mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-26 19:52:38 +00:00
### Description This PR is a preview of cherry-picks for ort-web to `rel-1.17.3` based on `rel-1.17.2`. <details> <summary>Changes of ort-web to cherry-pick</summary> The following commits are from main branch. `o` stands for pick, and `x` stands for skip. ``` o2e0a388c36[js/webgpu] Add HardSigmoid support (#19215) od226e40856[js/webgpu] set query type in onRunStart (#19202) o61610ff986[js/webgpu] Add FusedConv clip test case (#18900) oa33b5bd1fa[JS/WebGPU] Added Uniforms to SkipLayerNorm. (#18788) o591f90c0b9[js/webgpu] Fix issue of timestamp query (#19258) o7252c6e747[WebNN EP] Support WebNN async API with Asyncify (#19145) o5b06505073[js/webgpu] Fix Tanh explosion (#19201) o656ca66186[js/webgpu] Support uniforms for conv, conv transpose, conv grouped (#18753) oa3f0e2422b[js/webgpu] Support f16 uniform (#19098) o9e69606360fix f16 for attention, enable slice and flatten for more types (#19262) o624b4e2063[js/webgpu] Remove enableShapesUniforms (#19279) o90883a366a[js/webgpu] Add hardSigmoid activation for fusedConv (#19233) o85cef0af8c[js/webgpu] Support capture and replay for jsep (#18989) od73131cf0f[js/webgpu] Use DataType as uniform cpu type (#19281) odd1f6ccc45[js/webgpu] resolve codescan alert (#19343) o3a2ab1963a[js/webgpu] Refactor createTensorShapeVariables (#18883) oefc17e79de[js/webgpu] Fix the undefined push error (#19366) x50806a7dd5[js/web] support external data in npm test (#19377) occbe264a39[js/webgpu] Add LeakyRelu activation for fusedConv (#19369) o5ff27ef02a[js/webgpu] support customop FastGelu (#19392) x03be65e064[js/web] fix types exports in package.json (#19458) o06269a3952[js/webgpu] allow uint8 tensors for webgpu (#19545) odfeda9019c[JS/WebGPU] Add MatMulNBits (#19446) o1b48054e1b[js/webgpu] Create Split indices helpers by rank, not by shape (#19554) o3fe2c137ee[js] small fix to workaround formatter (#19400) x70567a4b3a[js/web] use ApiTensor insteadof onnxjs Tensor in TensorResultValidator (#19358) o6e04e36e3f[js/common] upgrade tsc in common from 4.9.5 to 5.2.2 (#19317) o58f4921686[js] changes to allow Float16Array if any polyfill is available (#19305) o57d6819212[js/web] Fix fused-conv is not included in npm test (#19581) oebd220b073Misspelling in README.md (#19433) o38c3432393Bump ip from 1.1.8 to 1.1.9 in /js/react_native (#19582) ofe82fccf1a[js/webgpu] Fix Conv2DTransposeMatMul f16 compilation failure (#19596) o76a2a487a1Bump ip from 1.1.8 to 1.1.9 in /js/react_native/e2e (#19583) o29b1106033[node] Switch to setImmediate to avoid starving the Node.js event loop (#19610) oae3d73c981[JS/WebGPU] Fix Split and Where to handle corner cases. (#19613) oaec2389ad0[js/webgpu] allows a ProgramInfo's RunData to use zero sized output (#19614) obb43a0f133[js/webgpu] minor fixes to make tinyllama work (#19564) o0edb035808[js/web] fix suite test list for zero sized tensor (#19638) o3cb81cdde2[js/common] move 'env.wasm.trace' to 'env.trace' (#19617) oe30618d055[js/webgpu] use Headless for webgpu test by default (#19702) of06164ef8b[js/web] transfer input buffer back to caller thread (#19677) xa788514027[js/web] dump debug logs for karma for diagnose purpose (#19785) o24b72d2613[JS/WebGPU] Preserve zero size input tensor dims. (#19737) o4538d31a8b[js/webgpu] expose a few properties in WebGPU API (#19857) o53de2d8cb0[js/webgpu] Enable GroupedConvVectorize path (#19791) oed250b88c3[JS/WebGPU] Optimize MatMulNBits (#19852) xe771a763c3[js/test] align web test runner flags with ort.env (#19790) o79e50aeef3[js/web] rewrite backend resolve to allow multiple EPs (#19735) oacb0df2280Fix #19931 broken Get Started link of "ONNX Runtime JavaScript API" page (#19932) ob29849a287[js/common] fix typedoc warnings (#19933) oafdab62f53Bump follow-redirects from 1.15.4 to 1.15.6 in /js/web (#19949) o28ad6c3955Bump follow-redirects from 1.15.4 to 1.15.6 in /js/node (#19951) o7e0d424934accumulate in fp32 for Reduce* (#19868) o4c6a6a37f7[js/webgpu] Fix NAN caused by un-initialized buffer in instance-norm (#19387) o01c7aaf6aa[js/webgpu] allow setting env.webgpu.adapter (#19940) oc45cff60cf[js/webgpu] fix maxpool / fp16 (#19981) ``` </details> <details> <summary>Cherry-pick commandlines</summary> ```sh git cherry-pick2e0a388c36git cherry-pickd226e40856git cherry-pick61610ff986git cherry-picka33b5bd1fagit cherry-pick591f90c0b9git cherry-pick7252c6e747git cherry-pick5b06505073git cherry-pick656ca66186git cherry-picka3f0e2422bgit cherry-pick9e69606360git cherry-pick624b4e2063git cherry-pick90883a366agit cherry-pick85cef0af8c#<<<<< Note: conflicts git cherry-pickd73131cf0fgit cherry-pickdd1f6ccc45git cherry-pick3a2ab1963agit cherry-pickefc17e79degit cherry-pickccbe264a39git cherry-pick5ff27ef02agit cherry-pick06269a3952git cherry-pickdfeda9019cgit cherry-pick1b48054e1bgit cherry-pick3fe2c137eegit cherry-pick6e04e36e3fgit cherry-pick58f4921686git cherry-pick57d6819212git cherry-pickebd220b073git cherry-pick38c3432393git cherry-pickfe82fccf1agit cherry-pick76a2a487a1git cherry-pick29b1106033git cherry-pickae3d73c981git cherry-pickaec2389ad0git cherry-pickbb43a0f133git cherry-pick0edb035808git cherry-pick3cb81cdde2git cherry-picke30618d055git cherry-pickf06164ef8bgit cherry-pick24b72d2613git cherry-pick4538d31a8bgit cherry-pick53de2d8cb0git cherry-picked250b88c3git cherry-pick79e50aeef3git cherry-pickacb0df2280git cherry-pickb29849a287git cherry-pickafdab62f53git cherry-pick28ad6c3955git cherry-pick7e0d424934git cherry-pick4c6a6a37f7git cherry-pick01c7aaf6aagit cherry-pickc45cff60cf``` </details> <details> <summary>Cherry-pick conflicts</summary> -85cef0af8c#18989 this change is for enabling graph capture feature for JSEP, and it is done after ROCM EP enabled graph capture feature. However, the ROCM EP graph capture feature is not cherry-picked in rel-1.17.2. </details> --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Jiajia Qin <jiajia.qin@intel.com> Co-authored-by: Xu Xing <xing.xu@intel.com> Co-authored-by: satyajandhyala <satya.k.jandhyala@gmail.com> Co-authored-by: Yang Gu <yang.gu@intel.com> Co-authored-by: Wanming Lin <wanming.lin@intel.com> Co-authored-by: Jiajie Hu <jiajie.hu@intel.com> Co-authored-by: Guenther Schmuelling <guschmue@microsoft.com> Co-authored-by: Matttttt <18152455+martholomew@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Segev Finer <segev208@gmail.com> Co-authored-by: Belem Zhang <belem.zhang@intel.com>
932 lines
34 KiB
TypeScript
932 lines
34 KiB
TypeScript
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import {DataType} from '../../../wasm-common';
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import {ShapeUtil} from '../../util';
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import {ProgramUniform} from '../types';
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/**
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* constant value for a workgroup size.
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*
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* We definitely can do further optimization in future, but for now we use 64.
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*
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* rule of thumb: Use [a workgroup size of] 64 unless you know what GPU you are targeting or that your workload
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* needs something different.
