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@tensorflow-models/coco-ssd

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Object detection model (coco-ssd) in TensorFlow.js

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"use strict"; /** * @license * Copyright 2018 Google Inc. 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. * ============================================================================= */ Object.defineProperty(exports, "__esModule", { value: true }); var environment_1 = require("../environment"); var tensor_util_env_1 = require("../tensor_util_env"); var util = require("../util"); var operation_1 = require("./operation"); var slice_util = require("./slice_util"); /** * Extracts a 1D slice from 1D array starting at coordinates `begin` and is * of length `size`. See `slice` for details. */ function slice1d_(x, begin, size) { var $x = tensor_util_env_1.convertToTensor(x, 'x', 'slice1d'); util.assert($x.rank === 1, "slice1d expects a rank-1 tensor, but got a rank-" + $x.rank + " tensor"); return exports.slice($x, [begin], [size]); } /** * Extracts a 2D slice from a 2D array starting at coordinates `begin` and * is of size `size`. See `slice` for details. */ function slice2d_(x, begin, size) { var $x = tensor_util_env_1.convertToTensor(x, 'x', 'slice2d'); util.assert($x.rank === 2, "slice2d expects a rank-2 tensor, but got a rank-" + $x.rank + " tensor"); return exports.slice($x, begin, size); } /** * Extracts a 3D slice from a 3D array starting at coordinates `begin` and * is of size `size`. See `slice` for details. */ function slice3d_(x, begin, size) { var $x = tensor_util_env_1.convertToTensor(x, 'x', 'slice3d'); util.assert($x.rank === 3, "slice3d expects a rank-3 tensor, but got a rank-" + $x.rank + " tensor"); return exports.slice($x, begin, size); } /** * Extracts a 4D slice from a 4D array starting at coordinates `begin` and * is of size `size`. See `slice` for details. */ function slice4d_(x, begin, size) { var $x = tensor_util_env_1.convertToTensor(x, 'x', 'slice4d'); util.assert($x.rank === 4, "slice4d expects a rank-4 tensor, but got a rank-" + $x.rank + " tensor"); return exports.slice($x, begin, size); } /** * Extracts a slice from a `tf.Tensor` starting at coordinates `begin` * and is of size `size`. * * Also available are stricter rank-specific methods with the same signature * as this method that assert that `x` is of the given rank: * - `tf.slice1d` * - `tf.slice2d` * - `tf.slice3d` * - `tf.slice4d` * * ```js * const x = tf.tensor1d([1, 2, 3, 4]); * * x.slice([1], [2]).print(); * ``` * * ```js * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]); * * x.slice([1, 0], [1, 2]).print(); * ``` * @param x The input `tf.Tensor` to slice from. * @param begin The coordinates to start the slice from. The length can be * less than the rank of x - the rest of the axes will have implicit 0 as * start. Can also be a single number, in which case it specifies the * first axis. * @param size The size of the slice. The length can be less than the rank of * x - the rest of the axes will have implicit -1. A value of -1 requests * the rest of the dimensions in the axis. Can also be a single number, * in which case it specifies the size of the first axis. */ /** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */ function slice_(x, begin, size) { var $x = tensor_util_env_1.convertToTensor(x, 'x', 'slice'); if ($x.rank === 0) { throw new Error('Slicing scalar is not possible'); } // The following logic allows for more ergonomic calls. var begin_; if (typeof begin === 'number') { begin_ = [begin].concat(new Array($x.rank - 1).fill(0)); } else if (begin.length < $x.rank) { begin_ = begin.concat(new Array($x.rank - begin.length).fill(0)); } else { begin_ = begin.slice(); } var size_; if (size == null) { size_ = new Array($x.rank).fill(-1); } else if (typeof size === 'number') { size_ = [size].concat(new Array($x.rank - 1).fill(-1)); } else if (size.length < $x.rank) { size_ = size.concat(new Array($x.rank - size.length).fill(-1)); } else { size_ = size; } size_ = size_.map(function (d, i) { if (d >= 0) { return d; } else { util.assert(d === -1, 'Bad value in size'); return $x.shape[i] - begin_[i]; } }); slice_util.assertParamsValid($x, begin_, size_); var inputShape = $x.shape; var grad = function (dy) { // Create an Nx2 padding where the first column represents how many // zeros are prepended (at start) for each dimension, and the second // column indicates how many zeros are appended (at end). // The number of zeros to append is the shape of the input // elementwise-subtracted by both the begin vector and sizes vector. var paddings = []; for (var i = 0; i < dy.rank; i++) { paddings.push([begin_[i], inputShape[i] - begin_[i] - size_[i]]); } return { $x: function () { return dy.pad(paddings); } }; }; return environment_1.ENV.engine.runKernel(function (backend) { return backend.slice($x, begin_, size_); }, { $x: $x }, grad); } exports.slice = operation_1.op({ slice_: slice_ }); exports.slice1d = operation_1.op({ slice1d_: slice1d_ }); exports.slice2d = operation_1.op({ slice2d_: slice2d_ }); exports.slice3d = operation_1.op({ slice3d_: slice3d_ }); exports.slice4d = operation_1.op({ slice4d_: slice4d_ }); //# sourceMappingURL=slice.js.map