[PT FE] Add huggingface hub tests (#19858)
* [PT FE] Add huggingface hub tests * Update requirements.txt * natten can't be installed * Remove librosa * Add xfail and skip marks * Remove t5 * Free up space * Apply suggestions from code review * Report free space * Clean pip cache * Temporarily disable det2 models * More du info * Remove tmp info * More du stats * Fix du report * Optimize du * Ignore error * Finalize changes * Update tests/model_hub_tests/torch_tests/test_transformers.py
This commit is contained in:
Maxim Vafin authored and 
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@@ -887,6 +887,13 @@ jobs:
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MODEL_HUB_TESTS_INSTALL_DIR: ${{ github.workspace }}/install/tests/model_hub_tests
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steps:
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- name: Maximize build space
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run: |
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sudo rm -rf /usr/local/lib/android # will release about 10 GB if you don't need Android
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sudo rm -rf /usr/share/dotnet # will release about 20GB if you don't need .NET
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sudo rm -rf /opt/ghc
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echo "Available storage:"
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df -h
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- name: Create Directories
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run: |
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mkdir -p ${{ env.INSTALL_DIR }} ${{ env.INSTALL_TEST_DIR }}
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@@ -917,16 +924,28 @@ jobs:
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- name: Install Python wheels
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run: |
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python3 -m pip install openvino --find-links=${{ env.INSTALL_DIR }}/tools
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- name: PyTorch Models Tests
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- name: Install requirements
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run: |
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python3 -m pip install -r ${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}/torch_tests/requirements.txt
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python3 -m pip install -r ${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}/torch_tests/requirements_secondary.txt
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python3 -m pip cache purge
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echo "Available storage:"
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df -h
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du -h -d0 ~/.cache ~/*
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- name: PyTorch Models Tests
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run: |
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export PYTHONPATH=${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}:$PYTHONPATH
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python3 -m pytest ${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}/torch_tests/ -m ${{ env.TYPE }} --html=${{ env.INSTALL_TEST_DIR }}/TEST-torch_model_tests.html --self-contained-html
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python3 -m pytest ${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}/torch_tests/ -m ${{ env.TYPE }} --html=${{ env.INSTALL_TEST_DIR }}/TEST-torch_model_tests.html --self-contained-html -v
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env:
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TYPE: ${{ github.event_name == 'schedule' && 'nightly' || 'precommit'}}
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TEST_DEVICE: CPU
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- name: Available storage after tests
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run: |
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echo "Available storage:"
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df -h
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du -h -d0 ~/.cache ~/*
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- name: Upload Test Results
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uses: actions/upload-artifact@v3
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if: ${{ always() }}
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@@ -78,7 +78,7 @@ class TestConvertModel:
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for i in range(len(ov_outputs)):
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cur_fw_res = fw_outputs[i]
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cur_ov_res = ov_outputs[i]
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print(f"fw_re: {cur_fw_res};\n ov_res: {cur_ov_res}")
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print(f"fw_res: {cur_fw_res};\n ov_res: {cur_ov_res}")
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is_ok = compare_two_tensors(cur_ov_res, cur_fw_res, fw_eps)
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assert is_ok, "Accuracy validation failed"
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@@ -0,0 +1,411 @@
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# List of models obtained from huggingface_hub api as one model per architecture with highest likes and downloads
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abcp4/mymodel-test,mymodel,skip,Load problem
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abeja/gpt-neox-japanese-2.7b,gpt_neox_japanese
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acl-submission-anonym/EAM-spectral,examuse,skip,Load problem
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adalbertojunior/modular-test,modular,skip,Load problem
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aerner/lm-v2,open-llama,skip,Load problem
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afonsosamarques/ardt-vanilla-combo_train_hopper_v2-2508_1336-33,decision_transformer,skip,Load problem
|
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aihijo/gec-zh-gector-bert-large,gector,skip,Load problem
|
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albert-base-v2,albert
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AlekseyKorshuk/test_reward_model,reward_model,skip,Load problem
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alibaba-damo/mgp-str-base,mgp-str,xfail,Compile error: unsupported Einsum
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allenai/hvila-block-layoutlm-finetuned-docbank,hierarchical_model,skip,Load problem
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allenai/longformer-base-4096,longformer,xfail,Unsupported op aten::as_strided
|
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ameya772/sentence-t5-base-atis-fine-tuned,T5,skip,Load problem
|
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andreasmadsen/efficient_mlm_m0.40,roberta-prelayernorm
|
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anton-l/emformer-base-librispeech,emformer,skip,Load problem
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anugunj/omnivore-swinL-in21k,omnivore,skip,Load problem
|
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apple/mobilevitv2-1.0-imagenet1k-256,mobilevitv2,xfail,Unsupported op aten::col2im
|
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ArthurZ/jukebox_prior_0,jukebox_prior,skip,Load problem
|
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ArthurZ/jukebox-vqvae,jukebox_vqvae,skip,Load problem
|
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ArthurZ/persimmon-8b-base,persimmon,skip,Load problem
|
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ashishpatel26/span-marker-bert-base-fewnerd-coarse-super,span-marker,skip,Load problem
|
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asi/albert-act-tiny,albert_act,skip,Load problem
|
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BAAI/AltCLIP,altclip,xfail,Unsupported op aten::numpy_T
|
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BAAI/AquilaCode-py,aquila,skip,Load problem
|
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bana513/opennmt-translator-en-hu,opennmt-translator,skip,Load problem
|
||||
benjamin/wtp-bert-mini,bert-char,skip,Load problem
|