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*
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* from: https://surma.dev/things/webgpu/
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**/
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export const WORKGROUP_SIZE = 64;
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interface IndicesHelperTypes {
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/**
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* WGSL type of indices expression
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*/
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readonly indices: string;
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/**
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* WGSL type of a value
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*/
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readonly value: string;
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/**
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* WGSL type of storage type representing a value
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*
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* This is usually the same to `value`, but for some type (eg. bool), we need to use `u32` as storage type for
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* value type `vec4<bool>`
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*/
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readonly storage: string;
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/**
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* tensor type as represented in TensorView
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*/
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readonly tensor: number;
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}
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/**
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* A helper class for generating WGSL code for manipulating indices and data for a shader's input or output.
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*
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* This class is designed to offer a unified way to generate WGSL code for manipulating indices and data for a shader's
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* input or output.
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*
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* The following is a list of terminologies used in this class:
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* - `offset`: a uint32 value representing the offset of an element in the data buffer.
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* - `indices`: an abstraction of a multi-dimensional array's indices representing the data's index on each dimension.
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* - `value`: a value of a data element.
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*
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* Users are expected to create an instance of this class for each shader's input or output, and use the instance to
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* generate WGSL code for manipulating indices and data. The following 2 exported functions are for users to call to
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* create an instance of an indices helper:
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* - `inputVariable()`: create an indices helper instance for an input.
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* - `outputVariable()`: create an indices helper instance for an output.
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* - `internalVariable()`: create an indices helper instance for an internal variable.
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*
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* An indices helper instance contains helper functions for the following operations:
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* - access readonly basic information, including: `name`(the name of the input or output), `usage`(whether it's an
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* input, an output or an internal variable) and `shape`(the passed in shape).
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* - `type`: access readonly type information, including: `indices`(the type of indices), `value`(the type of value at
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* runtime), `storage`(the type of value at storage) and `tensor`(the tensor type as represented in TensorView).
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* - generate WGSL code for getting indices from offset. Use `offsetToIndices()` for WGSL code snippet to calculate
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* indices from offset, and use `indicesToOffset()` for WGSL code snippet to calculate offset from indices.
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* - to manipulate an instance of indices, use `setIndices()` and `getIndices()` to set and get the indices on an
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* indices variable.
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* - to manipulate data, use `set()`/`get()` to access data at the given indices from parameter list, use
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* `setByIndices()`/`getByIndices()` to access data at the given indices from an indices variable, and use
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* `setByOffset()`/`getByOffset()` to access data at the given offset.
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* - `impl`: get WGSL code of function implementation for the util functions mentioned above.
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*/
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export interface IndicesHelper {
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/**
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* get WGSL code of function implementation for the util functions.
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*
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*/
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readonly impl: () => string;
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/**
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* get type info
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*/
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readonly type: IndicesHelperTypes;
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/**
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* WGSL code of a expression for getting indices from offset.
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*
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* @param varOffset - a u32 expression representing the offset.
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*
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* @returns an `type.indices` expression
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*/
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readonly offsetToIndices: (varOffset: string) => string;
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/**
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* WGSL code of an `u32` expression for getting offset from indices.
