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feat(paddlejs-backend-cpu): add flatten_continuous_range and pool2d_max #146

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74 changes: 74 additions & 0 deletions packages/paddlejs-backend-cpu/src/ops/flatten_contiguous_range.ts
View file Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,74 @@
import { Tensor } from './Tensor';
import { getInt } from './utils';

/* eslint-disable max-statements */
function main(tensorMap: Map<string, Tensor>, attrs: Attrs, runtime: i32): f32[] {
// v1 paddle.fluid parameter
let axis = attrs.axis;

// v2 paddle.nn parameter
let start_axis = attrs.start_axis;
let stop_axis = attrs.stop_axis;

// generic parameters
const origin = tensorMap.get('origin') as Tensor;
const out = tensorMap.get('out_' + runtime) as Tensor;

const outShape: i32[] = (out as Tensor).shape;
const startIndex = out.runtime * length;
const originReducedShape: i32[] = (origin as Tensor).shapeReduced;
const outReducedShape: i32[] = (out as Tensor).shapeReduced;

const originData: f32[] = (origin as Tensor).data;

const outN = outShape[0];
const outC = outShape[1];
const outH = outShape[2];
const outW = outShape[3];

const originS0 = originReducedShape[0];
const originS1 = originReducedShape[1];
const originS2 = originReducedShape[2];

const outS0 = outReducedShape[0];
const outS1 = outReducedShape[1];
const outS2 = outReducedShape[2];

const result = new Array<f32>(out.total);

for (let n = 0; n < outN; n++) {
for (let c = 0; c < outC; c++) {
for (let h = 0; h < outH; h++) {
for (let w = 0; w < outW; w++) {

result[n * originS0 + c * originS1 + h * originS2 + w]
= originData[n * originS0 + c * originS1 + h * originS2 + w];

}
}
}
}
return result;
}
/* eslint-enable max-statements */

class Attrs {
axis: i32 = 1;

start_axis : i32 = 0;
stop_axis : i32 = -1;

constructor(data: Obj) {
this.start_axis = getInt('start_axis', data);
this.stop_axis = getInt('stop_axis', data);
this.axis = getInt('axis', data);
}
}

const behaviors = [];

export {
main,
Attrs,
behaviors
};
129 changes: 129 additions & 0 deletions packages/paddlejs-backend-cpu/src/ops/pool2d_max.ts
View file Open in desktop
Original file line number Diff line number Diff line change
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import { Tensor } from './Tensor';
import { getIntArray, getInt } from './utils';

/* eslint-disable max-statements, max-depth */
function main(tensorMap: Map<string, Tensor>, attrs: Attrs, runtime: i32): f32[] {
const origin = tensorMap.get('origin') as Tensor;
const out = tensorMap.get('out_' + runtime) as Tensor;

const originShape: i32[] = (origin as Tensor).shape;
const outShape: i32[] = (out as Tensor).shape;

const originData: f32[] = (origin as Tensor).data;

const originReducedShape: i32[] = (origin as Tensor).shapeReduced;
const outReducedShape: i32[] = (out as Tensor).shapeReduced;

const strides = attrs.strides;
const paddings = attrs.paddings;
const ksizes = attrs.ksize;
const pooling_type = attrs.pooling_type;

const stride_v = strides[0] || 1;
const stride_h = strides[1] || 1;
const ksize_x = ksizes[0] || 1;
const ksize_y = ksizes[1] || 1;
const padTop = paddings[0] || 0;
const padLeft = paddings[1] || 0;

const outB = outShape[0];
const outC = outShape[1];
const outH = outShape[2];
const outW = outShape[3];


const originH = originShape[2];
const originW = originShape[3];

const originS0 = originReducedShape[0];
const originS1 = originReducedShape[1];
const originS2 = originReducedShape[2];

const outS0 = outReducedShape[0];
const outS1 = outReducedShape[1];
const outS2 = outReducedShape[2];

const result = new Array<f32>(out.total);

for (let n = 0; n < outB; n++) {
for (let c = 0; c < outC; c++) {
for (let h = 0; h < outH; h++) {
for (let w = 0; w < outW; w++) {
let res = 0.0;
let count_pool = 0;
const oy_base = h * stride_v - padTop;
const ox_base = w * stride_h - padLeft;
for (let fy = 0; fy < ksize_y; fy++) {
const oy = oy_base + fy;
if (oy >= originH) {
break;
}
if (oy < 0) {
continue;
}
for (let fx = 0; fx < ksize_x; fx++) {
const ox = ox_base + fx;
if (ox >= originW) {
break;
}
if (ox < 0) {
continue;
}
// origin数据
const curr = originData[n * originS0 + c * originS1 + oy * originS2 + ox];
/* eslint-disable-next-line */
if (pooling_type == 1) {
// max-pool update
if (count_pool == 0){
res = curr;
count_pool++;
}
if (curr > res) {
res = curr;
}
}
else {
res += curr;
// 在平均池化模式忽略填充值(exclusive默认为true)
count_pool++;
}
}
}
/* eslint-disable-next-line */
if (pooling_type != 1) {
res = res / count_pool;
}
result[n * outS0 + c * outS1 + h * outS2 + w] = f32(res);
}
}
}
}

return result;
}
/* eslint-enable max-statements */

class Attrs {
strides: i32[] = [];
paddings: i32[] = [];
ksize: i32[] = [];
pooling_type: i32;
constructor(data: Obj) {
this.strides = getIntArray('strides', data);
this.paddings = getIntArray('paddings', data);
this.ksize = getIntArray('dilations', data);
this.pooling_type = getInt('groups', data);
}
}

const behaviors = [
'isMax',
'setPacked',
'isGlobalPooling'
];

export {
main,
Attrs,
behaviors
};

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