     perplexity?: number;
@@ -58,7 +58,7 @@ export type tSNEOptions = {
     dimension: number;
 };
 
-class GuassRandom {
+class GaussRandom {
     private returnV = false;
     private vVal = 0.0;
 
@@ -85,7 +85,7 @@ export default class tSNE {
     epsilon = 10;
     perplexity = 30;
 
-    private Random = new GuassRandom();
+    private Random = new GaussRandom();
 
     private data = new Float32Array();
     private P: Float32Array = new Float32Array();

frontend/packages/core/src/resource/high-dimensional/types.ts

@@ -19,7 +19,10 @@ export type Reduction = 'pca' | 'tsne' | 'umap';
 
 export type Vectors = [number, number, number][];
 
+export type Shape = [number, number];
+
 export type VectorResult = {
+    rawShape: Shape;
     dimension: number;
     count: number;
     vectors: Float32Array;
@@ -42,7 +45,7 @@ export interface ParseFromStringParams extends BaseParseParams {
 }
 
 export interface ParseFromBlobParams extends BaseParseParams {
-    shape: [number, number];
+    shape: Shape;
     vectors: Blob;
 }
 
@@ -58,6 +61,7 @@ export type ParseParams =
     | null;
 
 export type ParseResult = {
+    rawShape: Shape;
     count: number;
     dimension: number;
     vectors: Float32Array;

frontend/packages/core/tsconfig.json

@@ -9,12 +9,7 @@
     ],
     "extends": "@snowpack/app-scripts-react/tsconfig.base.json",
     "compilerOptions": {
-        // You can't currently define paths in your 'extends' config,
-        // so we have to set 'baseUrl' & 'paths' here.
-        // Don't change these unless you know what you're doing.
-        // See: https://github.com/microsoft/TypeScript/issues/25430
         "baseUrl": "./",
-        /* more strict checking for errors that per-file transpilers like `esbuild` would crash */
         "isolatedModules": true,
         "paths": {
             "*": [
@@ -24,8 +19,6 @@
                 "./src/*"
             ]
         },
-        // Feel free to add/edit new config options below:
-        // ...
         "lib": [
             "DOM",
             "DOM.Iterable",

frontend/packages/demo/package.json

 {
     "name": "@visualdl/demo",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -34,7 +34,7 @@
     "devDependencies": {
         "@types/express": "4.17.9",
         "@types/mkdirp": "1.0.1",
-        "@types/node": "14.14.14",
+        "@types/node": "14.14.16",
         "@types/node-fetch": "2.5.7",
         "@types/rimraf": "3.0.0",
         "cpy-cli": "3.1.1",

frontend/packages/mock/package.json

 {
     "name": "@visualdl/mock",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -42,7 +42,7 @@
     "devDependencies": {
         "@types/express": "4.17.9",
         "@types/faker": "5.1.5",
-        "@types/node": "14.14.14",
+        "@types/node": "14.14.16",
         "cpy-cli": "3.1.1",
         "rimraf": "3.0.2",
         "ts-node": "9.1.1",

frontend/packages/netron/package.json

 {
     "name": "@visualdl/netron",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -51,8 +51,8 @@
         "sass": "1.30.0",
         "sass-loader": "10.1.0",
         "terser": "5.5.1",
-        "webpack": "5.10.3",
-        "webpack-cli": "4.2.0"
+        "webpack": "5.11.0",
+        "webpack-cli": "4.3.0"
     },
     "engines": {
         "node": ">=12",

frontend/packages/server/package.json

 {
     "name": "@visualdl/server",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [
         "visualdl",
@@ -36,25 +36,25 @@
         "ecosystem.config.d.ts"
     ],
     "dependencies": {
-        "@visualdl/core": "2.0.9",
+        "@visualdl/core": "2.1.0-1",
         "dotenv": "8.2.0",
-        "enhanced-resolve": "5.4.0",
+        "enhanced-resolve": "5.4.1",
         "express": "4.17.1",
         "http-proxy-middleware": "1.0.6",
-        "pm2": "4.5.0"
+        "pm2": "4.5.1"
     },
     "devDependencies": {
         "@types/enhanced-resolve": "3.0.6",
         "@types/express": "4.17.9",
-        "@types/node": "14.14.14",
-        "@visualdl/mock": "2.0.9",
+        "@types/node": "14.14.16",
+        "@visualdl/mock": "2.1.0-1",
         "cross-env": "7.0.3",
         "nodemon": "2.0.6",
         "ts-node": "9.1.1",
         "typescript": "4.0.5"
     },
     "optionalDependencies": {
-        "@visualdl/demo": "2.0.9"
+        "@visualdl/demo": "2.1.0-1"
     },
     "engines": {
         "node": ">=12",