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benjamin/wtp-canine-s-1l,la-canine,skip,Load problem
|
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beomi/exKcBERT-kowiki,exbert,skip,Load problem
|
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bert-base-uncased,bert
|
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bigscience/bloom-560m,bloom
|
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Bono93/basic-cnn-example,simplecnn,skip,Load problem
|
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caidas/swin2SR-realworld-sr-x4-64-bsrgan-psnr,swin2sr,xfail,Unsupported op prim::Constant
|
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camembert-base,camembert
|
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CarlCochet/trajectory-transformer-ant-expert-v2,trajectory_transformer,skip,Load problem
|
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CEBaB/bert-base-uncased.CEBaB.causalm.ambiance.2-class.exclusive.seed_42,bert_causalm,skip,Load problem
|
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CEBaB/gpt2.CEBaB.causalm.None__None.2-class.exclusive.seed_42,gpt2_causalm,skip,Load problem
|
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CEBaB/lstm.CEBaB.causalm.ambiance__food.2-class.exclusive.seed_42,lstm_causalm,skip,Load problem
|
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CEBaB/roberta-base.CEBaB.causalm.None__None.2-class.exclusive.seed_42,roberta_causalm,skip,Load problem
|
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cestwc/lava-small-gigaword,lava,skip,Load problem
|
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chlab/efficientnet_61_planet_detection,efficientnet_61_planet_detection,skip,Load problem
|
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CIDAS/clipseg-rd64-refined,clipseg
|
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clefourrier/graphormer-base-pcqm4mv2,graphormer,skip,Load problem
|
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cliang1453/deberta-v3-base-rte-teacher-stage1,ted-deberta-v2,skip,Load problem
|
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clip-italian/clip-italian,vision-text-dual-encoder,skip,Load problem
|
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Clyde013/deqbert-base,deqbert,skip,Load problem
|
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connor-henderson/fastspeech2_conformer,fastspeech2_conformer,skip,Load problem
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connor-henderson/fastspeech2_conformer_with_hifigan,fastspeech2_conformer_with_hifigan,skip,Load problem
|
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csarron/meter-vqa2-ft,meter,skip,Load problem
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ctrl,ctrl
|
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cwkeam/mctc-large,mctc,skip,Load problem
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dandelin/vilt-b32-finetuned-vqa,vilt,xfail,Unsupported op aten::_unique2 aten::multinomial
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dangkhoadl/custom_CNN_1D,cnn,skip,Load problem
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declare-lab/segue-w2v2-base,segue,skip,Load problem
|
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deepesh0x/autotrain-mlsec-1013333726,julien,skip,Load problem
|
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Dewa/Dog_Model_From_Scratch_v2,simple_image_classification,skip,Load problem
|
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dg845/univnet-dev,univnet,skip,Load problem
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distilbert-base-uncased,distilbert
|
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DiViorg/REC-Transformer,rec_transformer,skip,Load problem
|
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dreamerlin/chatbind-7b-delta,llava_image_bind_select,skip,Load problem
|
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edugp/data2vec-nlp-base,data2vec,skip,Load problem
|
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EleutherAI/enformer-official-rough,enformer,skip,Load problem
|
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EleutherAI/gpt-neo-125m,gpt_neo
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EleutherAI/pythia-6.9b,gpt_neox
|
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facebook/bart-large-mnli,bart
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facebook/convnextv2-tiny-22k-384,convnextv2
|
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facebook/detr-resnet-50,detr
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facebook/dinov2-base,dinov2,skip,Load problem
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facebook/dpr-question_encoder-single-nq-base,dpr
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facebook/encodec_24khz,encodec,skip,Load problem
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facebook/esm2_t6_8M_UR50D,esm,xfail,Tracing error: The values for attribute 'shape' do not match
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facebook/flava-full,flava,skip,Load problem
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facebook/flava-image-codebook,flava_image_codebook,skip,Load problem
|
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facebook/m2m100_418M,m2m_100
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facebook/mask2former-swin-base-coco-panoptic,mask2former,skip,Load problem
|
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facebook/maskformer-swin-base-coco,maskformer
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facebook/mms-tts-eng,vits,skip,Load problem
|
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facebook/musicgen-small,musicgen,skip,Load problem
|
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facebook/opt-125m,opt
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facebook/rag-token-nq,rag,skip,Load problem
|
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facebook/sam-vit-large,sam,xfail,No node with name original_sizes
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facebook/timesformer-base-finetuned-k400,timesformer,xfail,Shape inference of Add node failed: Eltwise shape infer input shapes dim index: 1 mismatch
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facebook/vit-mae-base,vit_mae,xfail,Accuracy validation failed
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facebook/wmt19-ru-en,fsmt,skip,Load problem
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facebook/xlm-roberta-xl,xlm-roberta-xl
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facebook/xmod-base,xmod,skip,Load problem
|
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flax-community/ft5-cnn-dm,f_t5,skip,Load problem
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fnlp/elasticbert-base,elasticbert,skip,Load problem
|
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FranzStrauss/ponet-base-uncased,ponet,skip,Load problem
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funnel-transformer/small,funnel
|
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fusing/latent-diffusion-text2im-large,ldmbert,skip,Load problem
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Geor111y/flair-ner-addresses-extractor,flair,skip,Load problem
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gia-project/gia,gia,skip,Load problem
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gokuls/bert_12_layer_model_v1,hybridbert,skip,Load problem
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google/bigbird-roberta-base,big_bird,skip,Load problem
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google/bit-50,bit
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google/canine-s,canine,xfail,aten::slice: Parameter axis 3 out of the tensor rank range
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google/efficientnet-b2,efficientnet,xfail,Compile error: AvgPool: Kernel after dilation has size (dim: 1408) larger than the data shape after padding (dim: 9) at axis 0.
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google/electra-base-discriminator,electra
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google/flan-t5-base,t5
|
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google/fnet-base,fnet,xfail,Unsupported op aten::fft_fftn aten::real
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google/mobilebert-uncased,mobilebert
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||||
google/mobilenet_v1_0.75_192,mobilenet_v1