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*
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* @param varIndices - a `type.indices` expression representing the indices.
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*
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* @returns an `u32` expression
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*/
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readonly indicesToOffset: (varIndices: string) => string;
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/**
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* WGSL code of an `u32` expression for getting original offset from broadcasted indices.
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*
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* @param varIndices - a `type.indices` expression representing the output indices.
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* @param output - output IndicesHelper.
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*
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* @returns an `u32` expression
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*/
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readonly broadcastedIndicesToOffset: (varIndices: string, output: IndicesHelper) => string;
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/**
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* WGSL code of generating an indices literal
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*
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* @param init - initial value.
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*/
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readonly indices: (...init: ReadonlyArray<number|string>) => string;
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/**
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* WGSL code of a statement for setting indices.
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*
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* @param varIndices - a variable name for the indices.
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* @param idx - the index of the indices to set. can be a number or a string (WGSL `u32` expression).
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* @param value - the value to set. can be a number or a string (WGSL `u32` expression).
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*
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* @returns a WGSL statement
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*/
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readonly indicesSet: (varIndices: string, idx: number|string, value: number|string) => void;
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/**
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* WGSL code of an `u32` expression for getting indices.
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*
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* @param varIndices - a variable name for the indices.
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* @param idx - the index of the indices to get. can be a number or a string (WGSL `u32` expression).
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*
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* @returns an `u32` expression
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*/
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readonly indicesGet: (varIndices: string, idx: number|string) => string;
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/**
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* WGSL code for a statement for setting data at the given indices.
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*
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* @param indicesAndValue - an array of numbers or strings (WGSL `u32` expression) representing the indices, followed
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* by the value to set. This array should have exactly `shape.length + 1` elements.
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*/
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readonly set: (...indicesAndValue: ReadonlyArray<number|string>) => string;
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/**
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* WGSL code for a statement for setting data at the given indices variable.
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*
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* @param varIndices - a variable name for the indices.
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* @param value - the value to set. should be a WGSL expression.
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*/
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readonly setByIndices: (varIndices: string, value: string) => string;
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/**
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* WGSL code for a statement for setting data at the given offset.
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*
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* @param offset - a number or a string (WGSL `u32` expression) representing the offset.
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* @param value - the value to set. should be a WGSL expression.
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*/
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readonly setByOffset: (offset: number|string, value: string) => string;
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/**
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* WGSL code for an expression for getting data at the given indices.
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*
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* @param indices - an array of numbers or strings (WGSL `u32` expression) representing the indices.
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*/
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readonly get: (...indices: ReadonlyArray<number|string>) => string;
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/**
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* WGSL code for an expression for getting data at the given indices variable.
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*
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* @param varIndices - a variable name for the indices.
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*/
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readonly getByIndices: (varIndices: string) => string;
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/**
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* WGSL code for an expression for getting data at the given offset.
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*
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* @param offset - a number or a string (WGSL `u32` expression) representing the offset.
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*/
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readonly getByOffset: (offset: number|string) => string;
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/**
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* name of the data variable
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*/
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readonly name: string;
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/**
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* whether the helper is for an input, an output or an internal variable.
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*/
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readonly usage: 'input'|'output'|'internal';
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/**
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* the rank of the input or output.
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*/
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readonly rank: number;
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/**
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* a string representing the variable name for the shape of the input or output.
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*/
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readonly shape: string;
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/**
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* a string representing the variable name for the strides of the input or output.
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*/
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readonly strides: string;
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}
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const getWgslMappedType = (type: number, components: 1|2|3|4): string|[string, string] => {
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if (components === 3) {
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throw new Error('vec3 has same alignment as vec4, use vec4 instead');
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}
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// return type is [ storage type, runtime type ] or a single string for both
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switch (type) {
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case DataType.float16:
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return components > 1 ? `vec${components}<f16>` : 'f16';
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case DataType.float:
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return components > 1 ? `vec${components}<f32>` : 'f32';
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case DataType.int32:
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return components > 1 ? `vec${components}<i32>` : 'i32';
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case DataType.uint32:
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return components > 1 ? `vec${components}<u32>` : 'u32';
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case DataType.int64:
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if (components > 1) {
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throw new Error('currently not supported vecX of uint64 yet');
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}
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return ['vec2<u32>', 'i32'];
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case DataType.uint64:
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if (components > 1) {
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throw new Error('currently not supported vecX of uint64 yet');
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}
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return ['vec2<u32>', 'u32'];
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case DataType.bool:
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if (components !== 4) {
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throw new Error('bool must be vec4');
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}
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return ['u32', 'vec4<bool>'];
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default:
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throw new Error(`Unknown data type: ${type}`);
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}
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};
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export const tensorTypeToWsglStorageType = (type: DataType, components: 1|2|3|4 = 1) => {
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const mappedType = getWgslMappedType(type, components);
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return typeof mappedType === 'string' ? mappedType : mappedType[0];
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};
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export const tensorTypeToWsglValueType = (type: DataType, components: 1|2|3|4 = 1) => {
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const mappedType = getWgslMappedType(type, components);
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return typeof mappedType === 'string' ? mappedType : mappedType[1];
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};
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export const createTensorShapeVariables = (...dims: ReadonlyArray<readonly number[]>): ProgramUniform[] => {
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const programUniforms: ProgramUniform[] = [];
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dims.forEach(dim => {
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if (dim.length !== 0) {
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programUniforms.push(
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{type: DataType.uint32, data: dim}, {type: DataType.uint32, data: ShapeUtil.computeStrides(dim)});
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}
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});
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return programUniforms;
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};
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/**
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* A helper function to get maximum vector size for specified data length
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* @param size
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*/
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export const getMaxComponents = (size: number) => {
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// we cannot use vec3 type since it has alignment of 16 bytes
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if (size % 4 === 0) {
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return 4;
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} else if (size % 2 === 0) {
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return 2;
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}
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return 1;
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};
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/**
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* A helper function that initializes variable as a scalar or vector. e.g. f32(0) or vec4f(0,0,0,0)
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* @param dataType
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* @param components
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* @param value
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*/
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export const fillVector = (dataType = 'f32', components?: number, value = '0') => {
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if (!components || components === 1) {
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return `${dataType}(${value})`;
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}
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return `vec${components}<${dataType}>(${value})`;
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};
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/**
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* A helper function that casts value or vector to f32
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* @param dataType
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* @param components
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* @param value
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*/
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export const castToF32 = (dataType: string, components: number, value: string) => {
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if (dataType === 'f32') {
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return value;
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}
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if (components === 1) {
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return `f32(${value})`;
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}
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return `vec${components}f(${value})`;
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};
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/**
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* A helper function that returns scalar or sums all components of a vector
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* @param name
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* @param components
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*/
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export const sumVector = (name: string, components: number) => {
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if (components === 4) {
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return `(${name}.x + ${name}.y + ${name}.z + ${name}.w)`;
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} else if (components === 2) {
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return `(${name}.x + ${name}.y)`;
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} else if (components === 3) {
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return `(${name}.x + ${name}.y + ${name}.z)`;
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}
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return name;
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};
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/**
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* A helper function that returns variable element at index.