frontend/packages/wasm/package.json

 {
     "name": "@visualdl/wasm",
-    "version": "2.0.9",
+    "version": "2.1.0-1",
     "title": "VisualDL",
     "description": "A platform to visualize the deep learning process and result.",
     "keywords": [

frontend/scripts/install.sh

@@ -2,6 +2,10 @@
 
 set -e
 
+SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
+
+cd $SCRIPT_DIR/..
+
 # rust toolchain
 # https://rustup.rs/
 if ! hash rustup 2>/dev/null; then

scripts/build.ps1

-# Build script for Windows
-# Requires: PowerShell, Python 3, Visual Studio 15 2017
-
-$TOP_DIR=$pwd.PATH
-$FRONTEND_DIR="$TOP_DIR/frontend"
-$BACKEND_DIR="$TOP_DIR/visualdl"
-$BUILD_DIR="$TOP_DIR/build"
-
-mkdir $BUILD_DIR -ErrorAction Ignore
-
-function check_duplicated($filename_format) {
-    $files = ls dist/$filename_format -ErrorAction Ignore
-    if (Get-TypeName($files.Length) -ne "FileInfo") {
-      Write-Error "dist have duplicate file for $filename_format, please clean and rerun"
-      exit(1)
-    }
-}
-
-function build_frontend_from_source() {
-    cd $FRONTEND_DIR
-    # TODO:
-    # ./scripts/build.sh
-}
-
-function build_frontend() {
-    $PACKAGE_NAME="@visualdl/serverless"
-    $SRC=npm view $PACKAGE_NAME dist.tarball
-    Invoke-WebRequest -Uri "$SRC" -OutFile "$BUILD_DIR/$PACKAGE_NAME.tar.gz"
-    # Need Windows 10 Insider Build 17063 and later
-    tar -zxf "$BUILD_DIR/$PACKAGE_NAME.tar.gz" -C "$BUILD_DIR"
-}
-
-function build_frontend_fake() {
-    mkdir -p "$BUILD_DIR/package/dist"
-}
-
-function build_backend() {
-    cd $BUILD_DIR
-    cmake -G "Visual Studio 15 2017 Win64" `
-        -DCMAKE_BUILD_TYPE=Release `
-        -DON_RELEASE=ON `
-        -DWITH_PYTHON3=ON `
-        -DWITH_TESTING=OFF `
-        -DBUILD_FOR_HOST:BOOL=YES ..
-    cmake --build . --config Release
-}
-
-function build_onnx_graph() {
-    $env:PATH = "$BUILD_DIR/third_party/protobuf/src/extern_protobuf-build/Release;" + $env:PATH
-    cd $TOP_DIR/visualdl/server/model/onnx
-    protoc onnx.proto --python_out .
-    cd $TOP_DIR/visualdl/server/model/paddle
-    protoc framework.proto --python_out .
-}
-
-function clean_env() {
-    rm -Recurse -Force -ErrorAction Ignore $TOP_DIR/visualdl/server/dist
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/bdist*
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/lib*
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/temp*
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/scripts*
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/*.tar.gz
-    rm -Recurse -Force -ErrorAction Ignore $BUILD_DIR/package
-}
-
-function package() {
-    cp -Recurse $BUILD_DIR/package/dist $TOP_DIR/visualdl/server/
-    cp $BUILD_DIR/visualdl/logic/Release/core.pyd $TOP_DIR/visualdl
-    cp $BUILD_DIR/visualdl/logic/Release/core.pyd $TOP_DIR/visualdl/python/
-}
-
-clean_env
-build_frontend
-build_backend
-build_onnx_graph
-package

scripts/check_style.sh

-#!/bin/bash
-function abort(){
-    echo "Your change doesn't follow VisualDL's code style." 1>&2
-    echo "Please use pre-commit to check what is wrong." 1>&2
-    exit 1
-}
-
-trap 'abort' 0
-set -e
-
-cd $TRAVIS_BUILD_DIR
-export PATH=/usr/bin:$PATH
-pre-commit install
-clang-format --version
-
-flake8 --version
-
-if ! pre-commit run -a ; then
-    git diff
-    exit 1
-fi
-
-trap : 0

