Updating to tfjs master: latest (#41)

* Update jasmine_util.ts (tensorflow#6872)

FIX

* webgl: Fix NaN issue (tensorflow#6828)

Fix tensorflow#6822

Problem
1： On some GPUs, even if a and b are both non-NaN, the value of isNaN in vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0)); are still larger than 0., which misleads all values become NAN.
2： After resolving NAN issue, the result is still incorrect. It seems that the isnan_custom is not well supported on the problem GPU. After switching back to builtin isnan, everything works well.

Solution:
Use the bool type bvec4 instead of float type vec4 to calculate isNaN to avoid the the float precision issue when comparing with zero.
Meanwhile, add an env flag WEBGL2_ISNAN_CUSTOM to allow user to specify which isnan to use.

* Upgrade nodejs to 18.7.0 (tensorflow#6863)

* Upgrade nodejs to 18.7.0

* Fix hash table test string not passed as base64

* fixed prelu fusing code that pre-maturely neg the const on multiply (tensorflow#6876)

Co-authored-by: RajeshT <[email protected]>

Co-authored-by: Linchenn <[email protected]>
Co-authored-by: Jiajia Qin <[email protected]>
Co-authored-by: Matthew Soulanille <[email protected]>
Co-authored-by: Ping Yu <[email protected]>
Co-authored-by: RajeshT <[email protected]>

Author: 6 people

WORKSPACE

@@ -50,7 +50,7 @@ load("@rules_nodejs//nodejs:repositories.bzl", "nodejs_register_toolchains")
 
 nodejs_register_toolchains(
     name = "nodejs",
-    node_version = "16.13.2",
+    node_version = "18.7.0",
 )
 
 # Install the yarn tool

package.json

@@ -58,7 +58,7 @@
     "rollup": "^2.46.0",
     "rollup-plugin-sourcemaps": "^0.6.3",
     "rollup-plugin-terser": "^7.0.2",
-    "rollup-plugin-visualizer": "~3.3.2",
+    "rollup-plugin-visualizer": "~5.8.2",
     "seedrandom": "^3.0.5",
     "shelljs": "~0.8.5",
     "string_decoder": "^1.3.0",

tfjs-backend-webgl/src/binaryop_packed_gpu.ts

@@ -21,11 +21,11 @@ import {GPGPUProgram, useShapeUniforms} from './gpgpu_math';
 import {getChannels} from './packing_util';
 import {getCoordsDataType} from './shader_compiler';
 
-export const CHECK_NAN_SNIPPET = `
-  result.r = isNaN.r > 0. ? NAN : result.r;
-  result.g = isNaN.g > 0. ? NAN : result.g;
-  result.b = isNaN.b > 0. ? NAN : result.b;
-  result.a = isNaN.a > 0. ? NAN : result.a;
+export const CHECK_NAN_SNIPPET_PACKED = `
+  result.r = isNaN.r ? NAN : result.r;
+  result.g = isNaN.g ? NAN : result.g;
+  result.b = isNaN.b ? NAN : result.b;
+  result.a = isNaN.a ? NAN : result.a;
 `;
 
 export const ELU_DER = `

tfjs-backend-webgl/src/flags_webgl.ts

@@ -268,3 +268,9 @@ ENV.registerFlag('WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE', () => Infinity);
  * problem: https://github.com/tensorflow/tfjs/issues/6775.
  */
 ENV.registerFlag('WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE', () => false);
+
+/**
+ * Whether to use the customized isnan. It's only useful for webgl2 since webgl1
+ * doesn't have the builtin isnan.
+ */
+ENV.registerFlag('WEBGL2_ISNAN_CUSTOM', () => false);

tfjs-backend-webgl/src/glsl_version.ts

@@ -62,7 +62,7 @@ export function getGlslDifferences(): GLSL {
     //   - fraction = anything except all 0 bits (since all 0 bits represents
     //   infinity).
     // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers
-    defineSpecialNaN = `
+    defineSpecialNaN = env().getBool('WEBGL2_ISNAN_CUSTOM') ? `
       bool isnan_custom(float val) {
         uint floatToUint = floatBitsToUint(val);
         return (floatToUint & 0x7fffffffu) > 0x7f800000u;
@@ -74,7 +74,8 @@ export function getGlslDifferences(): GLSL {
       }
 
       #define isnan(value) isnan_custom(value)
-    `;
+    ` :
+                                                              '';
     // In webgl 2 we do not need to specify a custom isinf so there is no
     // need for a special INFINITY constant.
     defineSpecialInf = ``;

tfjs-backend-webgl/src/kernel_utils/kernel_funcs_utils.ts

@@ -32,18 +32,6 @@ import {SimpleBinaryKernelImplCPU, SimpleUnaryKernelImplCPU} from './shared';
 
 export const CHECK_NAN_SNIPPET_UNARY = `if (isnan(x)) return x;`;
 
