Write Bazel rule for IFRT dialect

[mofeing]

Currently it gives this error:

external/xla/xla/python/ifrt/ir/ifrt_ops.td:24:9: error: Could not find include file 'xla/python/ifrt/ir/ifrt_dialect.td'
include "xla/python/ifrt/ir/ifrt_dialect.td"

I believe that it's missing a include path flag.

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Benchmark Results

	main	7a96406...	main/7a964067b57d3d...
comptime/basics/2D sum	27 ± 1.6 ms	28.7 ± 1.1 ms	0.942
comptime/basics/Basic grad cos	0.0459 ± 0.0012 s	0.0485 ± 0.0018 s	0.947
comptime/basics/cos.(x)	31.4 ± 0.94 ms	0.0345 ± 0.0011 s	0.911
comptime/lux neural networks/ViT base	6.08 s	6.05 s	1
comptime/lux neural networks/ViT tiny	5.92 s	6.2 s	0.956
comptime/lux neural networks/vgg11 bn=false	0.409 ± 0.013 s	0.413 ± 0.013 s	0.99
comptime/lux neural networks/vgg13 bn=false	0.439 ± 0.0079 s	0.463 ± 0.0053 s	0.947
comptime/lux neural networks/vgg16 bn=false	0.529 ± 0.016 s	0.578 ± 0.024 s	0.915
comptime/lux neural networks/vgg19 bn=false	0.605 ± 0.0058 s	0.627 ± 0.021 s	0.965
runtime/lux neural networks/ViT base (compiled)	6.4 s	6.45 s	0.993
runtime/lux neural networks/ViT tiny (compiled)	1.73 s	1.75 s	0.986
runtime/lux neural networks/vgg11 bn=false (compiled)	2.12 s	2.08 s	1.02
runtime/lux neural networks/vgg13 bn=false (compiled)	2.97 s	3.02 s	0.984
runtime/lux neural networks/vgg16 bn=false (compiled)	3.78 s	3.74 s	1.01
runtime/lux neural networks/vgg19 bn=false (compiled)	4.61 s	4.54 s	1.01
time_to_load	1.48 ± 0.017 s	1.54 ± 0.017 s	0.962

Benchmark Plots

A plot of the benchmark results have been uploaded as an artifact to the workflow run for this PR.
Go to "Actions"->"Benchmark a pull request"->[the most recent run]->"Artifacts" (at the bottom).

[github-actions]

Reactant.jl Benchmarks

Benchmark suite	Current: 7a96406	Previous: deefd18	Ratio
ViT base (256 x 256 x 3 x 32)/forward/CUDA/Reactant	1301347763 ns	1354313354 ns	0.96
ViT base (256 x 256 x 3 x 32)/forward/CUDA/Lux	217103056 ns	208305734 ns	1.04
ViT base (256 x 256 x 3 x 32)/forward/CPU/Reactant	5365149260 ns	5150619393 ns	1.04
ViT base (256 x 256 x 3 x 32)/forward/CPU/Lux	22423672030 ns	19034043181 ns	1.18
ViT small (256 x 256 x 3 x 4)/forward/CUDA/Reactant	1257814655 ns	1337880973 ns	0.94
ViT small (256 x 256 x 3 x 4)/forward/CUDA/Lux	8327637 ns	9140912.5 ns	0.91
ViT small (256 x 256 x 3 x 4)/forward/CPU/Reactant	1634348478 ns	1693455123 ns	0.97
ViT small (256 x 256 x 3 x 4)/forward/CPU/Lux	2178014879 ns	2263974104 ns	0.96
ViT tiny (256 x 256 x 3 x 32)/forward/CUDA/Reactant	1257786527 ns	1332284786.5 ns	0.94
ViT tiny (256 x 256 x 3 x 32)/forward/CUDA/Lux	90765896 ns	86734383.5 ns	1.05
ViT tiny (256 x 256 x 3 x 32)/forward/CPU/Reactant	2171489336 ns	2287781106 ns	0.95
ViT tiny (256 x 256 x 3 x 32)/forward/CPU/Lux	4967371369 ns	6118937863 ns	0.81
ViT tiny (256 x 256 x 3 x 4)/forward/CUDA/Reactant	1329525357.5 ns	1274319613 ns	1.04
ViT tiny (256 x 256 x 3 x 4)/forward/CUDA/Lux	7794196 ns	7577830 ns	1.03
ViT tiny (256 x 256 x 3 x 4)/forward/CPU/Reactant	1474849210 ns	1512493678 ns	0.98
ViT tiny (256 x 256 x 3 x 4)/forward/CPU/Lux	1724297638 ns	1456174515 ns	1.18
ViT tiny (256 x 256 x 3 x 16)/forward/CUDA/Reactant	1306781721.5 ns	1263335461 ns	1.03
ViT tiny (256 x 256 x 3 x 16)/forward/CUDA/Lux	11562433 ns	11439682 ns	1.01
ViT tiny (256 x 256 x 3 x 16)/forward/CPU/Reactant	1768896684 ns	1805020552 ns	0.98
ViT tiny (256 x 256 x 3 x 16)/forward/CPU/Lux	2646587434.5 ns	2506386037 ns	1.06
ViT small (256 x 256 x 3 x 16)/forward/CUDA/Reactant	1309249187 ns	1307096998 ns	1.00
ViT small (256 x 256 x 3 x 16)/forward/CUDA/Lux	88858488 ns	87573137 ns	1.01
ViT small (256 x 256 x 3 x 16)/forward/CPU/Reactant	2229256097 ns	2278669956 ns	0.98
ViT small (256 x 256 x 3 x 16)/forward/CPU/Lux	3817263196 ns	3700585497 ns	1.03
ViT small (256 x 256 x 3 x 32)/forward/CUDA/Reactant	1307760748 ns	1310298018 ns	1.00
ViT small (256 x 256 x 3 x 32)/forward/CUDA/Lux	118030839 ns	109805738 ns	1.07
ViT small (256 x 256 x 3 x 32)/forward/CPU/Reactant	3029932924 ns	3158445388 ns	0.96
ViT small (256 x 256 x 3 x 32)/forward/CPU/Lux	9978512015 ns	14341152106 ns	0.70
ViT base (256 x 256 x 3 x 16)/forward/CUDA/Reactant	1356889531 ns	1384173668 ns	0.98
ViT base (256 x 256 x 3 x 16)/forward/CUDA/Lux	122479512.5 ns	125016343 ns	0.98
ViT base (256 x 256 x 3 x 16)/forward/CPU/Reactant	3198347884 ns	3254191833 ns	0.98
ViT base (256 x 256 x 3 x 16)/forward/CPU/Lux	7412499032 ns	6513914428 ns	1.14
ViT base (256 x 256 x 3 x 4)/forward/CUDA/Reactant	1335763412 ns	1339992292 ns	1.00
ViT base (256 x 256 x 3 x 4)/forward/CUDA/Lux	88481951 ns	81713817 ns	1.08
ViT base (256 x 256 x 3 x 4)/forward/CPU/Reactant	1893395827 ns	1963454757 ns	0.96
ViT base (256 x 256 x 3 x 4)/forward/CPU/Lux	2734552651 ns	2503177627 ns	1.09

This comment was automatically generated by workflow using github-action-benchmark.