scripts/deploy_docs_on_travis.sh

-#!/usr/bin/env bash
-exit_code=0
-if [[ "$TRAVIS_PULL_REQUEST" != "false" ]]; then exit $exit_code; fi;
-
-if [ "$TRAVIS_BRANCH" == "develop_doc" ]; then
-    PPO_SCRIPT_BRANCH=develop
-elif [[ "$TRAVIS_BRANCH" == "develop" ]]; then
-    PPO_SCRIPT_BRANCH=master
-else
-    exit $exit_code;
-fi
-
-export DEPLOY_DOCS_SH=https://raw.githubusercontent.com/PaddlePaddle/PaddlePaddle.org/$PPO_SCRIPT_BRANCH/scripts/deploy/deploy_docs.sh
-
-docker run -it \
-    -e CONTENT_DEC_PASSWD=$CONTENT_DEC_PASSWD \
-    -e TRAVIS_BRANCH=$TRAVIS_BRANCH \
-    -e DEPLOY_DOCS_SH=$DEPLOY_DOCS_SH \
-    -e TRAVIS_PULL_REQUEST=$TRAVIS_PULL_REQUEST \
-    -e PPO_SCRIPT_BRANCH=$PPO_SCRIPT_BRANCH \
-    -e PADDLE_ROOT=/VisualDL \
-    -v "$PWD:/VisualDL" \
-    -w /VisualDL \
-    paddlepaddle/paddle:latest-dev \
-    /bin/bash -c 'curl $DEPLOY_DOCS_SH | bash -s $CONTENT_DEC_PASSWD $TRAVIS_BRANCH /VisualDL /VisualDL/build/doc/ $PPO_SCRIPT_BRANCH' || exit_code=$(( exit_code | $? ))

scripts/setup.sh

+#!/bin/bash
+set -e
+
+SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
+
+cd $SCRIPT_DIR/..
+
+which python > /dev/null 2>&1
+if [ $? -ne 0 ]; then
+    echo "You need to install Python 3.5+"
+    exit 1
+fi
+python --version
+
+which node > /dev/null 2>&1
+if [ $? -ne 0 ]; then
+    echo "You need to install nodejs 14+"
+    exit 1
+fi
+node --version
+
+pip install pre-commit && pre-commit install
+pip install --disable-pip-version-check -r requirements.txt
+(cd frontend && scripts/install.sh)

scripts/setup_dev_env.sh

-#!/bin/bash
-set -e
-
-SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
-
-cd $SCRIPT_DIR/..
-mkdir -p build
-cd build
-
-which node >/dev/null 2>&1
-if [ $? -ne 0 ]; then
-    echo "You need to install nodejs"
-    exit 1
-fi
-
-echo "Setting up nodejs dependencies"
-npm install visualdl@latest --no-package-lock
-
-processors=1
-if [ "$(uname)" == "Darwin" ]; then
-    processors=`sysctl -n hw.ncpu`
-elif [ "$(expr substr $(uname -s) 1 5)" == "Linux" ]; then
-    processors=`nproc`
-fi
-
-echo "Building VisualDL SDK"
-cmake ..
-
-make -j $processors
-
-export PYTHONPATH=$PYTHONPATH:"$SCRIPT_DIR/.."

scripts/start_dev_server.sh

-#!/bin/bash
-set -e
-
-ORIGINAL_ARGS="$@"
-
-ARGS=`getopt --long host:,port: -n 'start_dev_server.sh' -- "$@"`
-
-if [ $? != 0 ]; then
-    echo "Get arguments failed!" >&2
-    cd $CWD
-    exit 1
-fi
-
-PORT=8040
-HOST="localhost"
-
-eval set -- "$ARGS"
-
-while true
-do
-    case "$1" in
-        --host)
-            HOST="$2"
-            shift 2
-            ;;
-        --port)
-            PORT="$2"
-            shift 2
-            ;;
-        --)
-            shift
-            break
-            ;;
-        *)
-            break
-            ;;
-    esac
-done
-
-CURRENT_DIR=`pwd`
-
-SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
-
-export PYTHONPATH=$PYTHONPATH:"$SCRIPT_DIR/.."
-
-FRONTEND_PORT=8999
-VDL_BIN="./build/node_modules/.bin/visualdl"
-$VDL_BIN start --port=$FRONTEND_PORT --host=$HOST --backend="http://$HOST:$PORT"
-
-function finish {
-    $VDL_BIN stop
-}
-
-trap finish EXIT HUP INT QUIT PIPE TERM
-
-cd $CURRENT_DIR
-
-echo "Development server ready on http://$HOST:$FRONTEND_PORT"
-
-# Run the visualDL with local PATH
-python ${SCRIPT_DIR}/../visualdl/server/app.py "$ORIGINAL_ARGS"

