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Fixed performance drop for Interpolate-4 #4354

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vgavrilo
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Details:

  • Fixed performance drop in Interpolate-4 when mode=linear instead of linear_onnx

Tickets:

  • 49045

vgavrilo added 30 commits July 30, 2020 09:20
@vgavrilo vgavrilo requested a review from ilyachur as a code owner February 16, 2021 08:19
@vgavrilo vgavrilo requested review from a team, mvafin, rkazants, yekruglov and lazarevevgeny and removed request for a team February 16, 2021 08:20
@vgavrilo
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@vgavrilo
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@GlebKazantaev, @ilyachur, @mvafin, @yekruglov, @rkazants, @vladimir-paramuzov, please, see this PR (#4354)

@ilyachur
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Do we have a performance numbers or tests which proof that the performance was fixed?

@ilyachur ilyachur self-assigned this Feb 17, 2021
@ilyachur ilyachur added this to the 2021.3 milestone Feb 17, 2021
@ilyachur ilyachur added bug Something isn't working category: Core OpenVINO Core (aka ngraph) labels Feb 17, 2021
@vgavrilo
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Do we have a performance numbers or tests which proof that the performance was fixed?

According to ticket content (see link to a performance report in the ticket), we have the following.

Before the merge of #970, for any Interpolate-4 nodes with 4D input data, the transformation ConvertInterpolate1ToInterpolate4 set the attribute mode of the operation Interpolate-4 as linear_onnx instead of linear, in the case of 4D input tensors.

Generally speaking, this behavior is not correct for non-ONNX models, and this behavior was corrected in the PR #970.

Next, plugins have no any vectorized implementation of the mode = linear, but have vectorized implementations of the mode linear_onnx. Hence, we have a performance drop (see the ticket).

This PR corrects the reason of this performance drop.

I created tickets to implement vectorized implementation in CPU and GPU plugins.

@vgavrilo
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@GlebKazantaev, @ilyachur, @mvafin, @yekruglov, @rkazants, @vladimir-paramuzov, please, see this PR (#4354)

@ilyachur ilyachur merged commit 3b25069 into openvinotoolkit:master Feb 17, 2021
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6 participants