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* @param name - the name of variable.
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* @param index - the index of variable element.
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* @param length - the length of variable.
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* @param type - the type of variable, optional.
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*/
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export const getElementAt =
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(name: string, index: number|string, length: number, type?: UniformDataElementType): string => {
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if (name.startsWith('uniforms.') && length > 4) {
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if (typeof (index) === 'string') {
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if (type === 'f16') {
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return `${name}[(${index}) / 8][(${index}) % 8 / 4][(${index}) % 8 % 4]`;
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} else {
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return `${name}[(${index}) / 4][(${index}) % 4]`;
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}
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} else {
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if (type === 'f16') {
|
|
return `${name}[${Math.floor(index / 8)}][${Math.floor(index % 8 / 4)}][${index % 8 % 4}]`;
|
|
} else {
|
|
return `${name}[${Math.floor(index / 4)}][${index % 4}]`;
|
|
}
|
|
}
|
|
} else {
|
|
return length > 1 ? `${name}[${index}]` : name;
|
|
}
|
|
};
|
|
|
|
/**
|
|
* A helper function to get a IndicesHelper for a given input or output.
|
|
*
|
|
* @param name - the name of the input or output.
|
|
* @param tensorType - the tensor type of the input or output.
|
|
* @param shapeOrRank - the tensor shape or the rank of the input or output.
|
|
* @param usage - the usage of the indices helper.
|
|
* @param components - indicates the number of components of each element. 1 for scalar, 2 for vec2, 3 for vec3, 4 for
|
|
* vec4.
|
|
*/
|
|
const createIndicesHelper =
|
|
(name: string, tensorType: number, shapeOrRank: number|readonly number[], usage: IndicesHelper['usage'],
|
|
components: 1|2|3|4): IndicesHelper => {
|
|
const useUniform = typeof shapeOrRank === 'number';
|
|
const rank = useUniform ? shapeOrRank : shapeOrRank.length;
|
|
const rankIdentity = [...new Array(rank).keys()];
|
|
const indicesType = rank < 2 ? 'u32' : rank <= 4 ? `vec${rank}<u32>` : `array<u32, ${rank}>`;
|
|
const mappedType = getWgslMappedType(tensorType, components);
|
|
const valueType = typeof mappedType === 'string' ? mappedType : mappedType[1];
|
|
const storageType = typeof mappedType === 'string' ? mappedType : mappedType[0];
|
|
const type = {indices: indicesType, value: valueType, storage: storageType, tensor: tensorType};
|
|
|
|
const normalizeDim = (dim: number|string): string => typeof dim === 'string' ? dim : `${dim}u`;
|
|
|
|
const implementationUsed = {
|
|
offsetToIndices: false,
|
|
indicesToOffset: false,
|
|
broadcastedIndicesToOffset: false,
|
|
set: false,
|
|
setByIndices: false,
|
|
get: false,
|
|
getByIndices: false,
|
|
};
|
|
|
|
const uniformPrefix = useUniform ? 'uniforms.' : '';
|
|
const shape = `${uniformPrefix}${name}_shape`;
|
|
const strides = `${uniformPrefix}${name}_strides`;
|
|
|
|
let o2iSnippet = '';
|
|
for (let i = 0; i < rank - 1; i++) {
|
|
o2iSnippet += `
|
|
let dim${i} = current / ${getElementAt(strides, i, rank)};
|
|
let rest${i} = current % ${getElementAt(strides, i, rank)};
|
|
indices[${i}] = dim${i};
|
|
current = rest${i};
|
|
`;
|
|
}
|
|
o2iSnippet += `indices[${rank - 1}] = current;`;
|
|
|
|
const offsetToIndicesImplementation = rank < 2 ? '' : `
|
|
fn o2i_${name}(offset: u32) -> ${type.indices} {
|
|
var indices: ${type.indices};
|
|
var current = offset;
|
|
${o2iSnippet}
|
|
return indices;
|
|
}`;
|
|
|
|
const offsetToIndices = (varOffset: string) => {
|
|
implementationUsed.offsetToIndices = true;
|
|
return rank < 2 ? varOffset : `o2i_${name}(${varOffset})`;
|
|
};
|
|
|
|
const offsets: string[] = [];
|
|
if (rank >= 2) {
|
|
for (let i = rank - 1; i >= 0; i--) {
|
|
offsets.push(`${getElementAt(strides, i, rank)} * (indices[${i}])`);
|
|
}
|
|
}
|
|
|
|
const indicesToOffsetImplementation = rank < 2 ? '' : `
|
|
fn i2o_${name}(indices: ${type.indices}) -> u32 {
|
|
return ${offsets.join('+')};
|
|
}`;
|
|
|
|