scripts/tests.sh

-#!/bin/bash
-set -ex
-
-SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
-cd $SCRIPT_DIR/..
-
-mode=$1
-
-readonly TOP_DIR=$(pwd)
-readonly core_path=$TOP_DIR/build/visualdl/logic
-readonly python_path=$TOP_DIR/visualdl/python
-readonly max_file_size=1000000 # 1MB
-# version number follow the rule of https://semver.org/
-readonly version_number=`cat VERSION_NUMBER | sed 's/\([0-9]*.[0-9]*.[0-9]*\).*/\1/g'`
-
-sudo="sudo"
-pip="pip"
-python="python2"
-
-if [[ "$WITH_PYTHON3" == "ON" ]]; then
-    pip="pip3"
-    python="python3"
-    $sudo python3 -m pip install --upgrade pip
-fi
-
-if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then sudo=""; fi
-
-if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then
-		curl -O http://python-distribute.org/distribute_setup.py
-		$python distribute_setup.py
-		curl -O https://raw.github.com/pypa/pip/master/contrib/get-pip.py
-		$python get-pip.py
-fi
-
-$sudo $pip install numpy
-$sudo $pip install Flask
-$sudo $pip install Pillow
-$sudo $pip install --ignore-installed six
-$sudo $pip install protobuf
-
-export PYTHONPATH="${core_path}:${python_path}"
-
-# install the visualdl wheel first
-package() {
-    cd $TOP_DIR/visualdl/server
-    # manully install protobuf3
-    curl -OL https://github.com/google/protobuf/releases/download/v3.5.0/protoc-3.5.0-linux-x86_64.zip
-    unzip protoc-3.5.0-linux-x86_64.zip -d protoc3
-    export PATH="$PATH:$(pwd)/protoc3/bin"
-    chmod +x protoc3/bin/*
-
-    cd $TOP_DIR
-    $python setup.py bdist_wheel
-    $sudo $pip install dist/visualdl-${version_number}*.whl
-}
-
-backend_test() {
-    cd $TOP_DIR
-    mkdir -p build
-    cd build
-    if [[ "$WITH_PYTHON3" == "ON" ]]; then
-        cmake -DWITH_PYTHON3=ON ..
-    else
-        cmake ..
-    fi
-    make
-    make test
-}
-
-server_test() {
-    $sudo $pip install google
-    $sudo $pip install protobuf==3.5.1
-
-    cd $TOP_DIR/visualdl/server
-    bash graph_test.sh
-
-    cd $TOP_DIR/
-    $python -m visualdl.server.lib_test
-}
-
-# check the size of files in the repo.
-# reject PR that has some big data included.
-bigfile_reject() {
-    cd $TOP_DIR
-    # it failed to exclude .git, remove it first.
-    rm -rf .git
-    local largest_file=$(find . -path .git -prune -o -printf '%s %p\n' | sort -nr | grep -v "CycleGAN"| head -n1)
-    local size=$(echo "$largest_file" | awk '{print $1}')
-    if [ "$size" -ge "$max_file_size" ]; then
-        echo $largest_file
-        echo "file size exceed $max_file_size"
-        echo "Should not add large data or binary file."
-        exit -1
-    fi
-}
-
-clean_env() {
-    rm -rf $TOP_DIR/build
-    rm -rf $TOP_DIR/dist
-    rm -rf $TOP_DIR/visualdl/core.so
-    rm -rf $TOP_DIR/visualdl/python/core.so
-    rm -rf $TOP_DIR/visualdl/server/protoc3
-    rm -rf $TOP_DIR/visualdl/server/protoc*.zip
-}
-
-echo "mode" $mode
-
-if [ $mode = "backend" ]; then
-    backend_test
-elif [ $mode = "all" ]; then
-    # Clean before test
-    clean_env
-    # bigfile_reject should be tested first, or some files downloaded may fail this test.
-    bigfile_reject
-    package
-    backend_test
-    server_test
-elif [ $mode = "local" ]; then
-    backend_test
-    server_test
-fi

visualdl/.clang-format

-# This file is used by clang-format to autoformat paddle source code
-#
-# The clang-format is part of llvm toolchain.
-# It need to install llvm and clang to format source code style.
-#
-# The basic usage is,
-#   clang-format -i -style=file PATH/TO/SOURCE/CODE
-#
-# The -style=file implicit use ".clang-format" file located in one of 
-# parent directory. 
-# The -i means inplace change.
-#
-# The document of clang-format is 
-#   http://clang.llvm.org/docs/ClangFormat.html
-#   http://clang.llvm.org/docs/ClangFormatStyleOptions.html
----
-Language:        Cpp
-BasedOnStyle:  Google
-IndentWidth:     2
-TabWidth:        2
-ContinuationIndentWidth: 4
-AccessModifierOffset: -2  # The private/protected/public has no indent in class
-Standard:  Cpp11 
-AllowAllParametersOfDeclarationOnNextLine: true
-BinPackParameters: false
-BinPackArguments: false
-...
-

visualdl/__init__.py

@@ -17,9 +17,9 @@ from __future__ import absolute_import
 
 import os
 
-from visualdl.writer.writer import LogWriter  # noqa
-from visualdl.reader.reader import LogReader
-from visualdl.version import vdl_version as __version__
+from visualdl.writer.writer import LogWriter  # noqa: F401
+from visualdl.reader.reader import LogReader  # noqa: F401
+from visualdl.version import vdl_version as __version__  # noqa: F401
 from visualdl.utils.dir import init_vdl_config
 
 init_vdl_config()

visualdl/component/__init__.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 components = {
     "scalar": {
         "enabled": False

visualdl/component/base_component.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 from visualdl.proto.record_pb2 import Record
 import numpy as np
 from PIL import Image
@@ -80,11 +81,11 @@ def imgarray2bytes(np_array):
     return img_bin
 