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google/mt5-base,mt5
|
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google/owlvit-base-patch32,owlvit
|
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google/pix2struct-docvqa-base,pix2struct,skip,Load problem
|
||||
google/realm-orqa-nq-openqa,realm,skip,Load problem
|
||||
google/reformer-crime-and-punishment,reformer,skip,Load problem
|
||||
google/tapas-large-finetuned-wtq,tapas,skip,Load problem
|
||||
google/vit-hybrid-base-bit-384,vit-hybrid,skip,Load problem
|
||||
google/vivit-b-16x2-kinetics400,vivit
|
||||
Goutham-Vignesh/ContributionSentClassification-scibert,scibert,skip,Load problem
|
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gpt2,gpt2
|
||||
Graphcore/groupbert-base-uncased,groupbert,skip,Load problem
|
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haoranzhao419/saffu-100M-0.1,saffu-100M-0.1,skip,Load problem
|
||||
Helsinki-NLP/opus-mt-fr-en,marian
|
||||
hf-internal-testing/random-nllb-moe-2-experts,nllb-moe,skip,Load problem
|
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hf-internal-testing/tiny-random-BlenderbotModel,blenderbot,skip,Load problem
|
||||
hf-internal-testing/tiny-random-CodeGenModel,codegen
|
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hf-internal-testing/tiny-random-convnext,convnext
|
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hf-internal-testing/tiny-random-CvtModel,cvt
|
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hf-internal-testing/tiny-random-Data2VecAudioModel,data2vec-audio,skip,Load problem
|
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hf-internal-testing/tiny-random-Data2VecTextModel,data2vec-text
|
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hf-internal-testing/tiny-random-Data2VecVisionModel,data2vec-vision
|
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hf-internal-testing/tiny-random-DeiTModel,deit
|
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hf-internal-testing/tiny-random-DonutSwinModel,donut-swin,xfail,Unsupported op aten::adaptive_avg_pool1d
|
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hf-internal-testing/tiny-random-EfficientFormerForImageClassification,efficientformer
|
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hf-internal-testing/tiny-random-flaubert,flaubert
|
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hf-internal-testing/tiny-random-FocalNetModel,focalnet,xfail,Unsupported op aten::adaptive_avg_pool1d
|
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hf-internal-testing/tiny-random-GPTBigCodeForCausalLM,gpt_bigcode,skip,Load problem
|
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hf-internal-testing/tiny-random-GPTJModel,gptj
|
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hf-internal-testing/tiny-random-groupvit,groupvit
|
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hf-internal-testing/tiny-random-IBertModel,ibert,skip,Load problem
|
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hf-internal-testing/tiny-random-ImageGPTModel,imagegpt
|
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hf-internal-testing/tiny-random-LevitModel,levit,skip,Load problem
|
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hf-internal-testing/tiny-random-LiltModel,lilt,skip,Load problem
|
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hf-internal-testing/tiny-random-LongT5Model,longt5,skip,Load problem
|
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hf-internal-testing/tiny-random-mbart,mbart,xfail,Compile error: CPU plug-in doesnt support Squeeze operation with dynamic rank
|
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hf-internal-testing/tiny-random-MobileNetV2Model,mobilenet_v2
|
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hf-internal-testing/tiny-random-mobilevit,mobilevit
|
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hf-internal-testing/tiny-random-MPNetModel,mpnet
|
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hf-internal-testing/tiny-random-MptForCausalLM,mpt,skip,Load problem
|
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hf-internal-testing/tiny-random-NllbMoeForConditionalGeneration,nllb_moe,skip,Load problem
|
||||
hf-internal-testing/tiny-random-NystromformerModel,nystromformer
|
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hf-internal-testing/tiny-random-PegasusModel,pegasus,skip,Load problem
|
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hf-internal-testing/tiny-random-PoolFormerModel,poolformer,skip,Load problem
|
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hf-internal-testing/tiny-random-RegNetModel,regnet
|
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hf-internal-testing/tiny-random-RemBertModel,rembert
|
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hf-internal-testing/tiny-random-RoCBertModel,roc_bert,skip,Load problem
|
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hf-internal-testing/tiny-random-RoFormerModel,roformer
|
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hf-internal-testing/tiny-random-SegformerModel,segformer
|
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hf-internal-testing/tiny-random-SEWDModel,sew-d,skip,Load problem
|
||||
hf-internal-testing/tiny-random-SEWModel,sew,skip,Load problem
|
||||
hf-internal-testing/tiny-random-Speech2TextModel,speech_to_text,skip,Load problem
|
||||
hf-internal-testing/tiny-random-speech-encoder-decoder,speech-encoder-decoder,skip,Load problem
|
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hf-internal-testing/tiny-random-SplinterModel,splinter,skip,Load problem
|
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hf-internal-testing/tiny-random-SqueezeBertModel,squeezebert
|
||||
hf-internal-testing/tiny-random-SwinModel,swin,xfail,Unsupported op aten::adaptive_avg_pool1d
|
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hf-internal-testing/tiny-random-unispeech,unispeech,skip,Load problem
|
||||
hf-internal-testing/tiny-random-UniSpeechSatModel,unispeech-sat,skip,Load problem
|
||||
hf-internal-testing/tiny-random-vision_perceiver_conv,perceiver
|
||||
hf-internal-testing/tiny-random-ViTMSNModel,vit_msn
|
||||
hf-internal-testing/tiny-random-wav2vec2-conformer,wav2vec2-conformer
|
||||
hf-internal-testing/tiny-random-XLMModel,xlm
|
||||
hfl/vle-base,vle,skip,Load problem
|
||||
HJHGJGHHG/GAU-Base-Full,gau,skip,Load problem
|
||||
huggingface/autoformer-tourism-monthly,autoformer,skip,Load problem
|
||||
huggingface/informer-tourism-monthly,informer,skip,Load problem
|
||||
huggingface/time-series-transformer-tourism-monthly,time_series_transformer,skip,Load problem
|
||||
HuggingFaceM4/tiny-random-idefics,idefics,skip,Load problem
|
||||
HuggingFaceM4/tiny-random-vllama-clip,vllama,skip,Load problem
|
||||
HuggingFaceM4/tiny-random-vopt-clip,vopt,skip,Load problem
|
||||
HuiHuang/gpt3-damo-base-zh,gpt3,skip,Load problem
|
||||
hustvl/yolos-tiny,yolos
|
||||
iakarshu/tilt_base,tilt_base_configuration,skip,Load problem
|
||||
ibm/MoLM-350M-4B,moduleformer,skip,Load problem
|
||||
IDEA-CCNL/Randeng-Deltalm-362M-En-Zh,Deltalm,skip,Load problem
|
||||
Inderpreet01/seaformer-semantic-segmentation-large,seaformer,skip,Load problem
|
||||
Intel/dpt-hybrid-midas,dpt
|
||||
Intel/tvp-base,tvp,skip,Load problem
|
||||
isemmanuelolowe/code-embedder,instruct-codebert,skip,Load problem
|
||||
isemmanuelolowe/instruct-codet5-5,instruct-codet5,skip,Load problem
|
||||
jaketae/fastspeech2-ljspeech,fastspeech2,skip,Load problem
|
||||
jambran/depression-classification,DepressionDetection,skip,Load problem
|
||||
Jellywibble/dalio-reward-charlie-v1,reward-model,skip,Load problem
|
||||
JonasGeiping/crammed-bert-legacy,crammedBERT,skip,Load problem
|
||||
jonatasgrosman/wav2vec2-large-xlsr-53-english,wav2vec2,xfail,Unsupported op aten::index_put_ prim::TupleConstruct
|
||||
Joqsan/test-my-fnet,my_fnet,skip,Load problem
|
||||
jozhang97/deta-swin-large,deta,skip,Load problem
|
||||
jploski/retnet-mini-shakespeare,retnet,skip,Load problem
|
||||
juhi7ag/idea-model2,,skip,Load problem
|
||||
junnyu/autobert-small-light,autobert,skip,Load problem
|
||||
junnyu/chinese_GAU-alpha-char_L-24_H-768,gau_alpha,skip,Load problem
|
||||
junnyu/flash_small_wwm_cluecorpussmall,flash,skip,Load problem
|
||||
junnyu/flashquad_small_wwm_cluecorpussmall,flash_quad,skip,Load problem
|
||||
kakaobrain/align-base,align,xfail,Compile error: AvgPool: Kernel after dilation has size (dim: 640) larger than the data shape after padding (dim: 9) at axis 0.
