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conv3d.ts
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/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import {ENGINE} from '../engine';
import {Conv3D, Conv3DAttrs, Conv3DInputs} from '../kernel_names';
import {NamedAttrMap} from '../kernel_registry';
import {Tensor4D, Tensor5D} from '../tensor';
import {NamedTensorMap} from '../tensor_types';
import {convertToTensor} from '../tensor_util_env';
import {TensorLike} from '../types';
import * as util from '../util';
import {eitherStridesOrDilationsAreOne, stridesOrDilationsArePositive} from './conv_util';
import {op} from './operation';
import {reshape} from './reshape';
/**
* Computes a 3D convolution over the input x.
*
* @param x The input tensor, of rank 5 or rank 4, of shape
* `[batch, depth, height, width, channels]`. If rank 4,
* batch of 1 is assumed.
* @param filter The filter, rank 5, of shape
* `[filterDepth, filterHeight, filterWidth, inChannels, outChannels]`.
* inChannels must match between input and filter.
* @param strides The strides of the convolution: `[strideDepth, strideHeight,
* strideWidth]`.
* @param pad The type of padding algorithm.
* - `same` and stride 1: output will be of same size as input,
* regardless of filter size.
* - `valid`: output will be smaller than input if filter is larger
* than 1x1.
* - For more info, see this guide:
* [https://www.tensorflow.org/api_docs/python/tf/nn/convolution](
* https://www.tensorflow.org/api_docs/python/tf/nn/convolution)
* @param dataFormat: An optional string from: "NDHWC", "NCDHW". Defaults to
* "NDHWC". Specify the data format of the input and output data. With the
* default format "NDHWC", the data is stored in the order of: [batch,
* depth, height, width, channels]. Only "NDHWC" is currently supported.
* @param dilations The dilation rates: `[dilationDepth, dilationHeight,
* dilationWidth]` in which we sample input values across the height
* and width dimensions in atrous convolution. Defaults to `[1, 1, 1]`.
* If `dilations` is a single number, then
* `dilationDepth == dilationHeight == dilationWidth`. If it is greater
* than 1, then all values of `strides` must be 1.
*
* @doc {heading: 'Operations', subheading: 'Convolution'}
*/
function conv3d_<T extends Tensor4D|Tensor5D>(
x: T|TensorLike, filter: Tensor5D|TensorLike,
strides: [number, number, number]|number, pad: 'valid'|'same',
dataFormat: 'NDHWC'|'NCDHW' = 'NDHWC',
dilations: [number, number, number]|number = [1, 1, 1]): T {
const $x = convertToTensor(x, 'x', 'conv3d');
const $filter = convertToTensor(filter, 'filter', 'conv3d');
let x5D = $x as Tensor5D;
let reshapedTo5D = false;
if ($x.rank === 4) {
reshapedTo5D = true;
x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);
}
util.assert(
x5D.rank === 5,
() => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`);
util.assert(
$filter.rank === 5,
() => `Error in conv3d: filter must be rank 5, but got rank ` +
`${$filter.rank}.`);
util.assert(
x5D.shape[4] === $filter.shape[3],
() => `Error in conv3d: depth of input (${x5D.shape[4]}) must match ` +
`input depth for filter ${$filter.shape[3]}.`);
util.assert(
eitherStridesOrDilationsAreOne(strides, dilations),
() => 'Error in conv3D: Either strides or dilations must be 1. ' +
`Got strides ${strides} and dilations '${dilations}'`);
util.assert(
dataFormat === 'NDHWC',
() => `Error in conv3d: got dataFormat of ${
dataFormat} but only NDHWC is currently supported.`);
util.assert(
stridesOrDilationsArePositive(dilations),
() => 'Error in conv3D: Dilated rates should be larger than 0.');
util.assert(
stridesOrDilationsArePositive(strides),
() => 'Error in conv3D: Strides should be larger than 0.');
const inputs: Conv3DInputs = {x: x5D, filter: $filter};
const attrs: Conv3DAttrs = {strides, pad, dataFormat, dilations};
// tslint:disable-next-line: no-unnecessary-type-assertion
const res = ENGINE.runKernel(
Conv3D, inputs as unknown as NamedTensorMap,
attrs as unknown as NamedAttrMap) as T;
if (reshapedTo5D) {
return reshape(
res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]) as
T;
}
return res;
}
export const conv3d = /* @__PURE__ */ op({conv3d_});