 
-def make_grid(I, ncols=8):
+def make_grid(I, ncols=8):  # noqa: E741
     assert isinstance(
         I, np.ndarray), 'plugin error, should pass numpy array here'
     if I.shape[1] == 1:
-        I = np.concatenate([I, I, I], 1)
+        I = np.concatenate([I, I, I], 1)  # noqa: E741
     assert I.ndim == 4 and I.shape[1] == 3 or I.shape[1] == 4
     nimg = I.shape[0]
     H = I.shape[2]
@@ -404,6 +405,8 @@ def pr_curve_raw(tag, tp, fp, tn, fn, precision, recall, step, walltime):
         Record.Value(
             id=step, tag=tag, timestamp=walltime, pr_curve=prcurve)
     ])
+
+
 def compute_roc_curve(labels, predictions, num_thresholds=None, weights=None):
     """ Compute ROC curve data by labels and predictions.
     Args:
@@ -454,8 +457,7 @@ def compute_roc_curve(labels, predictions, num_thresholds=None, weights=None):
     return data
 
 
-def roc_curve(tag, labels, predictions, step, walltime, num_thresholds=127,
-             weights=None):
+def roc_curve(tag, labels, predictions, step, walltime, num_thresholds=127, weights=None):
     """Package data to one roc_curve.
     Args:
         tag (string): Data identifier
@@ -473,14 +475,14 @@ def roc_curve(tag, labels, predictions, step, walltime, num_thresholds=127,
     roc_curve_map = compute_roc_curve(labels, predictions, num_thresholds, weights)
 
     return roc_curve_raw(tag=tag,
-                        tp=roc_curve_map['tp'],
-                        fp=roc_curve_map['fp'],
-                        tn=roc_curve_map['tn'],
-                        fn=roc_curve_map['fn'],
-                        tpr=roc_curve_map['tpr'],
-                        fpr=roc_curve_map['fpr'],
-                        step=step,
-                        walltime=walltime)
+                         tp=roc_curve_map['tp'],
+                         fp=roc_curve_map['fp'],
+                         tn=roc_curve_map['tn'],
+                         fn=roc_curve_map['fn'],
+                         tpr=roc_curve_map['tpr'],
+                         fpr=roc_curve_map['fpr'],
+                         step=step,
+                         walltime=walltime)
 
 
 def roc_curve_raw(tag, tp, fp, tn, fn, tpr, fpr, step, walltime):
@@ -516,13 +518,12 @@ def roc_curve_raw(tag, tp, fp, tn, fn, tpr, fpr, step, walltime):
         fpr = fpr.astype(int).tolist()
     """
     roc_curve = Record.ROC_Curve(TP=tp,
-                             FP=fp,
-                             TN=tn,
-                             FN=fn,
-                             tpr=tpr,
-                             fpr=fpr)
+                                 FP=fp,
+                                 TN=tn,
+                                 FN=fn,
+                                 tpr=tpr,
+                                 fpr=fpr)
     return Record(values=[
         Record.Value(
             id=step, tag=tag, timestamp=walltime, roc_curve=roc_curve)
     ])
-    

visualdl/io/__init__.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 # =======================================================================
 
-from . import bfile  # noqa
+from . import bfile  # noqa: F401

visualdl/io/bfile.py

@@ -387,7 +387,7 @@ class BosFileSystem(object):
                                           content_md5=content_md5(file_content),
                                           content_length=content_length,
                                           offset=offset)
-        except (exception.BceServerError, exception.BceHttpClientError) as e:
+        except (exception.BceServerError, exception.BceHttpClientError):
             init_data = b''
             self.bos_client.append_object(bucket_name=bucket_name,
                                           key=object_key,
@@ -634,7 +634,7 @@ class BFile(object):
         if isinstance(self.fs, BosFileSystem):
             try:
                 self.fs.append(self._filename, b'', self.binary_mode, force=True)
-            except:
+            except Exception:
                 pass
         self.flush()
         if self.write_temp is not None:

visualdl/reader/reader.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 import collections
-from functools import partial
 from visualdl.io import bfile
 from visualdl.component import components
 from visualdl.reader.record_reader import RecordReader
@@ -34,7 +34,7 @@ def is_VDLRecord_file(path, check=False):
     Returns:
         True if the file is a VDL log file, otherwise false.
     """
-    if not "vdlrecords" in path:
+    if "vdlrecords" not in path:
         return False
     if check:
         _reader = RecordReader(filepath=path)
@@ -72,7 +72,8 @@ class LogReader(object):
         self.file_readers = {}
 