-export const CHECK_NAN_SNIPPET_BINARY = `
-  if (isnan(a)) return a;
-  if (isnan(b)) return b;
-`;
-
-export const CHECK_NAN_SNIPPET_BINARY_PACKED = `
-  result.r = isNaN.r > 0. ? NAN : result.r;
-  result.g = isNaN.g > 0. ? NAN : result.g;
-  result.b = isNaN.b > 0. ? NAN : result.b;
-  result.a = isNaN.a > 0. ? NAN : result.a;
-`;
-
 type UnaryKernelFuncConfig = {
   opSnippet: string,
   packedOpSnippet?: string,

tfjs-backend-webgl/src/kernels/Atan2.ts

@@ -17,18 +17,21 @@
 
 import {Atan2} from '@tensorflow/tfjs-core';
 import {KernelConfig} from '@tensorflow/tfjs-core';
+import {CHECK_NAN_SNIPPET} from '../binaryop_gpu';
+import {CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
+import {binaryKernelFunc} from '../kernel_utils/kernel_funcs_utils';
 
-import {binaryKernelFunc, CHECK_NAN_SNIPPET_BINARY, CHECK_NAN_SNIPPET_BINARY_PACKED} from '../kernel_utils/kernel_funcs_utils';
-
-const ATAN2 = CHECK_NAN_SNIPPET_BINARY + `
+const ATAN2 = CHECK_NAN_SNIPPET + `
   return atan(a, b);
 `;
 
 const ATAN2_PACKED = `
   vec4 result = atan(a, b);
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  bvec4 isNaNA = isnan(a);
+  bvec4 isNaNB = isnan(b);
+  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
   ` +
-    CHECK_NAN_SNIPPET_BINARY_PACKED + `
+    CHECK_NAN_SNIPPET_PACKED + `
   return result;
 `;
 

tfjs-backend-webgl/src/kernels/Maximum.ts

@@ -18,7 +18,7 @@
 import {KernelConfig, KernelFunc, Maximum} from '@tensorflow/tfjs-core';
 
 import {CHECK_NAN_SNIPPET} from '../binaryop_gpu';
-import {CHECK_NAN_SNIPPET as CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
+import {CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
 import {binaryKernelFunc} from '../kernel_utils/kernel_funcs_utils';
 import {maximumImplCPU} from '../kernel_utils/shared';
 
@@ -28,7 +28,9 @@ const MAXIMUM = CHECK_NAN_SNIPPET + `
 
 const MAXIMUM_PACKED = `
   vec4 result = vec4(max(a, b));
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  bvec4 isNaNA = isnan(a);
+  bvec4 isNaNB = isnan(b);
+  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
   ` +
     CHECK_NAN_SNIPPET_PACKED + `
   return result;

tfjs-backend-webgl/src/kernels/Minimum.ts

@@ -18,7 +18,7 @@
 import {KernelConfig, KernelFunc, Minimum} from '@tensorflow/tfjs-core';
 
 import {CHECK_NAN_SNIPPET} from '../binaryop_gpu';
-import {CHECK_NAN_SNIPPET as CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
+import {CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
 import {binaryKernelFunc} from '../kernel_utils/kernel_funcs_utils';
 import {minimumImplCPU} from '../kernel_utils/shared';
 
@@ -28,7 +28,9 @@ const MINIMUM = CHECK_NAN_SNIPPET + `
 
 const MINIMUM_PACKED = `
   vec4 result = vec4(min(a, b));
-  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
+  bvec4 isNaNA = isnan(a);
+  bvec4 isNaNB = isnan(b);
+  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
   ` +
     CHECK_NAN_SNIPPET_PACKED + `
   return result;

tfjs-backend-webgl/src/kernels/Mod.ts

@@ -17,17 +17,17 @@
 
 import {KernelConfig, KernelFunc, Mod} from '@tensorflow/tfjs-core';
 
-import {CHECK_NAN_SNIPPET} from '../binaryop_packed_gpu';
+import {CHECK_NAN_SNIPPET_PACKED} from '../binaryop_packed_gpu';
 import {binaryKernelFunc} from '../kernel_utils/kernel_funcs_utils';
 
 const MOD = `if (b == 0.0) return NAN;
   return mod(a, b);`;
 
 const MOD_PACKED = `
   vec4 result = mod(a, b);
-  vec4 isNaN = vec4(equal(b, vec4(0.0)));
+  bvec4 isNaN = equal(b, vec4(0.0));
   ` +
-    CHECK_NAN_SNIPPET + `
+    CHECK_NAN_SNIPPET_PACKED + `
   return result;
 `;