| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2018 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { ENGINE } from '../engine';
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| 18 | import { SparseToDense } from '../kernel_names';
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| 19 | import * as sparse_to_dense from '../ops/sparse_to_dense_util';
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| 20 | import { convertToTensor } from '../tensor_util_env';
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| 21 | import { op } from './operation';
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| 22 | /**
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| 23 | * Converts a sparse representation into a dense tensor.
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| 24 | *
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| 25 | * Builds an array dense with shape outputShape such that:
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| 26 | *
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| 27 | * // If sparseIndices is scalar
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| 28 | * dense[i] = (i == sparseIndices ? sparseValues : defaultValue)
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| 29 | *
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| 30 | * // If sparseIndices is a vector, then for each i
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| 31 | * dense[sparseIndices[i]] = sparseValues[i]
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| 32 | *
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| 33 | * // If sparseIndices is an n by d matrix, then for each i in [0, n)
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| 34 | * dense[sparseIndices[i][0], ..., sparseIndices[i][d-1]] = sparseValues[i]
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| 35 | * All other values in dense are set to defaultValue. If sparseValues is a
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| 36 | * scalar, all sparse indices are set to this single value.
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| 37 | *
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| 38 | * If indices are repeated the final value is summed over all values for those
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| 39 | * indices.
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| 40 | *
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| 41 | * ```js
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| 42 | * const indices = tf.tensor1d([4, 5, 6, 1, 2, 3], 'int32');
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| 43 | * const values = tf.tensor1d([10, 11, 12, 13, 14, 15], 'float32');
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| 44 | * const shape = [8];
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| 45 | * tf.sparseToDense(indices, values, shape).print();
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| 46 | * ```
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| 47 | *
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| 48 | * @param sparseIndices A 0-D, 1-D, or 2-D Tensor of type int32.
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| 49 | * sparseIndices[i] contains the complete index where sparseValues[i] will be
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| 50 | * placed.
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| 51 | * @param sparseValues A 0-D or 1-D Tensor. Values
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| 52 | * corresponding to each row of sparseIndices, or a scalar value to be used for
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| 53 | * all sparse indices.
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| 54 | * @param outputShape Shape of the dense output tensor. the type is inferred.
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| 55 | * @param defaultValue Scalar. Value to set for indices not specified in
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| 56 | * sparseIndices. Defaults to zero.
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| 57 | *
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| 58 | * @doc {heading: 'Operations', subheading: 'Normalization'}
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| 59 | */
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| 60 | function sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {
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| 61 | const $sparseIndices = convertToTensor(sparseIndices, 'sparseIndices', 'sparseToDense', 'int32');
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| 62 | const $sparseValues = convertToTensor(sparseValues, 'sparseValues', 'sparseToDense');
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| 63 | const $defaultValue = convertToTensor(defaultValue, 'defaultValue', 'sparseToDense', $sparseValues.dtype);
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| 64 | sparse_to_dense.validateInput($sparseIndices, $sparseValues, outputShape, $defaultValue);
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| 65 | const inputs = {
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| 66 | sparseIndices: $sparseIndices,
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| 67 | sparseValues: $sparseValues,
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| 68 | defaultValue: $defaultValue
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| 69 | };
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| 70 | const attrs = { outputShape };
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| 71 | return ENGINE.runKernel(SparseToDense, inputs, attrs);
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| 72 | }
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| 73 | export const sparseToDense = op({ sparseToDense_ });
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| 74 | //# 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