|
||||
KBLab/megatron-bert-large-swedish-cased-110k,megatron-bert
|
||||
kiddothe2b/hierarchical-transformer-base-4096-v2,hat,skip,Load problem
|
||||
k-l-lambda/clip-text-generator,clip_text_generator,skip,Load problem
|
||||
k-l-lambda/stable-diffusion-v1-4-inv-embed,inv_word_embed,skip,Load problem
|
||||
KoboldAI/fairseq-dense-13B-Janeway,xglm,skip,Large Model
|
||||
konverner/qdq-camembert-apolliner,qdqbert
|
||||
krasserm/perceiver-ar-clm-base,perceiver-ar-causal-language-model,skip,Load problem
|
||||
krasserm/perceiver-ar-sam-giant-midi,perceiver-ar-symbolic-audio-model,skip,Load problem
|
||||
krasserm/perceiver-io-img-clf,perceiver-io-image-classifier,skip,Load problem
|
||||
krasserm/perceiver-io-mlm,perceiver-io-masked-language-model,skip,Load problem
|
||||
krasserm/perceiver-io-optical-flow,perceiver-io-optical-flow,skip,Load problem
|
||||
krasserm/perceiver-io-txt-clf-imdb,perceiver-io-text-classifier,skip,Load problem
|
||||
ksmcg/fan_small_12_p16_224,fan,skip,Load problem
|
||||
laion/clap-htsat-unfused,clap,skip,Load problem
|
||||
Langboat/ReGPT-125M-200G,re_gpt,skip,Load problem
|
||||
lengyue233/content-vec-best,hubert
|
||||
Lewislou/cellseg_sribd,cell_sribd,skip,Load problem
|
||||
liamcripwell/o-conbart,context-bart,skip,Load problem
|
||||
liamcripwell/pgdyn-plan,context-roberta,skip,Load problem
|
||||
linhdo/graphdoc,graphdoc,skip,Load problem
|
||||
LinkSoul/Chinese-LLaVA-Baichuan,llava,skip,Load problem
|
||||
LinkSoul/LLaSM-Cllama2,llaaa,skip,Load problem
|
||||
lintang/t5-v2-xl-flan,umt5
|
||||
liuhaotian/LLaVA-Lightning-MPT-7B-preview,llava_mpt,skip,Load problem
|
||||
liya0121/my_finetune_0121,progen,skip,Load problem
|
||||
lucadiliello/BLEURT-20,bleurt,skip,Load problem
|
||||
lum-ai/metal,metal,skip,Load problem
|
||||
luodian/OTTER-MPT1B-RPJama-Init,otter,skip,Load problem
|
||||
luoruipu1/valley-13b-v1-delta,Valley,skip,Load problem
|
||||
luoruipu1/Valley2-7b,valley,skip,Load problem
|
||||
Lutech-AI/I-SPIn,I-SPIn,skip,Load problem
|
||||
MAGAer13/mplug-owl-llama-7b,mplug-owl,skip,Load problem
|
||||
manu/contrastive_zeroner,contrastive_zeroner,skip,Load problem
|
||||
manu/lilt-infoxlm-base,liltrobertalike,skip,Load problem
|
||||
manu/mplt_untrained,mplt,skip,Load problem
|
||||
matheusntg/character-bert-pt-normal,character_bert,skip,Load problem
|
||||
MBZUAI/swiftformer-xs,swiftformer
|
||||
MCG-NJU/videomae-base-finetuned-kinetics,videomae
|
||||
M-CLIP/XLM-Roberta-Large-Vit-B-32,M-CLIP,skip,Load problem
|
||||
medhabi/distilbert-base-uncased-score-pred,text-to-rating,skip,Load problem
|
||||
meta-llama/Llama-2-7b-hf,llama,skip,Load problem
|
||||
microsoft/beit-base-patch16-224-pt22k-ft22k,beit
|
||||
microsoft/biogpt,biogpt
|
||||
microsoft/conditional-detr-resnet-50,conditional_detr
|
||||
microsoft/deberta-base,deberta
|
||||
microsoft/git-large-coco,git,skip,Load problem
|
||||
microsoft/layoutlm-base-uncased,layoutlm
|
||||
microsoft/layoutlmv2-base-uncased,layoutlmv2,skip,Load problem
|
||||
microsoft/layoutlmv3-base,layoutlmv3,skip,Load problem
|
||||
microsoft/markuplm-base,markuplm,skip,Load problem
|
||||
microsoft/resnet-50,resnet
|
||||
microsoft/speecht5_hifigan,hifigan,skip,Load problem
|
||||
microsoft/speecht5_tts,speecht5,skip,Load problem
|
||||
microsoft/swinv2-tiny-patch4-window8-256,swinv2,xfail,Unsupported op aten::adaptive_avg_pool1d
|
||||
microsoft/table-transformer-detection,table-transformer
|
||||
microsoft/wavlm-large,wavlm,skip,Load problem
|
||||
microsoft/xclip-base-patch32,xclip,skip,Load problem
|
||||
microsoft/xprophetnet-large-wiki100-cased,xlm-prophetnet,xfail,Unsupported op aten::fill_diagonal_
|
||||
miguelvictor/python-fromzero-lstmlm,lstmlm,skip,Load problem
|
||||
mingzi151/test-hf-wav2vec2bert,wav2vec2bert,skip,Load problem
|
||||
MIT/ast-finetuned-audioset-10-10-0.4593,audio-spectrogram-transformer,skip,Load problem
|
||||
Mizuiro-sakura/luke-japanese-large-sentiment-analysis-wrime,luke
|
||||
mlml-chip/thyme2_colon_e2e,cnlpt,skip,Load problem
|
||||
mnaylor/mega-base-wikitext,mega,skip,Load problem
|
||||
mohitsha/tiny-random-testing-bert2gpt2,encoder-decoder
|
||||
MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli,deberta-v2
|
||||
MoritzLaurer/ernie-m-large-mnli-xnli,ernie_m
|
||||
mrm8488/prunebert-base-uncased-finepruned-topK-squadv2,masked_bert,skip,Load problem
|
||||
muditb/headline_classifier,BertModel,skip,Load problem
|
||||
nanashi161382/clip-text-deprojector,clip_text_deprojector_model,skip,Load problem
|
||||
nateraw/vit-age-classifier,vit
|
||||
naver-clova-ocr/bros-base-uncased,bros,skip,Load problem
|
||||
navervision/CompoDiff-Aesthetic,CompoDiff,skip,Load problem
|
||||
navervision/KELIP,kelip,skip,Load problem
|
||||
NCAI/NCAI-BERT,lean_albert,skip,Load problem
|
||||
nglaura/skimformer,skimformer,skip,Load problem
|
||||
nguyenvulebinh/robustspeech-asr,robustspeech,skip,Load problem
|
||||
nguyenvulebinh/voice-filter,voicefilter,skip,Load problem
|
||||
NiCy/seg-ment-tation,seg-ment-tation,skip,Load problem
|
||||
nielsr/audio-spectogram-transformer-finetuned-audioset-10-10-0.4593,audio-spectogram-transformer,skip,Load problem
|
||||
nielsr/convnext-tiny-maskrcnn,maskrcnn,skip,Load problem
|
||||
nielsr/H3-125m,h3,skip,Load problem
|
||||
nielsr/layoutreader-readingbank,layoutreader,skip,Load problem
|
||||
nielsr/pix2seq-base,pix2seq,skip,Load problem
|
||||
nielsr/tapex-large,tapex,skip,Load problem
