@hoff97/tensor-js/dist/lib/onnx/nodes/gather.js

PyTorch like deep learning inferrence library

var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
    return new (P || (P = Promise))(function (resolve, reject) {
        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
        step((generator = generator.apply(thisArg, _arguments || [])).next());
    });
};
import { CPUTensor } from '../../tensor/cpu/tensor';
import { OnnxNode } from '../node';
export class GatherNode extends OnnxNode {
    constructor(attributes, inputs, outputs, constants, onnxVersion, mode) {
        super(attributes, inputs, outputs, constants, onnxVersion, mode);
        this.axis = this.getAttributeInt('axis') || 0;
    }
    forward(inputs) {
        return __awaiter(this, void 0, void 0, function* () {
            const x = inputs[0];
            const indices = inputs[1];
            if (!(indices instanceof CPUTensor)) {
                throw new Error('Gather requires CPU tensor for the indices');
            }
            return [x.gather(this.axis, indices)];
        });
    }
    getType() {
        return 'Gather';
    }
    delete() { }
}
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