Linting issue resolved: unused import statement culled #39
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Co-authored-by: David Kim (@koyykdy) <[email protected]> Brian Zheng (@Brianzheng123) <[email protected]>
Rescaling Preprocessing Layer
Co-authored-by: Adam Lang (@AdamLang96) <[email protected]> Co-authored-by: (@Brianzheng123) <[email protected]>
Linting and PR issues resolved
Linting updates checked over, approved
Updating branch with master repo updates
…sociated unit tests. Comments and refactoring for image scaling layer
Initial implementation of resizing layer and unit tests, additional refactoring for rescaling layer
refactoring in computeOutputShape for image resizing layer
Update deploy-benchmark-prod.yml (tensorflow#6814)
Co-authored-by: Adam Lang <@AdamLang96> ([email protected])
Pulling down updates to tfjs master repository
Master branch pulldown for main repository updates
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Sep 29, 2022
* Customize setTimeout (tensorflow#6694) If the setTimeout nesting level is greater than 5 and timeout is less than 4ms, timeout will be clamped to 4ms, which hurts the perf. A custom setTimeout is provided to mitigate the perf impact. BUG: tensorflow#6687 Co-authored-by: Na Li <[email protected]> * Upgrade windows BrowserStack chrome to 104 (tensorflow#6866) * webgpu: Disable importExternalTexture (tensorflow#6868) WebGPU Working Group recently found some problem with importExtenalTexture in spec, so we have to disable it temporarily. * Refactored Resizing Layer Unit Tests (#38) * Rescaling Preprocessing Layer Co-authored-by: David Kim (@koyykdy) <[email protected]> Brian Zheng (@Brianzheng123) <[email protected]> * PR issues resolved * linting and PR issues resolved Co-authored-by: Adam Lang (@AdamLang96) <[email protected]> Co-authored-by: (@Brianzheng123) <[email protected]> * initial implementation of image preprocessing: resizing layer, and associated unit tests. Comments and refactoring for image scaling layer * refactoring in computeOutputShape for image resizing layer * Unit tests for image resizing preprocessing layer expanded and refactored * refactored unit tests for resizing layer * Preprocessing-Resizing layer unit test expansion and refactoring. Co-authored-by: Adam Lang <@AdamLang96> ([email protected]) * cleaning up commit diffs * cleaning up commit diffs * PR commit suggestions accepted - code refactored to reflect changes * resizing layer unit test refactoring Co-authored-by: AdamLang96 <[email protected]> * Linting issue resolved: unused import statement culled (#39) * Rescaling Preprocessing Layer Co-authored-by: David Kim (@koyykdy) <[email protected]> Brian Zheng (@Brianzheng123) <[email protected]> * PR issues resolved * linting and PR issues resolved Co-authored-by: Adam Lang (@AdamLang96) <[email protected]> Co-authored-by: (@Brianzheng123) <[email protected]> * initial implementation of image preprocessing: resizing layer, and associated unit tests. Comments and refactoring for image scaling layer * refactoring in computeOutputShape for image resizing layer * Unit tests for image resizing preprocessing layer expanded and refactored * refactored unit tests for resizing layer * Preprocessing-Resizing layer unit test expansion and refactoring. Co-authored-by: Adam Lang <@AdamLang96> ([email protected]) * cleaning up commit diffs * cleaning up commit diffs * PR commit suggestions accepted - code refactored to reflect changes * resizing layer unit test refactoring * linting issues resolved: unusued import statement culled Co-authored-by: AdamLang96 <[email protected]> * Update jasmine_util.ts (tensorflow#6872) FIX * webgl: Fix NaN issue (tensorflow#6828) Fix tensorflow#6822 Problem 1： On some GPUs, even if a and b are both non-NaN, the value of isNaN in vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0)); are still larger than 0., which misleads all values become NAN. 2： After resolving NAN issue, the result is still incorrect. It seems that the isnan_custom is not well supported on the problem GPU. After switching back to builtin isnan, everything works well. Solution: Use the bool type bvec4 instead of float type vec4 to calculate isNaN to avoid the the float precision issue when comparing with zero. Meanwhile, add an env flag WEBGL2_ISNAN_CUSTOM to allow user to specify which isnan to use. * Upgrade nodejs to 18.7.0 (tensorflow#6863) * Upgrade nodejs to 18.7.0 * Fix hash table test string not passed as base64 * fixed prelu fusing code that pre-maturely neg the const on multiply (tensorflow#6876) Co-authored-by: RajeshT <[email protected]> * Update tfjs-layers/src/layers/preprocessing/image_resizing.ts Co-authored-by: Matthew Soulanille <[email protected]> Co-authored-by: Yang Gu <[email protected]> Co-authored-by: Na Li <[email protected]> Co-authored-by: Matthew Soulanille <[email protected]> Co-authored-by: AdamLang96 <[email protected]> Co-authored-by: Linchenn <[email protected]> Co-authored-by: Jiajia Qin <[email protected]> Co-authored-by: Ping Yu <[email protected]> Co-authored-by: RajeshT <[email protected]> Co-authored-by: Matthew Soulanille <[email protected]> Co-authored-by: Yang Gu <[email protected]> Co-authored-by: Na Li <[email protected]> Co-authored-by: Matthew Soulanille <[email protected]> Co-authored-by: AdamLang96 <[email protected]> Co-authored-by: Linchenn <[email protected]> Co-authored-by: Jiajia Qin <[email protected]> Co-authored-by: Ping Yu <[email protected]> Co-authored-by: RajeshT <[email protected]> Co-authored-by: Matthew Soulanille <[email protected]>
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