|
||||
nielsr/udop-large,udop,skip,Load problem
|
||||
nielsr/vitmatte-small-composition-1k,vitmatte,skip,Load problem
|
||||
nllg/poetry-bygpt5-small-en,bygpt5,skip,Load problem
|
||||
nlpconnect/vit-gpt2-image-captioning,vision-encoder-decoder
|
||||
OATML-Markslab/Tranception_Small,tranception,skip,Load problem
|
||||
OFA-Sys/chinese-clip-vit-base-patch16,chinese_clip
|
||||
openai/clip-vit-large-patch14,clip
|
||||
openai/jukebox-1b-lyrics,jukebox,skip,Load problem
|
||||
openai/whisper-medium,whisper,skip,Load problem
|
||||
openai-gpt,openai-gpt
|
||||
OpenAssistant/oasst-rm-2-pythia-6.9b-epoch-1,gpt_neox_reward_model,skip,Load problem
|
||||
openmmlab/upernet-convnext-small,upernet,skip,Load problem
|
||||
openMUSE/clip-vit-large-patch14-text-enc,clip_text_model,skip,Load problem
|
||||
PatrickHaller/ngme-llama-264M,ngme,skip,Load problem
|
||||
patrickvonplaten/bert2gpt2-cnn_dailymail-fp16,encoder_decoder,skip,Load problem
|
||||
paulhindemith/test-zeroshot,test-zeroshot,skip,Load problem
|
||||
PGT/orig-nystromformer-s-artificial-balanced-max500-490000-0,graph_nystromformer,skip,Load problem
|
||||
pie/example-ner-spanclf-conll03,TransformerSpanClassificationModel,skip,Load problem
|
||||
pie/example-re-textclf-tacred,TransformerTextClassificationModel,skip,Load problem
|
||||
pleisto/yuren-baichuan-7b,multimodal_llama,skip,Load problem
|
||||
predictia/europe_reanalysis_downscaler_convbaseline,convbilinear,skip,Load problem
|
||||
predictia/europe_reanalysis_downscaler_convswin2sr,conv_swin2sr,skip,Load problem
|
||||
pszemraj/led-large-book-summary,led,xfail,Unsupported op aten::as_strided
|
||||
qmeeus/whisper-small-ner-combined,whisper_for_slu,skip,Load problem
|
||||
raman-ai/pcqv2-tokengt-lap16,tokengt,skip,Load problem
|
||||
range3/pegasus-gpt2-medium,pegasusgpt2,skip,Load problem
|
||||
regisss/bridgetower-newyorker-a100-8x,bridgetower
|
||||
rinna/japanese-cloob-vit-b-16,cloob,skip,Load problem
|
||||
Rocketknight1/tiny-random-falcon-7b,falcon,skip,Load problem
|
||||
RUCAIBox/mass-base-uncased,mass,skip,Load problem
|
||||
RWKV/rwkv-4-169m-pile,rwkv,skip,Load problem
|
||||
sahasrarjn/interbert,BERT,skip,Load problem
|
||||
saibo/genkalm-medium-gpt2,genkalm,skip,Load problem
|
||||
SajjadAyoubi/clip-fa-vision,clip_vision_model
|
||||
Salesforce/blip2-flan-t5-xl,blip-2,skip,Load problem
|
||||
Salesforce/blip-image-captioning-large,blip,skip,Load problem
|
||||
Salesforce/instructblip-vicuna-7b,instructblip,skip,Load problem
|
||||
SamLowe/roberta-base-go_emotions,roberta
|
||||
sanchit-gandhi/enhanced_direct_s2st_en_to_es,speech-to-speech,skip,Load problem
|
||||
sciki/finetune_tinybert,finetune-tinybert,skip,Load problem
|
||||
sebastian-hofstaetter/colbert-distilbert-margin_mse-T2-msmarco,ColBERT,skip,Load problem
|
||||
sebastian-hofstaetter/distilbert-cat-margin_mse-T2-msmarco,BERT_Cat,skip,Load problem
|
||||
sebastian-hofstaetter/idcm-distilbert-msmarco_doc,IDCM,skip,Load problem
|
||||
SenseTime/deformable-detr,deformable_detr,skip,Load problem
|
||||
shahules786/Reward-model-gptneox-410M,rm_gptneox_config,skip,Load problem
|
||||
shauray/Llava-Llama-2-7B-hf,llavallama,skip,Load problem
|
||||
shauray/ViTPose,vitpose,skip,Load problem
|
||||
sheonhan/ict-imagenet-256,ict,skip,Load problem
|
||||
shibing624/text2vec-base-chinese-paraphrase,ernie
|
||||
shikhartuli/flexibert-mini,flexibert,skip,Load problem
|
||||
shikras/shikra-7b-delta-v1-0708,shikra,skip,Load problem
|
||||
shi-labs/dinat-mini-in1k-224,dinat,xfail,Unsupported op aten::adaptive_avg_pool1d
|
||||
shi-labs/nat-mini-in1k-224,nat,xfail,Unsupported op aten::adaptive_avg_pool1d
|
||||
shi-labs/oneformer_ade20k_swin_large,oneformer,skip,Load problem
|
||||
shuqi/seed-encoder,seed_encoder,skip,Load problem
|
||||
sijunhe/nezha-cn-base,nezha
|
||||
sjiang1/codecse,roberta_for_cl,skip,Load problem
|
||||
slh/fcnet-base-cased,fcnet,skip,Load problem
|
||||
snoop2head/Deep-Shallow-Ko2En,transformer,skip,Load problem
|
||||
Solomonik/SeqTokenModelMultiple,SeqToken,skip,Load problem
|
||||
solotimes/lavibe_base,donut,skip,Load problem
|
||||
songlab/gpn-brassicales,ConvNet,skip,Load problem
|
||||
speechbrain/m-ctc-t-large,mctct
|
||||
Splend1dchan/wav2vec2-large-lv60_t5lephone-small_lna_bs64,speechmix,skip,Load problem
|
||||
stefan-it/bort-full,bort,skip,Load problem
|
||||
SteveZhan/my-resnet50d,resnet_steve,skip,Load problem
|
||||
suno/bark,bark,skip,Load problem
|
||||
surajnair/r3m-50,r3m,skip,Load problem
|
||||
susnato/clvp_dev,clvp,skip,Load problem
|
||||
Tanrei/GPTSAN-japanese,gptsan-japanese,xfail,Unsupported op aten::clip aten::index_put_ prim::TupleConstruct
|
||||
tau/bart-large-sled-govreport,tau/sled,skip,Load problem
|
||||
taufeeque/best-cb-model,codebook,skip,Load problem
|
||||
Team-PIXEL/pixel-base,pixel,skip,Load problem
|
||||
tensorpro/clip_vip_pretrained_base_16,clip_vip,skip,Load problem
|
||||
thomwolf/vqgan_imagenet_f16_1024,vqgan_model,skip,Load problem
|
||||
thu-ml/zh-clip-vit-roberta-large-patch14,zhclip,skip,Load problem
|
||||
tifa-benchmark/promptcap-coco-vqa,ofa,skip,Load problem
|
||||
tli8hf/robertabase_snli,transformerfornli,skip,Load problem
|
||||
transfo-xl-wt103,transfo-xl,xfail,Unsupported op aten::clamp_ aten::index_copy_
|
||||
transZ/BART_shared_clean,shared_bart,skip,Load problem
|
||||
transZ/BART_shared_v2,shared_bart_v2,skip,Load problem
|
||||
transZ/misecom,misecom,skip,Load problem
