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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); 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; //# sourceMappingURL=sparse_to_dense_util.js.map