gx

chenyc

2025-06-12 7b72ac13a83764a662159d4a49b7fffb90476ecb

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
import { FusedBatchNorm, util } from '@tensorflow/tfjs-core';
import { assertNotComplex } from '../cpu_util';
export function batchNorm(args) {
    const { inputs, backend, attrs } = args;
    const { x, scale, offset, mean, variance } = inputs;
    util.assert(mean.shape.length === variance.shape.length, () => 'Batch normalization gradient requires mean and variance to have ' +
        'equal ranks.');
    util.assert(offset == null || mean.shape.length === offset.shape.length, () => 'Batch normalization gradient requires mean and offset to have ' +
        'equal ranks.');
    util.assert(scale == null || mean.shape.length === scale.shape.length, () => 'Batch normalization gradient requires mean and scale to have ' +
        'equal ranks.');
    assertNotComplex([x, mean, variance, scale, offset], 'batchNorm');
    let { varianceEpsilon } = attrs;
    if (varianceEpsilon == null) {
        varianceEpsilon = 0.001;
    }
    const xVals = backend.data.get(x.dataId).values;
    const mVals = backend.data.get(mean.dataId).values;
    const varVals = backend.data.get(variance.dataId).values;
    const sVals = scale ? backend.data.get(scale.dataId).values :
        new Float32Array([1]);
    const offVals = offset ?
        backend.data.get(offset.dataId).values :
        new Float32Array([0]);
    const outVals = new Float32Array(xVals.length);
    const offValsLength = offVals.length;
    const sValsLength = sVals.length;
    const varValsLength = varVals.length;
    const mValsLength = mVals.length;
    let offi = 0;
    let mi = 0;
    let si = 0;
    let vi = 0;
    for (let i = 0; i < xVals.length; ++i) {
        outVals[i] = offVals[offi++] +
            (xVals[i] - mVals[mi++]) * sVals[si++] /
                Math.sqrt(varVals[vi++] + varianceEpsilon);
        if (offi >= offValsLength) {
            offi = 0;
        }
        if (mi >= mValsLength) {
            mi = 0;
        }
        if (si >= sValsLength) {
            si = 0;
        }
        if (vi >= varValsLength) {
            vi = 0;
        }
    }
    return backend.makeTensorInfo(x.shape, x.dtype, outVals);
}
export const batchNormConfig = {
    kernelName: FusedBatchNorm,
    backendName: 'cpu',
    kernelFunc: batchNorm,
};
//# sourceMappingURL=data:application/json;base64,{"version":3,"file":"BatchNorm.js","sourceRoot":"","sources":["../../../../../../tfjs-backend-cpu/src/kernels/BatchNorm.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,cAAc,EAA+F,IAAI,EAAC,MAAM,uBAAuB,CAAC;AAGxJ,OAAO,EAAC,gBAAgB,EAAC,MAAM,aAAa,CAAC;AAE7C,MAAM,UAAU,SAAS,CAAC,IAIzB;IACC,MAAM,EAAC,MAAM,EAAE,OAAO,EAAE,KAAK,EAAC,GAAG,IAAI,CAAC;IACtC,MAAM,EAAC,CAAC,EAAE,KAAK,EAAE,MAAM,EAAE,IAAI,EAAE,QAAQ,EAAC,GAAG,MAAM,CAAC;IAElD,IAAI,CAAC,MAAM,CACP,IAAI,CAAC,KAAK,CAAC,MAAM,KAAK,QAAQ,CAAC,KAAK,CAAC,MAAM,EAC3C,GAAG,EAAE,CAAC,kEAAkE;QACpE,cAAc,CAAC,CAAC;IACxB,IAAI,CAAC,MAAM,CACP,MAAM,IAAI,IAAI,IAAI,IAAI,CAAC,KAAK,CAAC,MAAM,KAAK,MAAM,CAAC,KAAK,CAAC,MAAM,EAC3D,GAAG,EAAE,CAAC,gEAAgE;QAClE,cAAc,CAAC,CAAC;IACxB,IAAI,CAAC,MAAM,CACP,KAAK,IAAI,IAAI,IAAI,IAAI,CAAC,KAAK,CAAC,MAAM,KAAK,KAAK,CAAC,KAAK,CAAC,MAAM,EACzD,GAAG,EAAE,CAAC,+DAA+D;QACjE,cAAc,CAAC,CAAC;IAExB,gBAAgB,CAAC,CAAC,CAAC,EAAE,IAAI,EAAE,QAAQ,EAAE,KAAK,EAAE,MAAM,CAAC,EAAE,WAAW,CAAC,CAAC;IAElE,IAAI,EAAC,eAAe,EAAC,GAAG,KAAK,CAAC;IAC9B,IAAI,eAAe,IAAI,IAAI,EAAE;QAC3B,eAAe,GAAG,KAAK,CAAC;KACzB;IAED,MAAM,KAAK,GAAG,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC,CAAC,MAAM,CAAC,CAAC,MAAoB,CAAC;IAC9D,MAAM,KAAK,GAAG,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,MAAM,CAAC,CAAC,MAAoB,CAAC;IACjE,MAAM,OAAO,GAAG,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,QAAQ,CAAC,MAAM,CAAC,CAAC,MAAoB,CAAC;IACvE,MAAM,KAAK,GAAG,KAAK,CAAC,CAAC,CAAC,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,KAAK,CAAC,MAAM,CAAC,CAAC,MAAoB,CAAC,CAAC;QACrD,IAAI,YAAY,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