@hoff97/tensor-js/dist/lib/ops/gpu/unary/powerScalar.js

PyTorch like deep learning inferrence library

import { UnaryOperation } from './unaryOperation';
export class PowerScalarOperation extends UnaryOperation {
    constructor(tensorConstructor, dtype, allocator) {
        super(tensorConstructor, dtype, allocator);
    }
    operation(input) {
        throw new Error('Method not implemented.');
    }
    getFragmentShader(info) {
        return `
    void main() {
      initVars();

      if (power < 0.0) {
        gl_FragColor = vec4(factor,factor,factor,factor) / pow(texture2D(X, uv), vec4(-power,-power,-power,-power));
      } else {
        gl_FragColor = pow(texture2D(X, uv), vec4(power,power,power,power)) * factor;
      }
    }
    `;
    }
    calc(input) {
        return this.compute(input.input.shape, { X: input.input }, { factor: input.factor, power: input.power });
    }
    getCompilationInfo(input) {
        const info = super.getCompilationInfo(input);
        return Object.assign(Object.assign({}, info), { factor: input.factor, power: input.power });
    }
    getInputInfoString(input) {
        return `${super.getInputInfoString(input)}-${input.factor}-${input.power}`;
    }
    getVariables() {
        return `
    ${this.getVarModifier('factor')} float factor;
    ${this.getVarModifier('power')} float power;
    `;
    }
    getUniformAttrs() {
        return [
            { name: 'factor', type: 'float' },
            { name: 'power', type: 'float' },
        ];
    }
}
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