@hoff97/tensor-js/dist/lib/ops/sparse/binary/multiply/multiply.js

PyTorch like deep learning inferrence library

import { CPUTensor } from '../../../../tensor/cpu/tensor';
import { SparseTensor } from '../../../../tensor/sparse/tensor';
import { WASMTensor } from '../../../../tensor/wasm/tensor';
import { multiplyDenseCPU, multiplySparseCPU } from './cpu';
import { multiplyDenseWASM, multiplySparseWASM } from './wasm';
export function multiply(a, b, resultShape, alpha) {
    if (b instanceof SparseTensor) {
        return multiplySparse(a, b, resultShape, alpha);
    }
    else {
        return multiplyDense(a, b, resultShape, alpha);
    }
}
function multiplySparse(a, b, resultShape, alpha) {
    if (a.nnz !== b.nnz) {
        throw new Error('Element wise multiplication with two sparse tensors expects the same sparsity pattern, and thus the same number of nonzero entries in both tensors');
    }
    else if (a.denseDims !== b.denseDims) {
        throw new Error('Element wise multiplication with two sparse tensors expects the same number of sparse and dense dimensions in both tensors');
    }
    if (a.values instanceof CPUTensor) {
        return multiplySparseCPU(a, b, resultShape, alpha);
    }
    else if (a.values instanceof WASMTensor) {
        return multiplySparseWASM(a, b, resultShape, alpha);
    }
    throw new Error('Sparse-sparse matrix addition not supported on WebGL backend');
}
function multiplyDense(a, b, resultShape, alpha) {
    if (b instanceof CPUTensor) {
        return multiplyDenseCPU(a, b, resultShape, alpha);
    }
    else if (b instanceof WASMTensor) {
        return multiplyDenseWASM(a, b, resultShape, alpha);
    }
    throw new Error('Sparse-dense matrix element wise multiplication not supported on WASM/WebGL backend');
}
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