;IAC5C,MAAM,OAAO,GAAG,MAAM,CAAC,CAAC;QACpB,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,MAAM,CAAC,MAAM,CAAC,CAAC,MAAoB,CAAC,CAAC;QACtD,IAAI,YAAY,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;IAC1B,MAAM,OAAO,GAAG,IAAI,YAAY,CAAC,KAAK,CAAC,MAAM,CAAC,CAAC;IAE/C,MAAM,aAAa,GAAG,OAAO,CAAC,MAAM,CAAC;IACrC,MAAM,WAAW,GAAG,KAAK,CAAC,MAAM,CAAC;IACjC,MAAM,aAAa,GAAG,OAAO,CAAC,MAAM,CAAC;IACrC,MAAM,WAAW,GAAG,KAAK,CAAC,MAAM,CAAC;IAEjC,IAAI,IAAI,GAAG,CAAC,CAAC;IACb,IAAI,EAAE,GAAG,CAAC,CAAC;IACX,IAAI,EAAE,GAAG,CAAC,CAAC;IACX,IAAI,EAAE,GAAG,CAAC,CAAC;IACX,KAAK,IAAI,CAAC,GAAG,CAAC,EAAE,CAAC,GAAG,KAAK,CAAC,MAAM,EAAE,EAAE,CAAC,EAAE;QACrC,OAAO,CAAC,CAAC,CAAC,GAAG,OAAO,CAAC,IAAI,EAAE,CAAC;YACxB,CAAC,KAAK,CAAC,CAAC,CAAC,GAAG,KAAK,CAAC,EAAE,EAAE,CAAC,CAAC,GAAG,KAAK,CAAC,EAAE,EAAE,CAAC;gBAClC,IAAI,CAAC,IAAI,CAAC,OAAO,CAAC,EAAE,EAAE,CAAC,GAAG,eAAe,CAAC,CAAC;QACnD,IAAI,IAAI,IAAI,aAAa,EAAE;YACzB,IAAI,GAAG,CAAC,CAAC;SACV;QACD,IAAI,EAAE,IAAI,WAAW,EAAE;YACrB,EAAE,GAAG,CAAC,CAAC;SACR;QACD,IAAI,EAAE,IAAI,WAAW,EAAE;YACrB,EAAE,GAAG,CAAC,CAAC;SACR;QACD,IAAI,EAAE,IAAI,aAAa,EAAE;YACvB,EAAE,GAAG,CAAC,CAAC;SACR;KACF;IACD,OAAO,OAAO,CAAC,cAAc,CAAC,CAAC,CAAC,KAAK,EAAE,CAAC,CAAC,KAAK,EAAE,OAAO,CAAC,CAAC;AAC3D,CAAC;AAED,MAAM,CAAC,MAAM,eAAe,GAAiB;IAC3C,UAAU,EAAE,cAAc;IAC1B,WAAW,EAAE,KAAK;IAClB,UAAU,EAAE,SAAkC;CAC/C,CAAC","sourcesContent":["/**\n * @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport {FusedBatchNorm, FusedBatchNormAttrs, FusedBatchNormInputs, KernelConfig, KernelFunc, TensorInfo, TypedArray, util} from '@tensorflow/tfjs-core';\n\nimport {MathBackendCPU} from '../backend_cpu';\nimport {assertNotComplex} from '../cpu_util';\n\nexport function batchNorm(args: {\n  inputs: FusedBatchNormInputs,\n  backend: MathBackendCPU,\n  attrs: FusedBatchNormAttrs\n}): TensorInfo {\n  const {inputs, backend, attrs} = args;\n  const {x, scale, offset, mean, variance} = inputs;\n\n  util.assert(\n      mean.shape.length === variance.shape.length,\n      () => 'Batch normalization gradient requires mean and variance to have ' +\n          'equal ranks.');\n  util.assert(\n      offset == null || mean.shape.length === offset.shape.length,\n      () => 'Batch normalization gradient requires mean and offset to have ' +\n          'equal ranks.');\n  util.assert(\n      scale == null || mean.shape.length === scale.shape.length,\n      () => 'Batch normalization gradient requires mean and scale to have ' +\n          'equal ranks.');\n\n  assertNotComplex([x, mean, variance, scale, offset], 'batchNorm');\n\n  let {varianceEpsilon} = attrs;\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 0.001;\n  }\n\n  const xVals = backend.data.get(x.dataId).values as TypedArray;\n  const mVals = backend.data.get(mean.dataId).values as TypedArray;\n  const varVals = backend.data.get(variance.dataId).values as TypedArray;\n  const sVals = scale ? backend.data.get(scale.dataId).values as TypedArray :\n                        new Float32Array([1]);\n  const offVals = offset ?\n      backend.data.get(offset.dataId).values as TypedArray :\n      new Float32Array([0]);\n  const outVals = new Float32Array(xVals.length);\n\n  const offValsLength = offVals.length;\n  const sValsLength = sVals.length;\n  const varValsLength = varVals.length;\n  const mValsLength = mVals.length;\n\n  let offi = 0;\n  let mi = 0;\n  let si = 0;\n  let vi = 0;\n  for (let i = 0; i < xVals.length; ++i) {\n    outVals[i] = offVals[offi++] +\n        (xVals[i] - mVals[mi++]) * sVals[si++] /\n            Math.sqrt(varVals[vi++] + varianceEpsilon);\n    if (offi >= offValsLength) {\n      offi = 0;\n    }\n    if (mi >= mValsLength) {\n      mi = 0;\n    }\n    if (si >= sValsLength) {\n      si = 0;\n    }\n    if (vi >= varValsLength) {\n      vi = 0;\n    }\n  }\n  return backend.makeTensorInfo(x.shape, x.dtype, outVals);\n}\n\nexport const batchNormConfig: KernelConfig = {\n  kernelName: FusedBatchNorm,\n  backendName: 'cpu',\n  kernelFunc: batchNorm as unknown as KernelFunc,\n};\n"]}