Update device selection explainer #824
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Signed-off-by: Zoltan Kis <[email protected]>
anssiko
requested changes
Feb 27, 2025
Signed-off-by: Zoltan Kis <[email protected]>
anssiko
approved these changes
Mar 6, 2025
Co-authored-by: Anssi Kostiainen <[email protected]>
anssiko
approved these changes
Mar 6, 2025
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(I merged this PR to have a reference at hand to give to folks who are interested in contributing, in particularly to use cases.) |
zolkis
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Jun 17, 2025
This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback. Key changes include: - Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR webmachinelearning#809) and the shift towards hint-based, implementation-led device selection. - Clarified the impact of key issues (webmachinelearning#749, webmachinelearning#302, webmachinelearning#350) and PRs (webmachinelearning#809, webmachinelearning#824, webmachinelearning#855) on the device selection strategy. - Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR webmachinelearning#855. - Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes. - Added new open questions based on recent discussions (e.g., issue webmachinelearning#836, PR webmachinelearning#854 regarding querying actual device usage). - Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR webmachinelearning#860). - Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches. - Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue webmachinelearning#815) and the investigation of `graph.devices` (issue webmachinelearning#836, PR webmachinelearning#854). - Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document.
zolkis
pushed a commit
to zolkis/webnn
that referenced
this pull request
Jun 17, 2025
This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback. Key changes include: - Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR webmachinelearning#809) and the shift towards hint-based, implementation-led device selection. - Clarified the impact of key issues (webmachinelearning#749, webmachinelearning#302, webmachinelearning#350) and PRs (webmachinelearning#809, webmachinelearning#824, webmachinelearning#855) on the device selection strategy. - Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR webmachinelearning#855. - Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes. - Added new open questions based on recent discussions (e.g., issue webmachinelearning#836, PR webmachinelearning#854 regarding querying actual device usage). - Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR webmachinelearning#860). - Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches. - Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue webmachinelearning#815) and the investigation of `graph.devices` (issue webmachinelearning#836, PR webmachinelearning#854). - Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document.
zolkis
pushed a commit
to zolkis/webnn
that referenced
this pull request
Jun 17, 2025
This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback. Key changes include: - Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR webmachinelearning#809) and the shift towards hint-based, implementation-led device selection. - Clarified the impact of key issues (webmachinelearning#749, webmachinelearning#302, webmachinelearning#350) and PRs (webmachinelearning#809, webmachinelearning#824, webmachinelearning#855) on the device selection strategy. - Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR webmachinelearning#855. - Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes. - Added new open questions based on recent discussions (e.g., issue webmachinelearning#836, PR webmachinelearning#854 regarding querying actual device usage). - Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR webmachinelearning#860). - Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches. - Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue webmachinelearning#815) and the investigation of `graph.devices` (issue webmachinelearning#836, PR webmachinelearning#854). - Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document.
anssiko
pushed a commit
that referenced
this pull request
Jun 27, 2025
This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback. Key changes include: - Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR #809) and the shift towards hint-based, implementation-led device selection. - Clarified the impact of key issues (#749, #302, #350) and PRs (#809, #824, #855) on the device selection strategy. - Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR #855. - Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes. - Added new open questions based on recent discussions (e.g., issue #836, PR #854 regarding querying actual device usage). - Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR #860). - Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches. - Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue #815) and the investigation of `graph.devices` (issue #836, PR #854). - Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document. Signed-off-by: Zoltan Kis <[email protected]> With thanks to Jules for proofreading: Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
anssiko
pushed a commit
that referenced
this pull request
Aug 8, 2025
This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback. Key changes include: - Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR #809) and the shift towards hint-based, implementation-led device selection. - Clarified the impact of key issues (#749, #302, #350) and PRs (#809, #824, #855) on the device selection strategy. - Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR #855. - Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes. - Added new open questions based on recent discussions (e.g., issue #836, PR #854 regarding querying actual device usage). - Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR #860). - Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches. - Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue #815) and the investigation of `graph.devices` (issue #836, PR #854). - Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document. Signed-off-by: Zoltan Kis <[email protected]> With thanks to Jules for proofreading: Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
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Updated the device selection explainer with the latest discussions.
Fixed links that refer to past spec versions.