onnxruntime/js/web/lib/wasm/jsep/webgpu/ops/unary-op.ts
Yulong Wang d471432e10
[js/webgpu] fix attribute cache key for 2 operators (#15710)
### Description
fix attribute cache key for LeakyRelu and ThresholdedRelu
2023-04-27 15:04:33 -07:00

220 lines
8.6 KiB
TypeScript

// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
import {TensorView} from '../../tensor';
import {MAX_CLIP, MIN_CLIP, ShapeUtil} from '../../util';
import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../attribute-with-cache-key';
import {ComputeContext, GpuDataType, ProgramInfo, ProgramInfoLoader, ProgramMetadata} from '../types';
import {ShaderHelper} from './common';
type BuiltinFunctionName = string;
type ElementwiseCustomExpression = (expression: string) => string;
type ElementwiseFunctionCall = BuiltinFunctionName|ElementwiseCustomExpression;
const createElementwiseProgramShader =
(shaderHelper: ShaderHelper, datasize: number, funcCall: ElementwiseFunctionCall,
additionalImplementation?: string): string => {
const vecSize = Math.ceil(datasize / 4);
let expression = '';
if (typeof funcCall === 'string') {
expression = `${funcCall}(a)`;
} else {
expression = funcCall('a');
}
return `
@group(0) @binding(0) var<storage, read> inputData : array<vec4<f32>>;
@group(0) @binding(1) var<storage, read_write> outputData : array<vec4<f32>>;
${additionalImplementation ?? ''}
${shaderHelper.mainStart()}
${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(vecSize)}
let a = inputData[global_idx];
outputData[global_idx] = ${expression};
}`;
};
const createElementwiseProgramInfo =
(metadata: ProgramMetadata, input: TensorView, funcCall: ElementwiseFunctionCall,
additionalImplementation?: string): ProgramInfo => ({
...metadata,
getShaderSource: shaderHelper =>
createElementwiseProgramShader(shaderHelper, ShapeUtil.size(input.dims), funcCall, additionalImplementation),
outputs: [{dims: input.dims, dataType: input.dataType, gpuDataType: GpuDataType.default}],
dispatchGroup: (inputTensors) =>
({x: Math.ceil(ShapeUtil.size(inputTensors[0].dims) / 64 /* workgroup size */ / 4 /* vec size */)})
});
const createElementwiseProgramInfoLoader =
(input: TensorView, name: string, funcCall: ElementwiseFunctionCall, additionalImplementation?: string,
cacheKey?: string): ProgramInfoLoader => {
const metadata: ProgramMetadata = {name, inputTypes: [GpuDataType.default], cacheHint: cacheKey};
return {
...metadata,
get: () => createElementwiseProgramInfo(metadata, input, funcCall, additionalImplementation)
};
};
export const abs = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Abs', 'abs'));
};
export const acos = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Acos', 'acos'));
};
export const acosh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Acosh', 'acosh'));
};
export const asin = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Asin', 'asin'));
};
export const asinh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Asinh', 'asinh'));
};
export const atan = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Atan', 'atan'));
};
export const atanh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Atanh', 'atanh'));
};
export interface ClipAttributes extends AttributeWithCacheKey {
readonly min: number;
readonly max: number;
}
export const clipV10 = (context: ComputeContext, attributes: ClipAttributes): void => {
context.compute(
createElementwiseProgramInfoLoader(
context.inputs[0], 'Clip', a => `clamp(${a}, clip_min_, clip_max_)`, `
const clip_min_: vec4<f32> = vec4(f32(${attributes.min}));
const clip_max_: vec4<f32> = vec4(f32(${attributes.max}));
`,
attributes.cacheKey),
{inputs: [0]});
};
const generateClipAttributesFromInputs = (inputs: readonly TensorView[]): ClipAttributes => {
const min = (inputs.length >= 2) ? inputs[1].getFloat32Array()[0] : MIN_CLIP;
const max = (inputs.length >= 3) ? inputs[2].getFloat32Array()[0] : MAX_CLIP;
return createAttributeWithCacheKey({min, max});
};
export const clip = (context: ComputeContext): void => {
const attributes = generateClipAttributesFromInputs(context.inputs);
clipV10(context, attributes);
};
export const ceil = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Ceil', 'ceil'));
};
export const cos = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Cos', 'cos'));
};
export const cosh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Cosh', 'cosh'));
};
export interface AlphaAttributes extends AttributeWithCacheKey {
readonly alpha: number;
}
export const parseAlphaAttributes = (attributes: Record<string, unknown>): AlphaAttributes =>
createAttributeWithCacheKey(attributes as {alpha: number});
export const elu = (context: ComputeContext, attributes: AlphaAttributes): void => {
context.compute(createElementwiseProgramInfoLoader(
context.inputs[0], 'Elu', a => `elu_vf32(${a})`, `
const elu_alpha_: f32 = f32(${attributes.alpha});
fn elu_f32(a: f32) -> f32 {
return select((exp(a) - 1.0) * elu_alpha_, a, a >= 0.0);
}
fn elu_vf32(v: vec4<f32>) -> vec4<f32> {
return vec4(elu_f32(v.x), elu_f32(v.y), elu_f32(v.z), elu_f32(v.w));
}`,
attributes.cacheKey));
};
export const erf = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Erf', a => `erf_vf32(${a})`, `
const r0: f32 = 0.3275911;
const r1: f32 = 0.254829592;
const r2: f32 = -0.284496736;
const r3: f32 = 1.421413741;
const r4: f32 = -1.453152027;
const r5: f32 = 1.061405429;
fn erf_vf32(v: vec4<f32>) -> vec4<f32> {
let absv = abs(v);
let x = 1.0 / (1.0 + r0 * absv);
return sign(v) * (1.0 - ((((r5 * x + r4) * x + r3) * x + r2) * x + r1) * x * exp(-absv * absv));
}`));
};
export const exp = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Exp', 'exp'));
};
export const floor = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Floor', 'floor'));
};
export const leakyRelu = (context: ComputeContext, attributes: AlphaAttributes): void => {
context.compute(createElementwiseProgramInfoLoader(
context.inputs[0], 'LeakyRelu', a => `select(leaky_relu_alpha_ * ${a}, ${a}, ${a} >= vec4<f32>(0.0))`,
`const leaky_relu_alpha_: f32 = f32(${attributes.alpha});`, attributes.cacheKey));
};
export const neg = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Neg', a => `-${a}`));
};
export const reciprocal = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Reciprocal', a => `1.0/${a}`));
};
export const relu = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(
context.inputs[0], 'Relu', a => `select(vec4<f32>(0.0), ${a}, ${a} > vec4<f32>(0.0))`));
};
export const sigmoid = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Sigmoid', a => `(1.0 / (1.0 + exp(-${a})))`));
};
export const sin = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Sin', 'sin'));
};
export const sinh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Sinh', 'sinh'));
};
export const sqrt = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Sqrt', 'sqrt'));
};
export const tan = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Tan', 'tan'));
};
export const tanh = (context: ComputeContext): void => {
context.compute(createElementwiseProgramInfoLoader(context.inputs[0], 'Tanh', 'tanh'));
};
export const thresholdedRelu = (context: ComputeContext, attributes: AlphaAttributes): number => {
context.compute(createElementwiseProgramInfoLoader(
context.inputs[0], 'ThresholdedRelu', a => `select(vec4<f32>(0.0), ${a}, ${a} > thresholded_relu_alpha_)`,
`const thresholded_relu_alpha_: vec4<f32> = vec4<f32>(${attributes.alpha});`, attributes.cacheKey));
return 0;
};