|
||||
transZ/parex,parex,skip,Load problem
|
||||
transZ/phrext,phrext,skip,Load problem
|
||||
transZ/reword,reword,skip,Load problem
|
||||
transZ/roberta_texid,roberta_texid,skip,Load problem
|
||||
transZ/tforge_v1.9,Transformer_Forge,skip,Load problem
|
||||
trl-internal-testing/tiny-random-BigBirdPegasusForConditionalGeneration,bigbird_pegasus,skip,Load problem
|
||||
trl-internal-testing/tiny-random-BlenderbotSmallForConditionalGeneration,blenderbot-small,skip,Load problem
|
||||
trl-internal-testing/tiny-random-MvpForConditionalGeneration,mvp,skip,Load problem
|
||||
trl-internal-testing/tiny-random-PegasusXForConditionalGeneration,pegasus_x,skip,Load problem
|
||||
trl-internal-testing/tiny-random-PLBartForConditionalGeneration,plbart,skip,Load problem
|
||||
trl-internal-testing/tiny-random-ProphetNetForConditionalGeneration,prophetnet,skip,Load problem
|
||||
trl-internal-testing/tiny-random-SwitchTransformersForConditionalGeneration,switch_transformers,skip,Load problem
|
||||
turing-motors/heron-chat-blip-ja-stablelm-base-7b-v0,video_blip,skip,Load problem
|
||||
turing-motors/heron-chat-git-ELYZA-fast-7b-v0,git_llama,skip,Load problem
|
||||
uclanlp/visualbert-vqa-coco-pre,visual_bert,skip,Load problem
|
||||
ummagumm-a/samolet_room_classifier,AirModelHF,skip,Load problem
|
||||
ummagumm-a/samolet-room-classifier,gru,skip,Load problem
|
||||
UNCANNY69/Misinfo-BERT-LSTM,BertLSTMForSequenceClassification,skip,Load problem
|
||||
UNCANNY69/Miss-BERT-CNN,BertCNNForSequenceClassification,skip,Load problem
|
||||
unc-nlp/lxmert-base-uncased,lxmert,skip,Load problem
|
||||
uw-madison/mra-base-512-4,mra,skip,Load problem
|
||||
uw-madison/yoso-4096,yoso,skip,Fatal Python error: Aborted
|
||||
valhalla/cogview-gpt2-test,cog_view,skip,Load problem
|
||||
valhalla/s2t_mustc_multilinguial_medium,speech_to_text_transformer,skip,Load problem
|
||||
vblagoje/greaselm-csqa,greaselm,skip,Load problem
|
||||
vinvino02/glpn-nyu,glpn
|
||||
Visual-Attention-Network/van-base,van
|
||||
visualjoyce/transformers4vl-uniter-base,uniter,skip,Load problem
|
||||
visualjoyce/transformers4vl-vilbert-mt,vilbert,skip,Load problem
|
||||
vumichien/nonsemantic-speech-trillsson3,trillsson_efficientnet,skip,Load problem
|
||||
vumichien/trillsson3-ft-keyword-spotting-12,trillsson_efficient,skip,Load problem
|
||||
wangruiai2023/nougat,nougat,skip,Load problem
|
||||
WENGSYX/CoNN_Parity,conn,skip,Load problem
|
||||
xlm-roberta-base,xlm-roberta
|
||||
xlnet-base-cased,xlnet
|
||||
ybelkada/focusondepth,focusondepth,skip,Load problem
|
||||
ybelkada/random-tiny-BertGenerationModel,bert-generation,skip,Load problem
|
||||
ydshieh/temp-testing-kosmos-2,kosmos-2,skip,Load problem
|
||||
YituTech/conv-bert-base,convbert
|
||||
yjernite/retribert-base-uncased,retribert,xfail,Unsupported op aten::cross_entropy_loss
|
||||
ylacombe/hf-seamless-m4t-medium,seamless_m4t,skip,Load problem
|
||||
youzanai/clip-product-title-chinese,clip_chinese_model,skip,Load problem
|
||||
Yova/SmallCapOPT7M,smallcap,skip,Load problem
|
||||
yusufani/trclip-vitl14-e10,trclip,skip,Load problem
|
||||
yysung53/dpr,text_similarity,skip,Load problem
|
||||
Zetatech/pvt-tiny-224,pvt,skip,Load problem
|
||||
ZinengTang/tvlt-base,tvlt,skip,Load problem
|
||||
zuppif/resnetd-18,resnetd,skip,Load problem
|
||||
@@ -5,3 +5,12 @@ pytest-html
|
||||
torch
|
||||
torchvision
|
||||
av
|
||||
transformers
|
||||
timm
|
||||
sacremoses
|
||||
sentencepiece
|
||||
datasets
|
||||
pyctcdecode
|
||||
pytorch-quantization --extra-index-url https://pypi.ngc.nvidia.com
|
||||
protobuf
|
||||
soundfile
|
||||
@@ -1,3 +1,4 @@
|
||||
-c ../../constraints.txt
|
||||
# This file contains requirements dependednt from modules in requirements.txt
|
||||
git+https://github.com/facebookresearch/detectron2.git
|
||||
git+https://github.com/facebookresearch/detectron2.git
|
||||
natten
|
||||
@@ -0,0 +1,287 @@
|
||||
# Copyright (C) 2018-2023 Intel Corporation
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
import pytest
|
||||
import os
|
||||
import torch
|
||||
import tempfile
|
||||
from huggingface_hub import model_info
|
||||
from models_hub_common.test_convert_model import TestConvertModel
|
||||
from openvino import convert_model
|
||||
from models_hub_common.utils import get_models_list
|
||||
|
||||
|
||||
def flattenize_tuples(list_input):
|
||||
unpacked_pt_res = []
|
||||
for r in list_input:
|
||||
if isinstance(r, (tuple, list)):
|
||||
unpacked_pt_res.extend(flattenize_tuples(r))
|
||||
else:
|
||||
unpacked_pt_res.append(r)
|
||||
return unpacked_pt_res
|
||||
|
||||
|
||||
def flattenize_outputs(outputs):
|
||||
if not isinstance(outputs, dict):
|
||||
outputs = flattenize_tuples(outputs)
|
||||
return [i.numpy(force=True) for i in outputs]
|
||||
else:
|
||||
return dict((k, v.numpy(force=True)) for k, v in outputs.items())
|
||||
|
||||
|
||||
# To make tests reproducible we seed the random generator
|
||||
torch.manual_seed(0)
|
||||
|
||||
|
||||
class TestTransformersModel(TestConvertModel):
|
||||
def setup_class(self):
|
||||
from PIL import Image
|
||||
import requests
|
||||
import os
|
||||
|
||||
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
|
||||
self.image = Image.open(requests.get(url, stream=True).raw)
|
||||
|
||||
self.cache_dir = tempfile.TemporaryDirectory()
|
||||
print(f"Setting temp cache dir: {str(self.cache_dir)}")