const indicesToOffset = (varIndices: string) => {
|
|
implementationUsed.indicesToOffset = true;
|
|
return rank < 2 ? varIndices : `i2o_${name}(${varIndices})`;
|
|
};
|
|
|
|
const indices = (...init: ReadonlyArray<number|string>) =>
|
|
rank === 0 ? '0u' : `${type.indices}(${init.map(normalizeDim).join(',')})`;
|
|
|
|
const indicesGet = (varIndices: string, idx: number|string) => {
|
|
if (rank < 2) {
|
|
return `${varIndices}`;
|
|
} else {
|
|
return `${getElementAt(varIndices, idx, rank)}`;
|
|
}
|
|
};
|
|
|
|
const indicesSet = (varIndices: string, idx: number|string, value: string) => {
|
|
if (rank < 2) {
|
|
return `${varIndices}=${value};`;
|
|
} else {
|
|
return `${getElementAt(varIndices, idx, rank)}=${value};`;
|
|
}
|
|
};
|
|
|
|
const broadcastedIndicesToOffsetImplementation: {[key: string]: string} = {};
|
|
const broadcastedIndicesToOffset = (varIndices: string, output: IndicesHelper) => {
|
|
implementationUsed.broadcastedIndicesToOffset = true;
|
|
const implKey = `${output.name}broadcastedIndicesTo${name}Offset`;
|
|
if (implKey in broadcastedIndicesToOffsetImplementation) {
|
|
return `${implKey}(${varIndices})`;
|
|
}
|
|
const offsets = [];
|
|
for (let i = rank - 1; i >= 0; i--) {
|
|
const idx = output.indicesGet('outputIndices', i + output.rank - rank);
|
|
offsets.push(`${indicesGet(strides, i)} * (${idx} % ${indicesGet(shape, i)})`);
|
|
}
|
|
broadcastedIndicesToOffsetImplementation[implKey] =
|
|
`fn ${implKey}(outputIndices: ${output.type.indices}) -> u32 {
|
|
return ${offsets.length > 0 ? offsets.join('+') : '0u'};
|
|
}`;
|
|
|
|
return `${implKey}(${varIndices})`;
|
|
};
|
|
|
|
const setByOffset = (offset: number|string, value: string) => (() => {
|
|
if (type.storage === type.value) {
|
|
return `${name}[${offset}]=${value};`;
|
|
} else if (type.storage === 'vec2<u32>' && type.value === 'i32') {
|
|
// int64, components === 1
|
|
return `${name}[${offset}]=vec2<u32>(u32(${value}), select(0u, 0xFFFFFFFFu, ${value} < 0));`;
|
|
} else if (type.storage === 'vec2<u32>' && type.value === 'u32') {
|
|
// uint64, components === 1
|
|
return `${name}[${offset}]=vec2<u32>(u32(${value}), 0u);`;
|
|
} else if (type.storage === 'u32' && type.value === 'vec4<bool>') {
|
|
// bool, components === 4
|
|
return `${name}[${offset}]=dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(${value}));`;
|
|
} else {
|
|
throw new Error(`not supported combination of storage type ${type.storage} and value type ${type.value} yet`);
|
|
}
|
|
})();
|
|
|
|
const getByOffset = (offset: number|string) => (() => {
|
|
if (type.storage === type.value) {
|
|
return `${name}[${offset}]`;
|
|
} else if (type.storage === 'vec2<u32>' && type.value === 'i32') {
|
|
// int64, components === 1
|
|
return `i32(${name}[${offset}].x)`;
|
|
} else if (type.storage === 'vec2<u32>' && type.value === 'u32') {
|
|
// uint64, components === 1
|
|
return `u32(${name}[${offset}].x)`;
|
|
} else if (type.storage === 'u32' && type.value === 'vec4<bool>') {
|
|
// bool, components === 4
|
|
return `vec4<bool>(bool(${name}[${offset}] & 0xFFu), bool(${name}[${offset}] & 0xFF00u), bool(${name}[${
|
|
offset}] & 0xFF0000u), bool(${name}[${offset}] & 0xFF000000u))`;
|
|
} else {
|
|
throw new Error(`not supported combination of storage type ${type.storage} and value type ${type.value} yet`);
|
|
}
|
|
})();
|
|
|
|
const getByIndicesImplementation = rank < 2 ? '' : `
|
|
fn get_${name}ByIndices(indices: ${type.indices}) -> ${valueType} {
|
|
return ${getByOffset(`i2o_${name}(indices)`)};
|
|
}`;
|
|
|
|
const getImplementation = rank < 2 ? '' : (() => {
|
|
const functionParams = rankIdentity.map(i => `d${i}: u32`).join(', ');
|
|
const dimsParams = rankIdentity.map(i => `d${i}`).join(', ');
|
|
return `
|
|
fn get_${name}(${functionParams}) -> ${valueType} {
|
|
return get_${name}ByIndices(${indices(dimsParams)});
|
|
}`;
|
|
})();
|
|
|
|
const get = (...indices: ReadonlyArray<number|string>) => {
|
|
if (indices.length !== rank) {
|
|
throw new Error(`indices length must be ${rank}`);
|
|
}
|
|
|
|
const normalizedIndices = indices.map(normalizeDim).join(',');
|
|
|
|
if (rank === 0) {
|
|
return getByOffset('0u');
|
|
} else if (rank === 1) {
|
|
return getByOffset(normalizedIndices[0]);
|
|
} else {
|
|
implementationUsed.get = true;
|
|
implementationUsed.getByIndices = true;
|
|
implementationUsed.indicesToOffset = true;
|
|
return `get_${name}(${normalizedIndices})`;
|
|
}
|
|
};
|
|
|
|
const getByIndices = (varIndices: string) => {
|
|
if (rank < 2) {
|
|
return getByOffset(varIndices);
