| 1 | {"version":3,"file":"where_async.js","sourceRoot":"","sources":["../../src/ops/where_async.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AACH,OAAO,EAAC,SAAS,EAAC,MAAM,wBAAwB,CAAC;AAEjD,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAGnD;;;;;;;;;;;;;;;;;;;GAmBG;AACH,KAAK,UAAU,WAAW,CAAC,SAA4B;IACrD,MAAM,UAAU,GACZ,eAAe,CAAC,SAAS,EAAE,WAAW,EAAE,YAAY,EAAE,MAAM,CAAC,CAAC;IAClE,MAAM,IAAI,GAAG,MAAM,UAAU,CAAC,IAAI,EAAE,CAAC;IACrC,MAAM,GAAG,GAAG,SAAS,CAAC,UAAU,CAAC,KAAK,EAAE,IAAI,CAAC,CAAC;IAC9C,IAAI,SAAS,KAAK,UAAU,EAAE;QAC5B,UAAU,CAAC,OAAO,EAAE,CAAC;KACtB;IACD,OAAO,GAAG,CAAC;AACb,CAAC;AAED,MAAM,CAAC,MAAM,UAAU,GAAG,WAAW,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 */\nimport {whereImpl} from '../backends/where_impl';\nimport {Tensor, Tensor2D} from '../tensor';\nimport {convertToTensor} from '../tensor_util_env';\nimport {TensorLike} from '../types';\n\n/**\n * Returns the coordinates of true elements of condition.\n *\n * The coordinates are returned in a 2-D tensor where the first dimension (rows)\n * represents the number of true elements, and the second dimension (columns)\n * represents the coordinates of the true elements. Keep in mind, the shape of\n * the output tensor can vary depending on how many true values there are in\n * input. Indices are output in row-major order. The resulting tensor has the\n * shape `[numTrueElems, condition.rank]`.\n *\n * This is analogous to calling the python `tf.where(cond)` without an x or y.\n *\n * ```js\n * const cond = tf.tensor1d([false, false, true], 'bool');\n * const result = await tf.whereAsync(cond);\n * result.print();\n * ```\n *\n * @doc {heading: 'Operations', subheading: 'Logical'}\n */\nasync function whereAsync_(condition: Tensor|TensorLike): Promise<Tensor2D> {\n const $condition =\n convertToTensor(condition, 'condition', 'whereAsync', 'bool');\n const vals = await $condition.data();\n const res = whereImpl($condition.shape, vals);\n if (condition !== $condition) {\n $condition.dispose();\n }\n return res;\n}\n\nexport const whereAsync = whereAsync_;\n"]} |