@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
39 lines • 1.78 kB
JavaScript
/**
* Validate sparseToDense inputs.
*
* @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
* sparseIndices[i] contains the complete index where sparseValues[i] will be
* placed.
* @param sparseValues A 0-D or 1-D Tensor. Values
* corresponding to each row of sparseIndices, or a scalar value to be used for
* all sparse indices.
* @param outputShape number[]. Shape of the dense output tensor.
* @param validateIndices boolean. indice validation is not supported, error
* will be thrown if it is set.
*/
export function validateInput(sparseIndices, sparseValues, outputShape, defaultValues) {
if (sparseIndices.dtype !== 'int32') {
throw new Error('tf.sparseToDense() expects the indices to be int32 type,' +
` but the dtype was ${sparseIndices.dtype}.`);
}
if (sparseIndices.rank > 2) {
throw new Error('sparseIndices should be a scalar, vector, or matrix,' +
` but got shape ${sparseIndices.shape}.`);
}
const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;
const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;
if (outputShape.length !== numDims) {
throw new Error('outputShape has incorrect number of elements:,' +
` ${outputShape.length}, should be: ${numDims}.`);
}
const numValues = sparseValues.size;
if (!(sparseValues.rank === 0 ||
sparseValues.rank === 1 && numValues === numElems)) {
throw new Error('sparseValues has incorrect shape ' +
`${sparseValues.shape}, should be [] or [${numElems}]`);
}
if (sparseValues.dtype !== defaultValues.dtype) {
throw new Error('sparseValues.dtype must match defaultValues.dtype');
}
}
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