         # {'run': {'scalar': {'tag1': data, 'tag2': data}}}
-        self._log_datas = collections.defaultdict(lambda: collections.defaultdict(lambda: collections.defaultdict(list)))
+        self._log_datas = collections.defaultdict(
+            lambda: collections.defaultdict(lambda: collections.defaultdict(list)))
 
         if file_path:
             self._log_data = collections.defaultdict(lambda: collections.defaultdict(list))
@@ -128,7 +129,9 @@ class LogReader(object):
         return log_tags
 
     def get_log_data(self, component, run, tag):
-        if run in self._log_datas.keys() and component in self._log_datas[run].keys() and tag in self._log_datas[run][component].keys():
+        if (run in self._log_datas.keys() and
+                component in self._log_datas[run].keys() and
+                tag in self._log_datas[run][component].keys()):
             return self._log_datas[run][component][tag]
         else:
             file_path = bfile.join(run, self.walks[run])

visualdl/reader/record_reader.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 from visualdl.io import bfile
 import struct
 

visualdl/server/api.py

@@ -112,6 +112,7 @@ class Api(object):
     @result()
     def pr_curve_tags(self):
         return self._get_with_retry('data/plugin/pr_curves/tags', lib.get_pr_curve_tags)
+
     @result()
     def roc_curve_tags(self):
         return self._get_with_retry('data/plugin/roc_curves/tags', lib.get_roc_curve_tags)
@@ -181,20 +182,26 @@ class Api(object):
     def pr_curves_pr_curve(self, run, tag):
         key = os.path.join('data/plugin/pr_curves/pr_curve', run, tag)
         return self._get_with_retry(key, lib.get_pr_curve, run, tag)
+
     @result()
     def roc_curves_roc_curve(self, run, tag):
         key = os.path.join('data/plugin/roc_curves/roc_curve', run, tag)
         return self._get_with_retry(key, lib.get_roc_curve, run, tag)
+
     @result()
     def pr_curves_steps(self, run):
         key = os.path.join('data/plugin/pr_curves/steps', run)
         return self._get_with_retry(key, lib.get_pr_curve_step, run)
+
     @result()
     def roc_curves_steps(self, run):
         key = os.path.join('data/plugin/roc_curves/steps', run)
         return self._get_with_retry(key, lib.get_roc_curve_step, run)
 
-    @result('application/octet-stream', lambda s: {"Content-Disposition": 'attachment; filename="%s"' % s.model_name} if len(s.model_name) else None)
+    @result(
+        'application/octet-stream',
+        lambda s: {"Content-Disposition": 'attachment; filename="%s"' % s.model_name} if len(s.model_name) else None
+    )
     def graph_graph(self):
         key = os.path.join('data/plugin/graphs/graph')
         return self._get_with_retry(key, lib.get_graph)

visualdl/server/lib.py

@@ -14,12 +14,12 @@
 # =======================================================================
 
 from __future__ import absolute_import
+from functools import partial  # noqa: F401
 import sys
 import time
 import os
 import io
 import csv
-from functools import partial
 import numpy as np
 from visualdl.server.log import logger
 from visualdl.io import bfile
@@ -198,8 +198,8 @@ def get_pr_curve(log_reader, run, tag):
                         list(pr_curve.FN),
                         num_thresholds])
     return results
- 
-    
+
+
 def get_roc_curve(log_reader, run, tag):
     run = log_reader.name2tags[run] if run in log_reader.name2tags else run
     log_reader.load_new_data()
@@ -225,7 +225,7 @@ def get_roc_curve(log_reader, run, tag):
 def get_pr_curve_step(log_reader, run, tag=None):
     fake_run = run
     run = log_reader.name2tags[run] if run in log_reader.name2tags else run
-    run2tag = get_pr_curve_tags(log_reader)
+    run2tag = get_pr_curve_tags(log_reader)  # noqa: F821
     tag = run2tag['tags'][run2tag['runs'].index(fake_run)][0]
     log_reader.load_new_data()
     records = log_reader.data_manager.get_reservoir("pr_curve").get_items(
@@ -237,7 +237,7 @@ def get_pr_curve_step(log_reader, run, tag=None):
 def get_roc_curve_step(log_reader, run, tag=None):
     fake_run = run
     run = log_reader.name2tags[run] if run in log_reader.name2tags else run
-    run2tag = get_roc_curve_tags(log_reader)
+    run2tag = get_roc_curve_tags(log_reader)  # noqa: F821
     tag = run2tag['tags'][run2tag['runs'].index(fake_run)][0]
     log_reader.load_new_data()
     records = log_reader.data_manager.get_reservoir("roc_curve").get_items(
@@ -245,7 +245,7 @@ def get_roc_curve_step(log_reader, run, tag=None):
     results = [[s2ms(item.timestamp), item.id] for item in records]
     return results
 
