| 1 | {"version":3,"file":"maximum.js","sourceRoot":"","sources":["../../src/ops/maximum.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,WAAW,CAAC;AACjC,OAAO,EAAC,OAAO,EAAgB,MAAM,iBAAiB,CAAC;AAGvD,OAAO,EAAC,cAAc,EAAC,MAAM,gBAAgB,CAAC;AAC9C,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAGnD,OAAO,EAAC,0BAA0B,EAAC,MAAM,kBAAkB,CAAC;AAC5D,OAAO,EAAC,IAAI,EAAC,MAAM,QAAQ,CAAC;AAC5B,OAAO,EAAC,EAAE,EAAC,MAAM,aAAa,CAAC;AAE/B;;;;;;;;;;;;;;;;;;;;;;;;;;GA0BG;AACH,SAAS,QAAQ,CACb,CAAoB,EAAE,CAAoB;IAC5C,IAAI,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,SAAS,CAAC,CAAC;IAC5C,IAAI,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,SAAS,CAAC,CAAC;IAC5C,CAAC,EAAE,EAAE,EAAE,CAAC,GAAG,cAAc,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC;IAElC,IAAI,EAAE,CAAC,KAAK,KAAK,MAAM,EAAE;QACvB,EAAE,GAAG,IAAI,CAAC,EAAE,EAAE,OAAO,CAAC,CAAC;QACvB,EAAE,GAAG,IAAI,CAAC,EAAE,EAAE,OAAO,CAAC,CAAC;KACxB;IACD,0BAA0B,CAAC,EAAE,CAAC,KAAK,EAAE,EAAE,CAAC,KAAK,CAAC,CAAC;IAE/C,MAAM,MAAM,GAAkB,EAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,EAAE,EAAC,CAAC;IAE7C,OAAO,MAAM,CAAC,SAAS,CAAC,OAAO,EAAE,MAA8B,CAAC,CAAC;AACnE,CAAC;AAED,MAAM,CAAC,MAAM,OAAO,GAAG,EAAE,CAAC,EAAC,QAAQ,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 {Maximum, MaximumInputs} 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 {assertAndGetBroadcastShape} from './broadcast_util';\nimport {cast} from './cast';\nimport {op} from './operation';\n\n/**\n * Returns the max of a and b (`a > b ? a : b`) element-wise.\n * Supports broadcasting.\n *\n * We also expose `tf.maximumStrict` 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.maximum(b).print(); // or tf.maximum(a, b)\n * ```\n *\n * ```js\n * // Broadcast maximum a with b.\n * const a = tf.tensor1d([2, 4, 6, 8]);\n * const b = tf.scalar(5);\n *\n * a.maximum(b).print(); // or tf.maximum(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 maximum_<T extends Tensor>(\n a: Tensor|TensorLike, b: Tensor|TensorLike): T {\n let $a = convertToTensor(a, 'a', 'maximum');\n let $b = convertToTensor(b, 'b', 'maximum');\n [$a, $b] = makeTypesMatch($a, $b);\n\n if ($a.dtype === 'bool') {\n $a = cast($a, 'int32');\n $b = cast($b, 'int32');\n }\n assertAndGetBroadcastShape($a.shape, $b.shape);\n\n const inputs: MaximumInputs = {a: $a, b: $b};\n\n return ENGINE.runKernel(Maximum, inputs as {} as NamedTensorMap);\n}\n\nexport const maximum = op({maximum_});\n"]} |