| 1 | {"version":3,"file":"dense_bincount.js","sourceRoot":"","sources":["../../src/ops/dense_bincount.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,WAAW,CAAC;AACjC,OAAO,EAAC,aAAa,EAA0C,MAAM,iBAAiB,CAAC;AAIvF,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAEnD,OAAO,KAAK,IAAI,MAAM,SAAS,CAAC;AAEhC,OAAO,EAAC,EAAE,EAAC,MAAM,aAAa,CAAC;AAE/B;;;;;;;;;;;;;;;;;;GAkBG;AACH,SAAS,cAAc,CACnB,CAAe,EAAE,OAAqB,EAAE,IAAY,EACpD,YAAY,GAAG,KAAK;IACtB,MAAM,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,eAAe,CAAC,CAAC;IACpD,MAAM,QAAQ,GAAG,eAAe,CAAC,OAAO,EAAE,SAAS,EAAE,eAAe,CAAC,CAAC;IAEtE,IAAI,CAAC,MAAM,CACP,EAAE,CAAC,KAAK,KAAK,OAAO,EACpB,GAAG,EAAE,CAAC,gCAAgC;QAClC,gCAAgC,EAAE,CAAC,KAAK,EAAE,CAAC,CAAC;IACpD,IAAI,CAAC,MAAM,CACP,EAAE,CAAC,IAAI,IAAI,CAAC,EACZ,GAAG,EAAE,CAAC,gEAAgE;QAClE,QAAQ,EAAE,CAAC,IAAI,GAAG,CAAC,CAAC;IAC5B,IAAI,CAAC,MAAM,CAAC,IAAI,IAAI,CAAC,EAAE,GAAG,EAAE,CAAC,sCAAsC,IAAI,GAAG,CAAC,CAAC;IAC5E,IAAI,CAAC,MAAM,CACP,QAAQ,CAAC,IAAI,KAAK,EAAE,CAAC,IAAI,IAAI,QAAQ,CAAC,IAAI,KAAK,CAAC,EAChD,GAAG,EAAE,CACD,mEAAmE;QACnE,8BAA8B,EAAE,CAAC,KAAK,mBAAmB;QACzD,GAAG,QAAQ,CAAC,KAAK,GAAG,CAAC,CAAC;IAE9B,MAAM,MAAM,GAAwB,EAAC,CAAC,EAAE,EAAE,EAAE,OAAO,EAAE,QAAQ,EAAC,CAAC;IAC/D,MAAM,KAAK,GAAuB,EAAC,IAAI,EAAE,YAAY,EAAC,CAAC;IAEvD,OAAO,MAAM,CAAC,SAAS,CACnB,aAAa,EAAE,MAA8B,EAC7C,KAA2B,CAAC,CAAC;AACnC,CAAC;AAED,MAAM,CAAC,MAAM,aAAa,GAAG,EAAE,CAAC,EAAC,cAAc,EAAC,CAAC,CAAC","sourcesContent":["/**\n * @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport {ENGINE} from '../engine';\nimport {DenseBincount, DenseBincountAttrs, DenseBincountInputs} from '../kernel_names';\nimport {NamedAttrMap} from '../kernel_registry';\nimport {Tensor1D, Tensor2D} from '../tensor';\nimport {NamedTensorMap} from '../tensor_types';\nimport {convertToTensor} from '../tensor_util_env';\nimport {TensorLike} from '../types';\nimport * as util from '../util';\n\nimport {op} from './operation';\n\n/**\n * Outputs a vector with length `size` and the same dtype as `weights`.\n *\n * If `weights` are empty, then index `i` stores the number of times the value\n * `i` is counted in `x`. If `weights` are non-empty, then index `i` stores the\n * sum of the value in `weights` at each index where the corresponding value in\n * `x` is `i`.\n *\n * Values in `x` outside of the range [0, size) are ignored.\n *\n * @param x The input int tensor, rank 1 or rank 2.\n * @param weights The weights tensor, must have the same shape as x, or a\n * length-0 Tensor, in which case it acts as all weights equal to 1.\n * @param size Non-negative integer.\n * @param binaryOutput Optional. Whether the kernel should count the appearance\n * or number of occurrences. Defaults to False.\n *\n * @doc {heading: 'Operations', subheading: 'Reduction'}\n */\nfunction denseBincount_<T extends Tensor1D|Tensor2D>(\n x: T|TensorLike, weights: T|TensorLike, size: number,\n binaryOutput = false): T {\n const $x = convertToTensor(x, 'x', 'denseBincount');\n const $weights = convertToTensor(weights, 'weights', 'denseBincount');\n\n util.assert(\n $x.dtype === 'int32',\n () => `Error in denseBincount: input ` +\n `dtype must be int32, but got ${$x.dtype}`);\n util.assert(\n $x.rank <= 2,\n () => `Error in denseBincount: input must be at most rank 2, but got ` +\n `rank ${$x.rank}.`);\n util.assert(size >= 0, () => `size must be non-negative, but got ${size}.`);\n util.assert(\n $weights.size === $x.size || $weights.size === 0,\n () =>\n `Error in denseBincount: weights must have the same shape as x or ` +\n `0-length, but got x shape: ${$x.shape}, weights shape: ` +\n `${$weights.shape}.`);\n\n const inputs: DenseBincountInputs = {x: $x, weights: $weights};\n const attrs: DenseBincountAttrs = {size, binaryOutput};\n\n return ENGINE.runKernel(\n DenseBincount, inputs as {} as NamedTensorMap,\n attrs as {} as NamedAttrMap);\n}\n\nexport const denseBincount = op({denseBincount_});\n"]} |