|
||||
os.environ["HUGGINGFACE_HUB_CACHE"] = str(self.cache_dir)
|
||||
|
||||
def load_model(self, name, type):
|
||||
mi = model_info(name)
|
||||
auto_processor = None
|
||||
model = None
|
||||
example = None
|
||||
try:
|
||||
auto_model = mi.transformersInfo['auto_model']
|
||||
if "processor" in mi.transformersInfo:
|
||||
auto_processor = mi.transformersInfo['processor']
|
||||
except:
|
||||
auto_model = None
|
||||
if "clip_vision_model" in mi.tags:
|
||||
from transformers import CLIPVisionModel, CLIPFeatureExtractor
|
||||
model = CLIPVisionModel.from_pretrained(name, torchscript=True)
|
||||
preprocessor = CLIPFeatureExtractor.from_pretrained(name)
|
||||
encoded_input = preprocessor(self.image, return_tensors='pt')
|
||||
example = dict(encoded_input)
|
||||
elif "t5" in mi.tags:
|
||||
from transformers import T5Tokenizer
|
||||
tokenizer = T5Tokenizer.from_pretrained(name)
|
||||
encoder = tokenizer(
|
||||
"Studies have been shown that owning a dog is good for you", return_tensors="pt")
|
||||
decoder = tokenizer("Studies show that", return_tensors="pt")
|
||||
example = (encoder.input_ids, encoder.attention_mask,
|
||||
decoder.input_ids, decoder.attention_mask)
|
||||
elif "hubert" in mi.tags:
|
||||
wav_input_16khz = torch.randn(1, 10000)
|
||||
example = (wav_input_16khz,)
|
||||
elif "vit-gpt2" in name:
|
||||
from transformers import VisionEncoderDecoderModel, ViTImageProcessor
|
||||
model = VisionEncoderDecoderModel.from_pretrained(
|
||||
name, torchscript=True)
|
||||
feature_extractor = ViTImageProcessor.from_pretrained(name)
|
||||
encoded_input = feature_extractor(
|
||||
images=[self.image], return_tensors="pt")
|
||||
|
||||
class VIT_GPT2_Model(torch.nn.Module):
|
||||
def __init__(self, model):
|
||||
super().__init__()
|
||||
self.model = model
|
||||
|
||||
def forward(self, x):
|
||||
return self.model.generate(x, max_length=16, num_beams=4)
|
||||
|
||||
model = VIT_GPT2_Model(model)
|
||||
example = (encoded_input.pixel_values,)
|
||||
elif "retribert" in mi.tags:
|
||||
from transformers import RetriBertTokenizer
|
||||
text = "How many cats are there?"
|
||||
tokenizer = RetriBertTokenizer.from_pretrained(name)
|
||||
encoding1 = tokenizer(
|
||||
"How many cats are there?", return_tensors="pt")
|
||||
encoding2 = tokenizer("Second text", return_tensors="pt")
|
||||
example = (encoding1.input_ids, encoding1.attention_mask,
|
||||
encoding2.input_ids, encoding2.attention_mask)
|
||||
elif "mgp-str" in mi.tags or "clip_vision_model" in mi.tags:
|
||||
from transformers import AutoProcessor
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
encoded_input = processor(images=self.image, return_tensors="pt")
|
||||
example = (encoded_input.pixel_values,)
|
||||
elif "vivit" in mi.tags:
|
||||
from transformers import VivitImageProcessor
|
||||
frames = list(torch.randint(
|
||||
0, 255, [32, 3, 224, 224]).to(torch.float32))
|
||||
processor = VivitImageProcessor.from_pretrained(name)
|
||||
encoded_input = processor(images=frames, return_tensors="pt")
|
||||
example = (encoded_input.pixel_values,)
|
||||
elif "tvlt" in mi.tags:
|
||||
from transformers import AutoProcessor
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
num_frames = 8
|
||||
images = list(torch.rand(num_frames, 3, 224, 224))
|
||||
audio = list(torch.randn(10000))
|
||||
input_dict = processor(
|
||||
images, audio, sampling_rate=44100, return_tensors="pt")
|
||||
example = dict(input_dict)
|
||||
elif "xmod" in mi.tags:
|
||||
from transformers import AutoTokenizer, AutoModel
|
||||
processor = AutoTokenizer.from_pretrained(name)
|
||||
text = "Replace me by any text you'd like."
|
||||
encoded_input = processor(text=[text], return_tensors="pt")
|
||||
model = AutoModel.from_pretrained(name, torchscript=True)
|
||||
model.set_default_language("de_CH")
|
||||
example = dict(encoded_input)
|
||||
elif "gptsan-japanese" in mi.tags:
|
||||
from transformers import AutoTokenizer
|
||||
processor = AutoTokenizer.from_pretrained(name)
|
||||
text = "織田信長は、"
|
||||
encoded_input = processor(text=[text], return_tensors="pt")
|
||||
example = dict(input_ids=encoded_input.input_ids,
|
||||
token_type_ids=encoded_input.token_type_ids)
|
||||
elif "videomae" in mi.tags or "timesformer" in mi.tags:
|
||||
from transformers import AutoProcessor
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
video = list(torch.randint(
|
||||
0, 255, [16, 3, 224, 224]).to(torch.float32))
|
||||
inputs = processor(video, return_tensors="pt")
|
||||
example = dict(inputs)
|
||||
else:
|
||||
if auto_model == "AutoModelForCausalLM":
|
||||
from transformers import AutoTokenizer, AutoModelForCausalLM
|
||||
tokenizer = AutoTokenizer.from_pretrained(name)
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
name, torchscript=True)
|
||||
text = "Replace me by any text you'd like."
|
||||
encoded_input = tokenizer(text, return_tensors='pt')
|
||||
inputs_dict = dict(encoded_input)
|
||||
if "facebook/incoder" in name and "token_type_ids" in inputs_dict:
|
||||
del inputs_dict["token_type_ids"]
|
||||
example = inputs_dict
|
||||
elif auto_model == "AutoModelForMaskedLM":
|
||||
from transformers import AutoTokenizer, AutoModelForMaskedLM
|
||||
tokenizer = AutoTokenizer.from_pretrained(name)
|
||||
model = AutoModelForMaskedLM.from_pretrained(
|
||||
name, torchscript=True)
|
||||
text = "Replace me by any text you'd like."
