| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { ENGINE } from '../engine';
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| 18 | import { Conv2DBackpropFilter } from '../kernel_names';
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| 19 | import * as util from '../util';
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| 20 | import { op } from './operation';
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| 21 | import { reshape } from './reshape';
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| 22 | /**
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| 23 | * Computes the derivative of the filter of a 2D convolution.
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| 24 | *
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| 25 | * @param x The input tensor, of rank 4 or rank 3 of shape
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| 26 | * [batch, height, width, inChannels]. If rank 3, batch of 1 is assumed.
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| 27 | * @param dy The dy image, of rank 4 or rank 3, of shape
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| 28 | * [batch, height, width, outDepth]. If rank 3, batch of 1 is assumed.
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| 29 | * @param filterShape The shape of the filter, length 4,
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| 30 | * [filterHeight, filterWidth, inDepth, outDepth].
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| 31 | * @param strides The strides of the convolution: [strideHeight,
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| 32 | * strideWidth].
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| 33 | * @param pad A string from: 'same', 'valid'. The type of padding algorithm
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| 34 | * used in the forward prop of the op.
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| 35 | * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
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| 36 | * "NHWC". Specify the data format of the input and output data. With the
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| 37 | * default format "NHWC", the data is stored in the order of: [batch,
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| 38 | * height, width, channels].
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| 39 | * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is
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| 40 | * provided, it will default to truncate.
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| 41 | */
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| 42 | function conv2DBackpropFilter_(x, dy, filterShape, strides, pad, dataFormat = 'NHWC', dimRoundingMode) {
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| 43 | let x4D = x;
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| 44 | if (x.rank === 3) {
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| 45 | x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);
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| 46 | }
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| 47 | let dy4D = dy;
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| 48 | if (dy4D.rank === 3) {
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| 49 | dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);
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| 50 | }
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| 51 | util.assert(x4D.rank === 4, () => `Error in conv2dDerFilter: input must be rank 4, but got shape ` +
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| 52 | `${x4D.shape}.`);
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| 53 | util.assert(dy4D.rank === 4, () => `Error in conv2dDerFilter: dy must be rank 4, but got shape ` +
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| 54 | `${dy4D.shape}.`);
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| 55 | util.assert(filterShape.length === 4, () => `Error in conv2dDerFilter: filterShape must be length 4, but got ` +
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| 56 | `${filterShape}.`);
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| 57 | const inDepth = dataFormat === 'NHWC' ? x4D.shape[3] : x4D.shape[1];
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| 58 | const outDepth = dataFormat === 'NHWC' ? dy4D.shape[3] : dy4D.shape[1];
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| 59 | util.assert(inDepth === filterShape[2], () => `Error in conv2dDerFilter: depth of input ${inDepth}) must ` +
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| 60 | `match input depth in filter (${filterShape[2]}.`);
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| 61 | util.assert(outDepth === filterShape[3], () => `Error in conv2dDerFilter: depth of dy (${outDepth}) must ` +
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| 62 | `match output depth for filter (${filterShape[3]}).`);
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| 63 | if (dimRoundingMode != null) {
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| 64 | util.assert(util.isInt(pad), () => `Error in conv2dDerFilter: pad must be an integer when using, ` +
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| 65 | `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
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| 66 | }
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| 67 | const inputs = { x: x4D, dy: dy4D };
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| 68 | const attrs = { strides, pad, dataFormat, dimRoundingMode, filterShape };
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| 69 | // tslint:disable-next-line: no-unnecessary-type-assertion
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| 70 | return ENGINE.runKernel(Conv2DBackpropFilter, inputs, attrs);
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| 71 | }
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| 72 | export const conv2DBackpropFilter = op({ conv2DBackpropFilter_ });
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| 73 | //# sourceMappingURL=conv2d_backprop_filter.js.map |
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