|
|
} else {
|
|
implementationUsed.getByIndices = true;
|
|
implementationUsed.indicesToOffset = true;
|
|
return `get_${name}ByIndices(${varIndices})`;
|
|
}
|
|
};
|
|
|
|
const setByIndicesImplementation = rank < 2 ? '' : `
|
|
fn set_${name}ByIndices(indices: ${type.indices}, value: ${valueType}) {
|
|
${setByOffset(`i2o_${name}(indices)`, 'value')}
|
|
}`;
|
|
|
|
const setImplementation = rank < 2 ? '' : (() => {
|
|
const functionParams = rankIdentity.map(i => `d${i}: u32`).join(', ');
|
|
const dimsParams = rankIdentity.map(i => `d${i}`).join(', ');
|
|
return `
|
|
fn set_${name}(${functionParams}, value: ${valueType}) {
|
|
set_${name}ByIndices(${indices(dimsParams)}, value);
|
|
}`;
|
|
})();
|
|
|
|
const set = (...indicesAndValue: ReadonlyArray<number|string>) => {
|
|
if (indicesAndValue.length !== rank + 1) {
|
|
throw new Error(`indices length must be ${rank}`);
|
|
}
|
|
const value = indicesAndValue[rank];
|
|
if (typeof value !== 'string') {
|
|
throw new Error('value must be string');
|
|
}
|
|
|
|
const normalizedIndices = indicesAndValue.slice(0, rank).map(normalizeDim).join(',');
|
|
|
|
if (rank === 0) {
|
|
return setByOffset('0u', value);
|
|
} else if (rank === 1) {
|
|
return setByOffset(normalizedIndices[0], value);
|
|
} else {
|
|
implementationUsed.set = true;
|
|
implementationUsed.setByIndices = true;
|
|
implementationUsed.indicesToOffset = true;
|
|
return `set_${name}(${normalizedIndices}, ${value})`;
|
|
}
|
|
};
|
|
|
|
const setByIndices = (varIndices: string, value: string) => {
|
|
if (rank < 2) {
|
|
return setByOffset(varIndices, value);
|
|
} else {
|
|
implementationUsed.setByIndices = true;
|
|
implementationUsed.indicesToOffset = true;
|
|
return `set_${name}ByIndices(${varIndices}, ${value});`;
|
|
}
|
|
};
|
|
|
|
const impl = () => {
|
|
const impls = [];
|
|
let needShapeStrides = false;
|
|
if (implementationUsed.offsetToIndices) {
|
|
impls.push(offsetToIndicesImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.indicesToOffset) {
|
|
impls.push(indicesToOffsetImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.broadcastedIndicesToOffset) {
|
|
Object.values(broadcastedIndicesToOffsetImplementation).forEach(impl => impls.push(impl));
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.set) {
|
|
impls.push(setImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.setByIndices) {
|
|
impls.push(setByIndicesImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.get) {
|
|
impls.push(getImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (implementationUsed.getByIndices) {
|
|
impls.push(getByIndicesImplementation);
|
|
needShapeStrides = true;
|
|
}
|
|
if (!useUniform && needShapeStrides) {
|
|
impls.unshift(
|
|
`const ${shape} = ${type.indices}(${shapeOrRank.join(',')});`,
|
|
`const ${strides} = ${type.indices}(${ShapeUtil.computeStrides(shapeOrRank).join(',')});`);
|
|
}
|
|
return impls.join('\n');
|
|
};
|
|
|
|
return {
|
|
impl,
|
|
type,
|
|
offsetToIndices,
|
|
indicesToOffset,
|
|
broadcastedIndicesToOffset,
|
|
indices,
|
|
indicesGet,
|
|
indicesSet,
|
|
set,
|
|
setByOffset,
|
|
setByIndices,
|
|
get,
|
|
getByOffset,
|
|
getByIndices,
|
|
// isVec4,
|
|
usage,
|
|
name,
|
|
strides,
|
|
shape,
|
|
rank
|
|
};
|
|
};
|
|
|
|
/**
|
|
* Create a IndicesHelper for an input.
|
|
*
|
|
* @param name - the name of the input.
|
|
* @param type - the tensor type of the input.
|
|
* @param shapeOrRank - the tensor shape or the rank of the input.
|
|
* @param components - the number of components of the input. available values are 1, 2, 3, 4. default is 1.
|
|
* @returns an IndicesHelper for the input.
|
|
*/
|
|
export const inputVariable =
|
|
(name: string, type: number, shapeOrRank: number|readonly number[], components: 1|2|3|4 = 1): IndicesHelper =>
|
|
createIndicesHelper(name, type, shapeOrRank, 'input', components);
|
|
|
|
/**
|
|
* Create a IndicesHelper for an output.
|
|
*
|
|
* @param name - the name of the output.
|
|
* @param type - the tensor type of the output.
|
|
* @param shapeOrRank - the tensor shape or the rank of the output.
|
|
* @param components - the number of components of the output. available values are 1, 2, 3, 4. default is 1.
|
|
* @returns an IndicesHelper for the output.
|
|
*/
|
|
export const outputVariable =
|
|
(name: string, type: number, shapeOrRank: number|readonly number[], components: 1|2|3|4 = 1): IndicesHelper =>
|
|
createIndicesHelper(name, type, shapeOrRank, 'output', components);
|
|
|
|
/**
|
|
* Create a IndicesHelper for an internal variable.