|
||||
encoded_input = tokenizer(text, return_tensors='pt')
|
||||
example = dict(encoded_input)
|
||||
elif auto_model == "AutoModelForImageClassification":
|
||||
from transformers import AutoProcessor, AutoModelForImageClassification
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
model = AutoModelForImageClassification.from_pretrained(
|
||||
name, torchscript=True)
|
||||
encoded_input = processor(
|
||||
images=self.image, return_tensors="pt")
|
||||
example = dict(encoded_input)
|
||||
elif auto_model == "AutoModelForSeq2SeqLM":
|
||||
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
|
||||
tokenizer = AutoTokenizer.from_pretrained(name)
|
||||
model = AutoModelForSeq2SeqLM.from_pretrained(
|
||||
name, torchscript=True)
|
||||
inputs = tokenizer(
|
||||
"Studies have been shown that owning a dog is good for you", return_tensors="pt")
|
||||
decoder_inputs = tokenizer(
|
||||
"<pad> Studien haben gezeigt dass es hilfreich ist einen Hund zu besitzen",
|
||||
return_tensors="pt",
|
||||
add_special_tokens=False,
|
||||
)
|
||||
example = dict(input_ids=inputs.input_ids,
|
||||
decoder_input_ids=decoder_inputs.input_ids)
|
||||
elif auto_model == "AutoModelForSpeechSeq2Seq":
|
||||
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
|
||||
from datasets import load_dataset
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
model = AutoModelForSpeechSeq2Seq.from_pretrained(
|
||||
name, torchscript=True)
|
||||
dataset = load_dataset(
|
||||
"hf-internal-testing/librispeech_asr_demo", "clean", split="validation")
|
||||
dataset = dataset.sort("id")
|
||||
sampling_rate = dataset.features["audio"].sampling_rate
|
||||
inputs = processor(
|
||||
dataset[0]["audio"]["array"], sampling_rate=sampling_rate, return_tensors="pt")
|
||||
example = dict(inputs)
|
||||
elif auto_model == "AutoModelForCTC":
|
||||
from transformers import AutoProcessor, AutoModelForCTC
|
||||
from datasets import load_dataset
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
model = AutoModelForCTC.from_pretrained(
|
||||
name, torchscript=True)
|
||||
ds = load_dataset(
|
||||
"patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
|
||||
input_values = processor(
|
||||
ds[0]["audio"]["array"], return_tensors="pt")
|
||||
example = dict(input_values)
|
||||
elif auto_model == "AutoModelForTableQuestionAnswering":
|
||||
import pandas as pd
|
||||
from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering
|
||||
tokenizer = AutoTokenizer.from_pretrained(name)
|
||||
model = AutoModelForTableQuestionAnswering.from_pretrained(
|
||||
name, torchscript=True)
|
||||
data = {"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"],
|
||||
"Number of movies": ["87", "53", "69"]}
|
||||
queries = ["What is the name of the first actor?",
|
||||
"How many movies has George Clooney played in?",
|
||||
"What is the total number of movies?",]
|
||||
answer_coordinates = [[(0, 0)], [(2, 1)], [
|
||||
(0, 1), (1, 1), (2, 1)]]
|
||||
answer_text = [["Brad Pitt"], ["69"], ["209"]]
|
||||
table = pd.DataFrame.from_dict(data)
|
||||
encoded_input = tokenizer(table=table, queries=queries, answer_coordinates=answer_coordinates,
|
||||
answer_text=answer_text, padding="max_length", return_tensors="pt",)
|
||||
example = dict(encoded_input)
|
||||
else:
|
||||
from transformers import AutoTokenizer, AutoProcessor
|
||||
text = "Replace me by any text you'd like."
|
||||
if auto_processor is not None and "Tokenizer" not in auto_processor:
|
||||
processor = AutoProcessor.from_pretrained(name)
|
||||
encoded_input = processor(
|
||||
text=[text], images=self.image, return_tensors="pt", padding=True)
|
||||
else:
|
||||
tokenizer = AutoTokenizer.from_pretrained(name)
|
||||
encoded_input = tokenizer(text, return_tensors='pt')
|
||||
example = dict(encoded_input)
|
||||
if model is None:
|
||||
from transformers import AutoModel
|
||||
model = AutoModel.from_pretrained(name, torchscript=True)
|
||||
self.example = example
|
||||
return model
|
||||
|
||||
def get_inputs_info(self, model_obj):
|
||||
return None
|
||||
|
||||
def prepare_inputs(self, inputs_info):
|
||||
if isinstance(self.example, dict):
|
||||
return dict((k, v.numpy()) for k, v in self.example.items())
|
||||
else:
|
||||
return [i.numpy() for i in self.example]
|
||||
|
||||
def convert_model(self, model_obj):
|
||||
ov_model = convert_model(model_obj, example_input=self.example)
|
||||
return ov_model
|
||||
|
||||
def infer_fw_model(self, model_obj, inputs):
|
||||
if isinstance(inputs, dict):
|
||||
inps = dict((k, torch.from_numpy(v)) for k, v in inputs.items())
|
||||
fw_outputs = model_obj(**inps)
|
||||
else:
|
||||
fw_outputs = model_obj(*[torch.from_numpy(i) for i in inputs])
|
||||
return flattenize_outputs(fw_outputs)
|
||||
|
||||
def teardown_method(self):
|
||||
# cleanup tmpdir
|
||||
print(f"Cleaning temp cache dir: {str(self.cache_dir)}")
|
||||
self.cache_dir.cleanup()
|
||||
super().teardown_method()
|
||||
|
||||
@pytest.mark.parametrize("name,type", [("bert-base-uncased", "bert"),
|
||||
("facebook/bart-large-mnli", "bart"),
|
||||
("gpt2", "gpt2"),
|
||||
("openai/clip-vit-large-patch14", "clip")])
|
||||
@pytest.mark.precommit
|
||||
def test_convert_model_precommit(self, name, type, ie_device):
|
||||
self.run(model_name=name, model_link=type, ie_device=ie_device)
|
||||
|
||||
@pytest.mark.parametrize("name",
|
||||
[pytest.param(n, marks=pytest.mark.xfail(reason=r) if m == "xfail" else pytest.mark.skip(reason=r)) if m else n for n, _, m, r in get_models_list(os.path.join(os.path.dirname(__file__), "hf_transformers_models"))])
|
||||
@pytest.mark.nightly
|
||||
def test_convert_model_all_models(self, name, ie_device):
|
||||
self.run(model_name=name, model_link=None, ie_device=ie_device)
|
||||
Reference in new issue
Block a user