| 1 | {"version":3,"file":"mod.js","sourceRoot":"","sources":["../../src/ops/mod.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,WAAW,CAAC;AACjC,OAAO,EAAC,GAAG,EAAY,MAAM,iBAAiB,CAAC;AAG/C,OAAO,EAAC,cAAc,EAAC,MAAM,gBAAgB,CAAC;AAC9C,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAGnD,OAAO,EAAC,EAAE,EAAC,MAAM,aAAa,CAAC;AAE/B;;;;;;;;;;;;;;;;;;;;;;;;;;;GA2BG;AACH,SAAS,IAAI,CAAmB,CAAoB,EAAE,CAAoB;IACxE,IAAI,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,KAAK,CAAC,CAAC;IACxC,IAAI,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,KAAK,CAAC,CAAC;IACxC,CAAC,EAAE,EAAE,EAAE,CAAC,GAAG,cAAc,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC;IAElC,MAAM,MAAM,GAAc,EAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,EAAE,EAAC,CAAC;IAEzC,OAAO,MAAM,CAAC,SAAS,CAAC,GAAG,EAAE,MAA8B,CAAC,CAAC;AAC/D,CAAC;AAED,MAAM,CAAC,MAAM,GAAG,GAAG,EAAE,CAAC,EAAC,IAAI,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 {Mod, ModInputs} from '../kernel_names';\nimport {Tensor} from '../tensor';\nimport {NamedTensorMap} from '../tensor_types';\nimport {makeTypesMatch} from '../tensor_util';\nimport {convertToTensor} from '../tensor_util_env';\nimport {TensorLike} from '../types';\n\nimport {op} from './operation';\n\n/**\n * Returns the mod of a and b element-wise.\n * `floor(x / y) * y + mod(x, y) = x`\n * Supports broadcasting.\n *\n * We also expose `tf.modStrict` which has the same signature as this op and\n * asserts that `a` and `b` are the same shape (does not broadcast).\n *\n * ```js\n * const a = tf.tensor1d([1, 4, 3, 16]);\n * const b = tf.tensor1d([1, 2, 9, 4]);\n *\n * a.mod(b).print(); // or tf.mod(a, b)\n * ```\n *\n * ```js\n * // Broadcast a mod b.\n * const a = tf.tensor1d([2, 4, 6, 8]);\n * const b = tf.scalar(5);\n *\n * a.mod(b).print(); // or tf.mod(a, b)\n * ```\n *\n * @param a The first tensor.\n * @param b The second tensor. Must have the same type as `a`.\n *\n * @doc {heading: 'Operations', subheading: 'Arithmetic'}\n */\nfunction mod_<T extends Tensor>(a: Tensor|TensorLike, b: Tensor|TensorLike): T {\n let $a = convertToTensor(a, 'a', 'mod');\n let $b = convertToTensor(b, 'b', 'mod');\n [$a, $b] = makeTypesMatch($a, $b);\n\n const inputs: ModInputs = {a: $a, b: $b};\n\n return ENGINE.runKernel(Mod, inputs as {} as NamedTensorMap);\n}\n\nexport const mod = op({mod_});\n"]} |