|
|
*
|
|
* @param name - the name of the variable.
|
|
* @param type - the tensor type of the variable.
|
|
* @param shapeOrRank - the tensor shape or the rank of the variable.
|
|
* @param components - the number of components of the variable. available values are 1, 2, 3, 4. default is 1.
|
|
* @returns an IndicesHelper for the variable.
|
|
*/
|
|
export const internalVariable =
|
|
(name: string, type: number, shapeOrRank: number|readonly number[], components: 1|2|3|4 = 1): IndicesHelper =>
|
|
createIndicesHelper(name, type, shapeOrRank, 'internal', components);
|
|
|
|
export type UniformDataElementType = 'u32'|'f16'|'f32'|'i32';
|
|
export type UniformsArrayType = Array<{name: string; type: UniformDataElementType; length?: number}>;
|
|
|
|
/**
|
|
* A ShaderHelper is a helper class for generating WGSL code.
|
|
*/
|
|
export interface ShaderHelper {
|
|
/**
|
|
* A helper function to generate the start of main function in WGSL source code.
|
|
*
|
|
* @example
|
|
* const getShaderSource = (shaderHelper: ShaderHelper) => `
|
|
* ...
|
|
*
|
|
* ${shaderHelper.mainStart()}
|
|
* // your code here inside main() function
|
|
* ...
|
|
* }
|
|
* `;
|
|
*
|
|
* @param workgroupSize - an optional workgroup size. default is WORKGROUP_SIZE.
|
|
*/
|
|
mainStart(workgroupSize?: number|[number, number, number]): string;
|
|
|
|
/**
|
|
* A helper function to generate the code snippet for guarding against out-of-bounds size.
|
|
*
|
|
* @example
|
|
* const getShaderSource = (shaderHelper: ShaderHelper) => `
|
|
* ...
|
|
*
|
|
* ${shaderHelper.mainStart()}
|
|
* ${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)}
|
|
*
|
|
* // your code here inside main() function
|
|
* ...
|
|
* }
|
|
* `;
|
|
*
|
|
* @param size - the size of the data to guard against. can be a number or a string (WGSL `u32` expression).
|
|
*/
|
|
guardAgainstOutOfBoundsWorkgroupSizes(size: unknown): string;
|
|
|
|
/**
|
|
* A helper function to generate the code snippet for declaring multiple inputs or outputs.
|
|
*
|
|
* @param variables - an array of IndicesHelper for the variables.
|
|
*/
|
|
declareVariables(...variables: IndicesHelper[]): string;
|
|
|
|
/**
|
|
* A helper function to register one uniform. Can be called multiple times to register multiple uniforms.
|
|
*
|
|
* @param name - the name of the uniform.
|
|
* @param type - the type of the uniform.
|
|
* @param length - the length of the uniform, default to 1 when it is not provided.
|
|
*/
|
|
registerUniform(name: string, type: string, length?: number): ShaderHelper;
|
|
|
|
/**
|
|
* A helper function to register multiple uniforms. Can be called multiple times to register multiple uniforms.
|
|
*
|
|
* @param uniforms - an array of uniforms. Each element of the array is an object with 2 properties: `name` and
|
|
* `type`.
|
|
*/
|
|
registerUniforms(uniforms: UniformsArrayType): ShaderHelper;
|
|
|
|
/**
|
|
* A helper function to register multiple internal variables. Can be called multiple times to register multiple
|
|
* internal variables.
|
|
*
|
|
* @param variables - an array of IndicesHelper for the variables.
|
|
*/
|
|
registerInternalVariables(...variables: IndicesHelper[]): ShaderHelper;
|
|
}
|
|
|
|
class ShaderHelperImpl implements ShaderHelper {
|
|
constructor(private normalizedDispatchGroup: [number, number, number]) {}
|
|
|
|
guardAgainstOutOfBoundsWorkgroupSizes(size: number|string): string {
|
|
// Guard against out-of-bounds work group sizes
|
|
const sizeInCode = typeof size === 'number' ? `${size}u` : size;
|
|
return `if (global_idx >= ${sizeInCode}) { return; }`;
|
|
}
|
|
|
|
mainStart(workgroupSize: number|[number, number, number] = WORKGROUP_SIZE) {
|
|
const workgroupSizeX = typeof workgroupSize === 'number' ? workgroupSize : workgroupSize[0];
|
|
const workgroupSizeY = typeof workgroupSize === 'number' ? 1 : workgroupSize[1];
|
|
const workgroupSizeZ = typeof workgroupSize === 'number' ? 1 : workgroupSize[2];
|
|
|
|
const is1DimensionDispatch = this.normalizedDispatchGroup[1] === 1 && this.normalizedDispatchGroup[2] === 1;
|
|
const paramList = is1DimensionDispatch ? `@builtin(global_invocation_id) global_id : vec3<u32>,
|
|
@builtin(workgroup_id) workgroup_id : vec3<u32>,
|
|
@builtin(local_invocation_id) local_id : vec3<u32>` :
|
|
`@builtin(local_invocation_id) local_id : vec3<u32>,
|
|
@builtin(local_invocation_index) local_idx : u32,
|
|
@builtin(workgroup_id) workgroup_id : vec3<u32>,
|
|
@builtin(num_workgroups) num_workgroups : vec3<u32>`;
|
|
const globalIdxDefinition = is1DimensionDispatch ?
