| 1 | {"version":3,"file":"space_to_batch_nd.js","sourceRoot":"","sources":["../../src/ops/space_to_batch_nd.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,WAAW,CAAC;AACjC,OAAO,EAAC,cAAc,EAA4C,MAAM,iBAAiB,CAAC;AAI1F,OAAO,EAAC,eAAe,EAAC,MAAM,oBAAoB,CAAC;AAEnD,OAAO,KAAK,IAAI,MAAM,SAAS,CAAC;AAEhC,OAAO,EAAC,EAAE,EAAC,MAAM,aAAa,CAAC;AAE/B;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;GA+CG;AACH,SAAS,eAAe,CACpB,CAAe,EAAE,UAAoB,EAAE,QAAoB;IAC7D,MAAM,EAAE,GAAG,eAAe,CAAC,CAAC,EAAE,GAAG,EAAE,gBAAgB,CAAC,CAAC;IAErD,IAAI,CAAC,MAAM,CACP,EAAE,CAAC,IAAI,IAAI,CAAC,GAAG,UAAU,CAAC,MAAM,EAChC,GAAG,EAAE,CAAC,cAAc,EAAE,CAAC,IAAI,kCACvB,UAAU,CAAC,MAAM,EAAE,CAAC,CAAC;IAE7B,IAAI,CAAC,MAAM,CACP,QAAQ,CAAC,MAAM,KAAK,UAAU,CAAC,MAAM,EACrC,GAAG,EAAE,CAAC,qBACF,QAAQ,CAAC,MAAM,kCAAkC,UAAU,CAAC,MAAM,EAAE,CAAC,CAAC;IAE9E,IAAI,CAAC,MAAM,CACP,EAAE,CAAC,KAAK,CAAC,MAAM,CACX,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,EAAE;QACV,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,IAAI,UAAU,CAAC,MAAM,EAAE;YACnC,OAAO,CAAC;gBACJ,CAAC,CAAC,CAAC,GAAG,QAAQ,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,QAAQ,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;oBACzC,UAAU,CAAC,CAAC,GAAG,CAAC,CAAC;oBACrB,CAAC,CAAC,CAAC;SACT;QACD,OAAO,CAAC,CAAC;IACX,CAAC,EACD,IAAI,CAAC,EACT,GAAG,EAAE,CAAC,4BAA4B,EAAE,CAAC,KAAK,CAAC,KAAK,CAAC,CAAC,CAAC,kBAC/C,QAAQ,CAAC,QAAQ,EAAE,qCACnB,UAAU,CAAC,QAAQ,EAAE,EAAE,CAAC,CAAC;IAEjC,MAAM,MAAM,GAAyB,EAAC,CAAC,EAAE,EAAE,EAAC,CAAC;IAC7C,MAAM,KAAK,GAAwB,EAAC,UAAU,EAAE,QAAQ,EAAC,CAAC;IAE1D,OAAO,MAAM,CAAC,SAAS,CACnB,cAAc,EAAE,MAA8B,EAC9C,KAA2B,CAAC,CAAC;AACnC,CAAC;AAED,MAAM,CAAC,MAAM,cAAc,GAAG,EAAE,CAAC,EAAC,eAAe,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 {SpaceToBatchND, SpaceToBatchNDAttrs, SpaceToBatchNDInputs} from '../kernel_names';\nimport {NamedAttrMap} from '../kernel_registry';\nimport {Tensor} 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 * This operation divides \"spatial\" dimensions `[1, ..., M]` of the input into\n * a grid of blocks of shape `blockShape`, and interleaves these blocks with\n * the \"batch\" dimension (0) such that in the output, the spatial\n * dimensions `[1, ..., M]` correspond to the position within the grid,\n * and the batch dimension combines both the position within a spatial block\n * and the original batch position. Prior to division into blocks,\n * the spatial dimensions of the input are optionally zero padded\n * according to `paddings`. See below for a precise description.\n *\n * ```js\n * const x = tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]);\n * const blockShape = [2, 2];\n * const paddings = [[0, 0], [0, 0]];\n *\n * x.spaceToBatchND(blockShape, paddings).print();\n * ```\n *\n * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +\n * remainingShape`, where spatialShape has `M` dimensions.\n * @param blockShape A 1-D array. Must have shape `[M]`, all values must\n * be >= 1.\n * @param paddings A 2-D array. Must have shape `[M, 2]`, all values must be >=\n * 0. `paddings[i] = [padStart, padEnd]` specifies the amount to zero-pad\n * from input dimension `i + 1`, which corresponds to spatial dimension `i`. It\n * is required that\n * `(inputShape[i + 1] + padStart + padEnd) % blockShape[i] === 0`\n *\n * This operation is equivalent to the following steps:\n *\n * 1. Zero-pad the start and end of dimensions `[1, ..., M]` of the input\n * according to `paddings` to produce `padded` of shape paddedShape.\n *\n * 2. Reshape `padded` to `reshapedPadded` of shape:\n * `[batch] + [paddedShape[1] / blockShape[0], blockShape[0], ...,\n * paddedShape[M] / blockShape[M-1], blockShape[M-1]] + remainingShape`\n *\n * 3. Permute dimensions of `reshapedPadded` to produce `permutedReshapedPadded`\n * of shape: `blockShape + [batch] + [paddedShape[1] / blockShape[0], ...,\n * paddedShape[M] / blockShape[M-1]] + remainingShape`\n *\n * 4. Reshape `permutedReshapedPadded` to flatten `blockShape` into the\n * batch dimension, producing an output tensor of shape:\n * `[batch * prod(blockShape)] + [paddedShape[1] / blockShape[0], ...,\n * paddedShape[M] / blockShape[M-1]] + remainingShape`\n *\n * @doc {heading: 'Tensors', subheading: 'Transformations'}\n */\nfunction spaceToBatchND_<T extends Tensor>(\n x: T|TensorLike, blockShape: number[], paddings: number[][]): T {\n const $x = convertToTensor(x, 'x', 'spaceToBatchND');\n\n util.assert(\n $x.rank >= 1 + blockShape.length,\n () => `input rank ${$x.rank} should be > than [blockShape] ${\n blockShape.length}`);\n\n util.assert(\n paddings.length === blockShape.length,\n () => `paddings.shape[0] ${\n paddings.length} must be equal to [blockShape] ${blockShape.length}`);\n\n util.assert(\n $x.shape.reduce(\n (a, b, i) => {\n if (i > 0 && i <= blockShape.length) {\n return a &&\n ((b + paddings[i - 1][0] + paddings[i - 1][1]) %\n blockShape[i - 1] ===\n 0);\n }\n return a;\n },\n true),\n () => `input spatial dimensions ${$x.shape.slice(1)} with paddings ${\n paddings.toString()} must be divisible by blockShapes ${\n blockShape.toString()}`);\n\n const inputs: SpaceToBatchNDInputs = {x: $x};\n const attrs: SpaceToBatchNDAttrs = {blockShape, paddings};\n\n return ENGINE.runKernel(\n SpaceToBatchND, inputs as {} as NamedTensorMap,\n attrs as {} as NamedAttrMap);\n}\n\nexport const spaceToBatchND = op({spaceToBatchND_});\n"]} |