@@ -509,52 +509,13 @@ function withSpaceToBatchBasePaddings(
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* - For more info, see this guide:
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* [https://www.tensorflow.org/api_guides/python/nn#Convolution](
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* https://www.tensorflow.org/api_guides/python/nn#Convolution)
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- * @param dimRoundingMode The rounding mode used when computing output
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- * dimensions if pad is a number. If none is provided, it will not round
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- * and error if the output is of fractional size.
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- * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
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- * "NDHWC". Specify the data format of the input and output data. With the
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- * default format "NDHWC", the data is stored in the order of: [batch,
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- * depth, height, width, channels]. Only "NDHWC" is currently supported.
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- */
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- /** @doc {heading: 'Operations', subheading: 'Convolution'} */
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- function avgPool3d_ (
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- x : Tensor5D | TensorLike , filterSize : [ number , number , number ] | number ,
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- strides : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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- dimRoundingMode ?: 'floor' | 'round' | 'ceil' ,
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- dataFormat : 'NDHWC' | 'NCDHW' = 'NDHWC' ) : Tensor5D {
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- return avgPool3dImpl_ (
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- x , filterSize , strides , 1 , pad , dimRoundingMode , dataFormat ) ;
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- }
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-
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- /**
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- * Computes the 3D average pooling.
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- *
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- * @param x The input tensor, of rank 5 of shape
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- * `[batch, depth, height, width, inChannels]`.
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- * @param filterSize The filter size:
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- * `[filterDepth, filterHeight, filterWidth]`.
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- * If `filterSize` is a single number,
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- * then `filterDepth == filterHeight == filterWidth`.
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- * @param strides The strides of the pooling:
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- * `[strideDepth, strideHeight, strideWidth]`.
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- * If `strides` is a single number,
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- * then `strideDepth == strideHeight == strideWidth`.
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* @param dilations The dilation rates:
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* `[dilationDepth, dilationHeight, dilationWidth]`
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* in which we sample input values across the depth, height and width
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* dimensions in dilated pooling.
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* Defaults to `[1, 1, 1]`. If `dilations` is a single number,
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* then `dilationDepth == dilationHeight == dilationWidth`.
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* If it is greater than 1, then all values of `strides` must be 1.
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- * @param pad The type of padding algorithm.
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- * - `same` and stride 1: output will be of same size as input,
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- * regardless of filter size.
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- * - `valid`: output will be smaller than input if filter is larger
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- * than 1*1x1.
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- * - For more info, see this guide:
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- * [https://www.tensorflow.org/api_guides/python/nn#Convolution](
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- * https://www.tensorflow.org/api_guides/python/nn#Convolution)
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* @param dimRoundingMode The rounding mode used when computing output
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* dimensions if pad is a number. If none is provided, it will not round
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* and error if the output is of fractional size.
@@ -563,10 +524,10 @@ function avgPool3d_(
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* default format "NDHWC", the data is stored in the order of: [batch,
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* depth, height, width, channels]. Only "NDHWC" is currently supported.
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*/
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- function avgPool3dImpl_ (
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+ /** @doc {heading: 'Operations', subheading: 'Convolution'} */
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+ function avgPool3d_ (
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x : Tensor5D | TensorLike , filterSize : [ number , number , number ] | number ,
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- strides : [ number , number , number ] | number ,
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- dilations : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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+ strides : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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dimRoundingMode ?: 'floor' | 'round' | 'ceil' ,
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dataFormat : 'NDHWC' | 'NCDHW' = 'NDHWC' ) : Tensor5D {
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const $x = convertToTensor ( x , 'x' , 'avgPool3d' , 'float32' ) ;
@@ -706,52 +667,13 @@ function avgPool3dBackprop(
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* - For more info, see this guide:
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* [https://www.tensorflow.org/api_guides/python/nn#Convolution](
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* https://www.tensorflow.org/api_guides/python/nn#Convolution)
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- * @param dimRoundingMode The rounding mode used when computing output
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- * dimensions if pad is a number. If none is provided, it will not round
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- * and error if the output is of fractional size.
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- * @param dataFormat An optional string from: "NDHWC", "NCDHW". Defaults to
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- * "NDHWC". Specify the data format of the input and output data. With the
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- * default format "NDHWC", the data is stored in the order of: [batch,
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- * depth, height, width, channels]. Only "NDHWC" is currently supported.
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- */
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- /** @doc {heading: 'Operations', subheading: 'Convolution'} */
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- function maxPool3d_ (
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- x : Tensor5D | TensorLike , filterSize : [ number , number , number ] | number ,
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- strides : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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- dimRoundingMode ?: 'floor' | 'round' | 'ceil' ,
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- dataFormat : 'NDHWC' | 'NCDHW' = 'NDHWC' ) : Tensor5D {
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- return maxPool3dImpl_ (
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- x , filterSize , strides , 1 , pad , dimRoundingMode , dataFormat ) ;
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- }
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-
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- /**
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- * Computes the 3D max pooling.
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- *
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- * @param x The input tensor, of rank 5 of shape
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- * `[batch, depth, height, width, inChannels]`.
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- * @param filterSize The filter size:
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- * `[filterDepth, filterHeight, filterWidth]`.
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- * If `filterSize` is a single number,
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- * then `filterDepth == filterHeight == filterWidth`.
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- * @param strides The strides of the pooling:
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- * `[strideDepth, strideHeight, strideWidth]`.
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- * If `strides` is a single number,
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- * then `strideDepth == strideHeight == strideWidth`.
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* @param dilations The dilation rates:
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* `[dilationDepth, dilationHeight, dilationWidth]`
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* in which we sample input values across the depth, height and width
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* dimensions in dilated pooling.
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* Defaults to `[1, 1, 1]`. If `dilations` is a single number,
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* then `dilationDepth == dilationHeight == dilationWidth`.
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* If it is greater than 1, then all values of `strides` must be 1.
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- * @param pad The type of padding algorithm.
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- * - `same` and stride 1: output will be of same size as input,
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- * regardless of filter size.
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- * - `valid`: output will be smaller than input if filter is larger
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- * than 1*1x1.
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- * - For more info, see this guide:
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- * [https://www.tensorflow.org/api_guides/python/nn#Convolution](
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- * https://www.tensorflow.org/api_guides/python/nn#Convolution)
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* @param dimRoundingMode The rounding mode used when computing output
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* dimensions if pad is a number. If none is provided, it will not round
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* and error if the output is of fractional size.
@@ -760,10 +682,11 @@ function maxPool3d_(
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* default format "NDHWC", the data is stored in the order of: [batch,
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* depth, height, width, channels]. Only "NDHWC" is currently supported.
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*/
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- function maxPool3dImpl_ (
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+ /** @doc {heading: 'Operations', subheading: 'Convolution'} */
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+ function maxPool3d_ (
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x : Tensor5D | TensorLike , filterSize : [ number , number , number ] | number ,
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- strides : [ number , number , number ] | number ,
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- dilations : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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+ strides : [ number , number , number ] | number , pad : 'valid' | 'same' | number ,
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+ dilations : [ number , number , number ] | number ,
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dimRoundingMode ?: 'floor' | 'round' | 'ceil' ,
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dataFormat : 'NDHWC' | 'NCDHW' = 'NDHWC' ) : Tensor5D {
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const $x = convertToTensor ( x , 'x' , 'maxPool3d' ) ;
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