| 1 | {"version":3,"file":"avg_pool_3d.js","sourceRoot":"","sources":["../../src/ops/avg_pool_3d.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,WAAW,CAAC;AACjC,OAAO,EAAC,SAAS,EAAkC,MAAM,iBAAiB,CAAC;AAI3E,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAEnD,OAAO,KAAK,IAAI,MAAM,SAAS,CAAC;AAEhC,OAAO,EAAC,IAAI,EAAC,MAAM,QAAQ,CAAC;AAC5B,OAAO,EAAC,EAAE,EAAC,MAAM,aAAa,CAAC;AAC/B,OAAO,EAAC,OAAO,EAAC,MAAM,WAAW,CAAC;AAElC;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;GAmCG;AACH,SAAS,UAAU,CACf,CAAe,EAAE,UAA2C,EAC5D,OAAwC,EAAE,GAA0B,EACpE,eAAwC,EACxC,aAA8B,OAAO;IACvC,MAAM,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,WAAW,EAAE,SAAS,CAAC,CAAC;IAE3D,IAAI,GAAG,GAAG,EAAc,CAAC;IACzB,IAAI,YAAY,GAAG,KAAK,CAAC;IACzB,IAAI,EAAE,CAAC,IAAI,KAAK,CAAC,EAAE;QACjB,YAAY,GAAG,IAAI,CAAC;QACpB,GAAG,GAAG,OAAO,CAAC,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;KAC5E;IAED,IAAI,CAAC,MAAM,CACP,GAAG,CAAC,IAAI,KAAK,CAAC,EACd,GAAG,EAAE,CAAC,qDAAqD,GAAG,CAAC,IAAI,GAAG,CAAC,CAAC;IAC5E,IAAI,CAAC,MAAM,CACP,UAAU,KAAK,OAAO,EACtB,GAAG,EAAE,CAAC,yDAAyD;QAC3D,yBAAyB,UAAU,EAAE,CAAC,CAAC;IAE/C,IAAI,eAAe,IAAI,IAAI,EAAE;QAC3B,IAAI,CAAC,MAAM,CACP,IAAI,CAAC,KAAK,CAAC,GAAa,CAAC,EACzB,GAAG,EAAE,CAAC,yDAAyD;YAC3D,mBAAmB,eAAe,gBAAgB,GAAG,GAAG,CAAC,CAAC;KACnE;IAED,MAAM,MAAM,GAAoB,EAAC,CAAC,EAAE,GAAG,EAAC,CAAC;IAEzC,MAAM,KAAK,GACU,EAAC,UAAU,EAAE,OAAO,EAAE,GAAG,EAAE,eAAe,EAAE,UAAU,EAAC,CAAC;IAE7E,0DAA0D;IAC1D,IAAI,GAAG,GAAG,MAAM,CAAC,SAAS,CACZ,SAAS,EAAE,MAA8B,EACzC,KAA2B,CAAM,CAAC;IAEhD,GAAG,GAAG,IAAI,CAAC,GAAG,EAAE,GAAG,CAAC,KAAK,CAAC,CAAC;IAE3B,IAAI,YAAY,EAAE;QAChB,OAAO,OAAO,CACH,GAAG,EAAE,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,GAAG,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,GAAG,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,GAAG,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,CACnE,CAAC;KACP;IAED,OAAO,GAAG,CAAC;AACb,CAAC;AAED,MAAM,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAC,UAAU,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 {AvgPool3D, AvgPool3DAttrs, AvgPool3DInputs} from '../kernel_names';\nimport {NamedAttrMap} from '../kernel_registry';\nimport {Tensor4D, Tensor5D} from '../tensor';\nimport {NamedTensorMap} from '../tensor_types';\nimport {convertToTensor} from '../tensor_util_env';\nimport {TensorLike} from '../types';\nimport * as util from '../util';\n\nimport {cast} from './cast';\nimport {op} from './operation';\nimport {reshape} from './reshape';\n\n/**\n * Computes the 3D average pooling.\n *\n * ```js\n * const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);\n * const result = tf.avgPool3d(x, 2, 1, 'valid');\n * result.print();\n * ```\n *\n * @param x The input tensor, of rank 5 or rank 4 of shape\n * `[batch, depth, height, width, inChannels]`.\n * @param filterSize The filter size:\n * `[filterDepth, filterHeight, filterWidth]`.\n * If `filterSize` is a single number,\n * then `filterDepth == filterHeight == filterWidth`.\n * @param strides The strides of the pooling:\n * `[strideDepth, strideHeight, strideWidth]`.\n * If `strides` is a single number,\n * then `strideDepth == strideHeight == strideWidth`.\n * @param pad The type of padding algorithm.\n * - `same` and stride 1: output will be of same size as input,\n * regardless of filter size.\n * - `valid`: output will be smaller than input if filter is larger\n * than 1*1x1.\n * - For more info, see this guide:\n * [https://www.tensorflow.org/api_guides/python/nn#Convolution](\n * https://www.tensorflow.org/api_guides/python/nn#Convolution)\n * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is\n * provided, it will default to truncate.\n * @param dataFormat An optional string from: \"NDHWC\", \"NCDHW\". Defaults to\n * \"NDHWC\". Specify the data format of the input and output data. With the\n * default format \"NDHWC\", the data is stored in the order of: [batch,\n * depth, height, width, channels]. Only \"NDHWC\" is currently supported.\n *\n * @doc {heading: 'Operations', subheading: 'Convolution'}\n */\nfunction avgPool3d_<T extends Tensor4D|Tensor5D>(\n x: T|TensorLike, filterSize: [number, number, number]|number,\n strides: [number, number, number]|number, pad: 'valid'|'same'|number,\n dimRoundingMode?: 'floor'|'round'|'ceil',\n dataFormat: 'NDHWC'|'NCDHW' = 'NDHWC'): T {\n const $x = convertToTensor(x, 'x', 'avgPool3d', 'float32');\n\n let x5D = $x as Tensor5D;\n let reshapedTo5D = false;\n if ($x.rank === 4) {\n reshapedTo5D = true;\n x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n }\n\n util.assert(\n x5D.rank === 5,\n () => `Error in avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`);\n util.assert(\n dataFormat === 'NDHWC',\n () => `Error in avgPool3d: Only NDHWC is currently supported, ` +\n `but got dataFormat of ${dataFormat}`);\n\n if (dimRoundingMode != null) {\n util.assert(\n util.isInt(pad as number),\n () => `Error in avgPool3d: pad must be an integer when using, ` +\n `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);\n }\n\n const inputs: AvgPool3DInputs = {x: x5D};\n\n const attrs:\n AvgPool3DAttrs = {filterSize, strides, pad, dimRoundingMode, dataFormat};\n\n // tslint:disable-next-line: no-unnecessary-type-assertion\n let res = ENGINE.runKernel(\n AvgPool3D, inputs as {} as NamedTensorMap,\n attrs as {} as NamedAttrMap) as T;\n\n res = cast(res, x5D.dtype);\n\n if (reshapedTo5D) {\n return reshape(\n res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]) as\n T;\n }\n\n return res;\n}\n\nexport const avgPool3d = op({avgPool3d_});\n"]} |