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Use fill_argument for literals that have the same value #3815

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@pfultz2 pfultz2 commented Feb 14, 2025

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codecov bot commented Feb 14, 2025

Codecov Report

Attention: Patch coverage is 0% with 10 lines in your changes missing coverage. Please review.

Project coverage is 92.37%. Comparing base (768b4dd) to head (df700bd).

Files with missing lines Patch % Lines
src/module.cpp 0.00% 10 Missing ⚠️
Additional details and impacted files
@@             Coverage Diff             @@
##           develop    #3815      +/-   ##
===========================================
- Coverage    92.41%   92.37%   -0.04%     
===========================================
  Files          520      520              
  Lines        22472    22480       +8     
===========================================
  Hits         20767    20767              
- Misses        1705     1713       +8     

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Test Batch Rate new
3f5ec1
Rate old
214139
Diff Compare
torchvision-resnet50 64 3,233.96 3,235.79 -0.06%
torchvision-resnet50_fp16 64 6,866.95 6,876.30 -0.14%
torchvision-densenet121 32 2,434.16 2,437.41 -0.13%
torchvision-densenet121_fp16 32 4,194.65 4,205.62 -0.26%
torchvision-inceptionv3 32 1,614.53 1,614.06 0.03%
torchvision-inceptionv3_fp16 32 2,677.82 2,678.00 -0.01%
cadene-inceptionv4 16 750.47 750.03 0.06%
cadene-resnext64x4 16 808.90 809.60 -0.09%
slim-mobilenet 64 6,661.89 6,656.41 0.08%
slim-nasnetalarge 64 196.58 196.58 0.00%
slim-resnet50v2 64 3,429.13 3,429.08 0.00%
bert-mrpc-onnx 8 1,131.54 1,142.46 -0.96%
bert-mrpc-tf 1 497.51 487.75 2.00%
pytorch-examples-wlang-gru 1 483.62 539.97 -10.44% 🔴
pytorch-examples-wlang-lstm 1 436.41 432.68 0.86%
torchvision-resnet50_1 1 793.65 810.41 -2.07%
cadene-dpn92_1 1 431.43 430.86 0.13%
cadene-resnext101_1 1 389.11 390.48 -0.35%
onnx-taau-downsample 1 371.60 369.93 0.45%
dlrm-criteoterabyte 1 31.80 31.80 0.01%
dlrm-criteoterabyte_fp16 1 50.94 50.96 -0.03%
agentmodel 1 8,630.44 8,828.00 -2.24%
unet_fp16 2 58.29 58.15 0.25%
resnet50v1_fp16 1 1,063.83 1,029.51 3.33% 🔆
resnet50v1_int8 1 787.40 807.40 -2.48%
bert_base_cased_fp16 64 1,159.21 1,164.60 -0.46%
bert_large_uncased_fp16 32 360.12 361.78 -0.46%
bert_large_fp16 1 215.52 201.22 7.11% 🔆
distilgpt2_fp16 16 2,188.78 2,218.71 -1.35%
yolov5s 1 520.89 519.18 0.33%
tinyllama 1 49.12 43.62 12.60% 🔆
vicuna-fastchat 1 43.65 43.86 -0.47%
whisper-tiny-encoder 1 436.68 412.16 5.95% 🔆
whisper-tiny-decoder 1 448.43 410.84 9.15% 🔆

This build is not recommended to merge 🔴

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     ✅ bert-mrpc-onnx: PASSED: MIGraphX meets tolerance

     ✅ bert-mrpc-tf: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-gru: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-lstm: PASSED: MIGraphX meets tolerance

     ✅ torchvision-resnet50_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-dpn92_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-resnext101_1: PASSED: MIGraphX meets tolerance

     ✅ dlrm-criteoterabyte: PASSED: MIGraphX meets tolerance

     ✅ agentmodel: PASSED: MIGraphX meets tolerance

     ✅ unet: PASSED: MIGraphX meets tolerance

     ✅ resnet50v1: PASSED: MIGraphX meets tolerance

     ✅ bert_base_cased_fp16: PASSED: MIGraphX meets tolerance

🔴bert_large_uncased_fp16: FAILED: MIGraphX is not within tolerance - check verbose output


     ✅ bert_large: PASSED: MIGraphX meets tolerance

     ✅ yolov5s: PASSED: MIGraphX meets tolerance

     ✅ tinyllama: PASSED: MIGraphX meets tolerance

     ✅ vicuna-fastchat: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-encoder: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-decoder: PASSED: MIGraphX meets tolerance

     ✅ distilgpt2_fp16: PASSED: MIGraphX meets tolerance

@turneram turneram closed this Mar 7, 2025
@turneram turneram deleted the py-print-fill-argument branch March 7, 2025 15:48
@TedThemistokleous TedThemistokleous restored the py-print-fill-argument branch March 7, 2025 15:56
@TedThemistokleous TedThemistokleous added Perf Improve Cleanup Cleans up code from stale bits/warnings/previous changes for a previous feature PR labels Mar 7, 2025
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/AzurePipelines run

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Azure Pipelines successfully started running 1 pipeline(s).

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6 participants