|
|
'let global_idx = global_id.x; let local_idx = local_id.x;' :
|
|
`let global_idx = (workgroup_id.z * num_workgroups[0] * num_workgroups[1] +
|
|
workgroup_id.y * num_workgroups[0] + workgroup_id.x) * ${
|
|
workgroupSizeX * workgroupSizeY * workgroupSizeZ}u + local_idx;`;
|
|
|
|
return `@compute @workgroup_size(${workgroupSizeX}, ${workgroupSizeY}, ${workgroupSizeZ})
|
|
fn main(${paramList}) {
|
|
${globalIdxDefinition}
|
|
`;
|
|
}
|
|
|
|
private appendVariableUniforms(variable: IndicesHelper): void {
|
|
if (variable.rank !== 0) {
|
|
if (variable.shape.startsWith('uniforms.')) {
|
|
this.uniforms.push({name: variable.shape.replace('uniforms.', ''), type: 'u32', length: variable.rank});
|
|
}
|
|
if (variable.strides.startsWith('uniforms.')) {
|
|
this.uniforms.push({name: variable.strides.replace('uniforms.', ''), type: 'u32', length: variable.rank});
|
|
}
|
|
}
|
|
}
|
|
|
|
private declareVariable(variable: IndicesHelper, bindingIndex: number): string {
|
|
if (variable.usage === 'internal') {
|
|
throw new Error('cannot use internal variable with declareVariable(). use registerInternalVariables() instead.');
|
|
}
|
|
this.variables.push(variable);
|
|
this.appendVariableUniforms(variable);
|
|
|
|
const access = variable.usage === 'input' ? 'read' : 'read_write';
|
|
const storageType = variable.type.storage;
|
|
return `@group(0) @binding(${bindingIndex}) var<storage, ${access}> ${variable.name}: array<${storageType}>;`;
|
|
}
|
|
|
|
declareVariables(...variables: IndicesHelper[]): string {
|
|
return variables.map(v => this.declareVariable(v, this.variableIndex++)).join('\n');
|
|
}
|
|
|
|
private registerInternalVariable(variable: IndicesHelper): void {
|
|
if (variable.usage !== 'internal') {
|
|
throw new Error(
|
|
'cannot use input or output variable with registerInternalVariable(). use declareVariables() instead.');
|
|
}
|
|
|
|
this.internalVariables.push(variable);
|
|
this.appendVariableUniforms(variable);
|
|
}
|
|
|
|
registerInternalVariables(...variables: IndicesHelper[]): ShaderHelper {
|
|
variables.forEach(v => this.registerInternalVariable(v));
|
|
return this;
|
|
}
|
|
|
|
registerUniform(name: string, type: UniformDataElementType, length = 1): ShaderHelper {
|
|
this.uniforms.push({name, type, length});
|
|
return this;
|
|
}
|
|
|
|
registerUniforms(additionalUniforms: UniformsArrayType): ShaderHelper {
|
|
this.uniforms = this.uniforms.concat(additionalUniforms);
|
|
return this;
|
|
}
|
|
|
|
private internalVariables: IndicesHelper[] = [];
|
|
private variables: IndicesHelper[] = [];
|
|
private uniforms: UniformsArrayType = [];
|
|
private uniformDeclaration(): string {
|
|
if (this.uniforms.length === 0) {
|
|
return '';
|
|
}
|
|
|
|
const uniformSnippets: string[] = [];
|
|
for (const {name, type, length} of this.uniforms) {
|
|
if (length && length > 4) {
|
|
if (type === 'f16') {
|
|
uniformSnippets.push(`@align(16) ${name}:array<mat2x4<${type}>, ${Math.ceil(length / 8)}>`);
|
|
} else {
|
|
uniformSnippets.push(`${name}:array<vec4<${type}>, ${Math.ceil(length / 4)}>`);
|
|
}
|
|
} else {
|
|
const typeTemp = length == null || length === 1 ? type : `vec${length}<${type}>`;
|
|
uniformSnippets.push(`${name}:${typeTemp}`);
|
|
}
|
|
}
|
|
|
|
return `
|
|
struct Uniforms { ${uniformSnippets.join(', ')} };
|
|
@group(0) @binding(${this.variableIndex}) var<uniform> uniforms: Uniforms;`;
|
|
}
|
|
private variableIndex = 0;
|
|
|
|
/**
|
|
* Get additional implementation that needs to be added to the shader source.
|
|
*/
|
|
get additionalImplementations(): string {
|
|
return this.uniformDeclaration() + this.variables.map(i => i.impl()).join('\n') +
|
|
this.internalVariables.map(i => i.impl()).join('\n');
|
|
}
|
|
}
|
|
|
|
export const createShaderHelper = (dispatchGroup: [number, number, number]) => new ShaderHelperImpl(dispatchGroup);
|
|
|
|
/**
|
|
* This function comes from https://github.com/tensorflow/tfjs/blob/master/tfjs-core/src/ops/broadcast_util.ts#L18-L40
|
|
* Returns the dimensions in the input shape that are broadcasted to
|
|
* produce the provided output shape.
|
|
*
|
|
* The returned dimensions are 0-indexed and sorted. An example:
|
|
* inShape = [4, 1, 3]
|
|
* outShape = [5, 4, 3, 3]
|
|
* result = [1]. Dimension 1 (2nd dimension of input) gets broadcasted 1 => 3.
|
|
*/
|
|
export const getBroadcastDims = (inShape: readonly number[], outShape: readonly number[]): number[] => {
|
|
const inRank = inShape.length;
|
|
const dims: number[] = [];
|
|
for (let i = 0; i < inRank; i++) {
|
|
const dim = inRank - 1 - i;
|
|
const a = inShape[dim] || 1;
|
|
const b = outShape[outShape.length - 1 - i] || 1;
|
|
if (b > 1 && a === 1) {
|
|
dims.unshift(dim);
|
|
}
|
|
}
|
|
return dims;
|
|
};
|