-  
+
 def get_embeddings_list(log_reader):
     run2tag = get_logs(log_reader, 'embeddings')
 
@@ -356,26 +356,3 @@ def cache_get(cache):
         return data
 
     return _handler
-
-
-def simple_pca(x, dimension):
-    """
-    A simple PCA implementation to do the dimension reduction.
-    """
-
-    # Center the data.
-    x -= np.mean(x, axis=0)
-
-    # Computing the Covariance Matrix
-    cov = np.cov(x, rowvar=False)
-
-    # Get eigenvectors and eigenvalues from the covariance matrix
-    eigvals, eigvecs = np.linalg.eig(cov)
-
-    # Sort the eigvals from high to low
-    order = np.argsort(eigvals)[::-1]
-
-    # Drop the eigenvectors with low eigenvalues
-    eigvecs = eigvecs[:, order[:dimension]]
-
-    return np.dot(x, eigvecs)

visualdl/server/serve.py

@@ -14,6 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 import requests
 import json
 import os

visualdl/server/tsne.py

-#
-#  tsne.py
-#
-# Implementation of t-SNE in Python. The implementation was tested on Python
-# 2.7.10, and it requires a working installation of NumPy. The implementation
-# comes with an example on the MNIST dataset. In order to plot the
-# results of this example, a working installation of matplotlib is required.
-#
-# The example can be run by executing: `ipython tsne.py`
-#
-#
-#  Created by Laurens van der Maaten on 20-12-08.
-#  Copyright (c) 2008 Tilburg University. All rights reserved.
-
-# Editor's note: Thanks https://lvdmaaten.github.io/tsne/
-# For allowing it to be free to use, modify, or redistribute for non-commercial purposes
-# This file is modified to remove some print out.
-
-import numpy as np
-
-
-def Hbeta(D=np.array([]), beta=1.0):
-    """
-        Compute the perplexity and the P-row for a specific value of the
-        precision of a Gaussian distribution.
-    """
-
-    # Compute P-row and corresponding perplexity
-    P = np.exp(-D.copy() * beta)
-    sumP = sum(P)
-    H = np.log(sumP) + beta * np.sum(D * P) / sumP
-    P = P / sumP
-    return H, P
-
-
-def x2p(X=np.array([]), tol=1e-5, perplexity=30.0):
-    """
-        Performs a binary search to get P-values in such a way that each
-        conditional Gaussian has the same perplexity.
-    """
-
-    # Initialize some variables
-    print("Computing pairwise distances...")
-    (n, d) = X.shape
-    sum_X = np.sum(np.square(X), 1)
-    D = np.add(np.add(-2 * np.dot(X, X.T), sum_X).T, sum_X)
-    P = np.zeros((n, n))
-    beta = np.ones((n, 1))
-    logU = np.log(perplexity)
-
-    # Loop over all datapoints
-    for i in range(n):
-
-        # Print progress
-        # if i % 500 == 0:
-        #     print("Computing P-values for point %d of %d..." % (i, n))
-
-        # Compute the Gaussian kernel and entropy for the current precision
-        betamin = -np.inf
-        betamax = np.inf
-        Di = D[i, np.concatenate((np.r_[0:i], np.r_[i + 1:n]))]
-        (H, thisP) = Hbeta(Di, beta[i])
-
-        # Evaluate whether the perplexity is within tolerance
-        Hdiff = H - logU
-        tries = 0
-        while np.abs(Hdiff) > tol and tries < 50:
-
-            # If not, increase or decrease precision
-            if Hdiff > 0:
-                betamin = beta[i].copy()
-                if betamax == np.inf or betamax == -np.inf:
-                    beta[i] = beta[i] * 2.
-                else:
-                    beta[i] = (beta[i] + betamax) / 2.
-            else:
-                betamax = beta[i].copy()
-                if betamin == np.inf or betamin == -np.inf:
-                    beta[i] = beta[i] / 2.
-                else:
-                    beta[i] = (beta[i] + betamin) / 2.
-
-            # Recompute the values
-            (H, thisP) = Hbeta(Di, beta[i])
-            Hdiff = H - logU
-            tries += 1
-
-        # Set the final row of P
-        P[i, np.concatenate((np.r_[0:i], np.r_[i + 1:n]))] = thisP
-
-    # Return final P-matrix
-    print("Mean value of sigma: %f" % np.mean(np.sqrt(1 / beta)))
-    return P
-
-
-def pca(X=np.array([]), no_dims=50):
-    """
-        Runs PCA on the NxD array X in order to reduce its dimensionality to
-        no_dims dimensions.
-    """
-
-    (n, d) = X.shape
-    X = X - np.tile(np.mean(X, 0), (n, 1))
-    (l, M) = np.linalg.eig(np.dot(X.T, X))
-    Y = np.dot(X, M[:, 0:no_dims])
-    return Y
-
-
-def tsne(X=np.array([]), no_dims=2, initial_dims=50, perplexity=30.0):
-    """
-        Runs t-SNE on the dataset in the NxD array X to reduce its
-        dimensionality to no_dims dimensions. The syntaxis of the function is
-        `Y = tsne.tsne(X, no_dims, perplexity), where X is an NxD NumPy array.
-    """
-
-    # Check inputs
-    if isinstance(no_dims, float):
-        print("Error: array X should have type float.")
-        return -1
-    if round(no_dims) != no_dims:
-        print("Error: number of dimensions should be an integer.")
-        return -1
-
-    # Initialize variables
-    X = pca(X, initial_dims).real
-    (n, d) = X.shape
-    max_iter = 1000
-    initial_momentum = 0.5
-    final_momentum = 0.8
-    eta = 500
-    min_gain = 0.01
-    Y = np.random.randn(n, no_dims)
-    dY = np.zeros((n, no_dims))
-    iY = np.zeros((n, no_dims))
-    gains = np.ones((n, no_dims))
-
-    # Compute P-values
-    P = x2p(X, 1e-5, perplexity)
-    P = P + np.transpose(P)
-    P = P / np.sum(P)
-    P = P * 4.  # early exaggeration
-    P = np.maximum(P, 1e-12)
-
-    # Run iterations
-    for iter in range(max_iter):
-
-        # Compute pairwise affinities
-        sum_Y = np.sum(np.square(Y), 1)
-        num = -2. * np.dot(Y, Y.T)
-        num = 1. / (1. + np.add(np.add(num, sum_Y).T, sum_Y))
-        num[range(n), range(n)] = 0.
-        Q = num / np.sum(num)
-        Q = np.maximum(Q, 1e-12)
-
-        # Compute gradient
-        PQ = P - Q
-        for i in range(n):
-            dY[i, :] = np.sum(
-                np.tile(PQ[:, i] * num[:, i], (no_dims, 1)).T * (Y[i, :] - Y),
-                0)
-
-        # Perform the update
-        if iter < 20:
-            momentum = initial_momentum
-        else:
-            momentum = final_momentum
-        gains = (gains + 0.2) * ((dY > 0.) != (iY > 0.)) + \
-                (gains * 0.8) * ((dY > 0.) == (iY > 0.))
-        gains[gains < min_gain] = min_gain
-        iY = momentum * iY - eta * (gains * dY)
-        Y = Y + iY
-        Y = Y - np.tile(np.mean(Y, 0), (n, 1))
-
-        # Compute current value of cost function
-        # if (iter + 1) % 10 == 0:
-        #     C = np.sum(P * np.log(P / Q))
-        # print("Iteration %d: error is %f" % (iter + 1, C))
-
-        # Stop lying about P-values
-        if iter == 100:
-            P = P / 4.
-
-    # Return solution
-    return Y

