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@hoff97/tensor-js

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PyTorch like deep learning inferrence library

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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 { OnnxNode } from '../../node'; export class BinaryNode extends OnnxNode { constructor(attributes, inputs, outputs, constants, onnxVersion, name, mode) { super(attributes, inputs, outputs, constants, onnxVersion, mode); this.name = name; } forward(inputs) { return __awaiter(this, void 0, void 0, function* () { if (this.onnxVersion < 13 && this.onnxVersion >= 7) { const a = inputs[0]; const b = inputs[1]; return [this.compute(a, b)]; } throw new Error(`${this.name} not implemented for onnx version ${this.onnxVersion}`); }); } getType() { return this.name; } delete() { } } //# sourceMappingURL=binaryNode.js.map