@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
42 lines • 1.92 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
/**
* 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.
*/
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 + "."));
}
var numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;
var 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 + "."));
}
var 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');
}
}
exports.validateInput = validateInput;
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