@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import { ENGINE } from '../engine';
import { SparseToDense } from '../kernel_names';
import * as sparse_to_dense from '../ops/sparse_to_dense_util';
import { convertToTensor } from '../tensor_util_env';
import { op } from './operation';
/**
* Converts a sparse representation into a dense tensor.
*
* Builds an array dense with shape outputShape such that:
*
* // If sparseIndices is scalar
* dense[i] = (i == sparseIndices ? sparseValues : defaultValue)
*
* // If sparseIndices is a vector, then for each i
* dense[sparseIndices[i]] = sparseValues[i]
*
* // If sparseIndices is an n by d matrix, then for each i in [0, n)
* dense[sparseIndices[i][0], ..., sparseIndices[i][d-1]] = sparseValues[i]
* All other values in dense are set to defaultValue. If sparseValues is a
* scalar, all sparse indices are set to this single value.
*
* If indices are repeated the final value is summed over all values for those
* indices.
*
* ```js
* const indices = tf.tensor1d([4, 5, 6, 1, 2, 3], 'int32');
* const values = tf.tensor1d([10, 11, 12, 13, 14, 15], 'float32');
* const shape = [8];
* tf.sparseToDense(indices, values, shape).print();
* ```
*
* @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 Shape of the dense output tensor. the type is inferred.
* @param defaultValue Scalar. Value to set for indices not specified in
* sparseIndices. Defaults to zero.
*
* @doc {heading: 'Operations', subheading: 'Normalization'}
*/
function sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {
const $sparseIndices = convertToTensor(sparseIndices, 'sparseIndices', 'sparseToDense', 'int32');
const $sparseValues = convertToTensor(sparseValues, 'sparseValues', 'sparseToDense');
const $defaultValue = convertToTensor(defaultValue, 'defaultValue', 'sparseToDense', $sparseValues.dtype);
sparse_to_dense.validateInput($sparseIndices, $sparseValues, outputShape, $defaultValue);
const inputs = {
sparseIndices: $sparseIndices,
sparseValues: $sparseValues,
defaultValue: $defaultValue
};
const attrs = { outputShape };
return ENGINE.runKernel(SparseToDense, inputs, attrs);
}
export const sparseToDense = op({ sparseToDense_ });
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