visualdl/utils/crc32.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 import array
 
 

visualdl/utils/string_util.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 # =======================================================================
 
-
 def encode_tag(tag):
     return tag.replace("%", "/")
 

visualdl/utils/update_util.py

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 import threading
 import hashlib
 import requests
-import json
 from visualdl import __version__
 from visualdl.proto.record_pb2 import DESCRIPTOR
 

visualdl/writer/record_writer.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 # =======================================================================
 
-
 from visualdl.io import bfile
 from visualdl.utils.crc32 import masked_crc32c
 from visualdl.proto import record_pb2
@@ -95,7 +94,7 @@ class RecordFileWriter(object):
                 fn = "vdlrecords.%010d.log%s" % (time.time(), filename_suffix)
                 self._file_name = bfile.join(logdir, fn)
                 print(
-                    'Since the log filename should contain `vdlrecords`, the filename is invalid and `{}` will replace `{}`'.format(
+                    'Since the log filename should contain `vdlrecords`, the filename is invalid and `{}` will replace `{}`'.format(  # noqa: E501
                         fn, filename))
         else:
             self._file_name = bfile.join(logdir, "vdlrecords.%010d.log%s" % (

visualdl/writer/writer.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =======================================================================
+
 import os
 import time
 import numpy as np
@@ -380,14 +381,15 @@ class LogWriter(object):
                 num_thresholds=num_thresholds,
                 weights=weights
                 ))
+
     def add_roc_curve(self,
-                     tag,
-                     labels,
-                     predictions,
-                     step,
-                     num_thresholds=10,
-                     weights=None,
-                     walltime=None):
+                      tag,
+                      labels,
+                      predictions,
+                      step,
+                      num_thresholds=10,
+                      weights=None,
+                      walltime=None):
         """Add an ROC curve to vdl record file.
         Args:
             tag (string): Data identifier
@@ -422,7 +424,6 @@ class LogWriter(object):
                 weights=weights
                 ))
 
-
     def flush(self):
         """Flush all data in cache to disk.
         """