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Fix format (#615)
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echarlaix authored Mar 19, 2024
1 parent 877cf9d commit 894334d
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Showing 3 changed files with 70 additions and 73 deletions.
4 changes: 2 additions & 2 deletions Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -22,11 +22,11 @@ REAL_CLONE_URL = $(if $(CLONE_URL),$(CLONE_URL),$(DEFAULT_CLONE_URL))
# Run code quality checks
style_check:
black --check .
ruff .
ruff check .

style:
black .
ruff . --fix
ruff check . --fix

# Run tests for the library
test:
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131 changes: 66 additions & 65 deletions examples/openvino/test_examples.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import unittest
from unittest.mock import patch


SRC_DIRS = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
Expand All @@ -29,39 +30,39 @@
sys.path.extend(SRC_DIRS)

if SRC_DIRS is not None:
import run_image_classification
import run_audio_classification
import run_glue
import run_image_classification
import run_qa


class TestExamples(unittest.TestCase):
def test_audio_classification(self):
with tempfile.TemporaryDirectory() as tmp_dir:
test_args = f"""
run_audio_classification.py
--model_name_or_path hf-internal-testing/tiny-random-Wav2Vec2Model
--nncf_compression_config examples/openvino/audio-classification/configs/wav2vec2-base-qat.json
--dataset_name superb
--dataset_config_name ks
--max_train_samples 10
--max_eval_samples 2
--remove_unused_columns False
--do_train
--learning_rate 3e-5
--max_length_seconds 1
--attention_mask False
--warmup_ratio 0.1
--num_train_epochs 1
--gradient_accumulation_steps 1
--dataloader_num_workers 1
--logging_strategy steps
--logging_steps 1
--evaluation_strategy epoch
--save_strategy epoch
--load_best_model_at_end False
run_audio_classification.py
--model_name_or_path hf-internal-testing/tiny-random-Wav2Vec2Model
--nncf_compression_config examples/openvino/audio-classification/configs/wav2vec2-base-qat.json
--dataset_name superb
--dataset_config_name ks
--max_train_samples 10
--max_eval_samples 2
--remove_unused_columns False
--do_train
--learning_rate 3e-5
--max_length_seconds 1
--attention_mask False
--warmup_ratio 0.1
--num_train_epochs 1
--gradient_accumulation_steps 1
--dataloader_num_workers 1
--logging_strategy steps
--logging_steps 1
--evaluation_strategy epoch
--save_strategy epoch
--load_best_model_at_end False
--seed 42
--output_dir {tmp_dir}
--output_dir {tmp_dir}
--overwrite_output_dir
""".split()

Expand All @@ -71,21 +72,21 @@ def test_audio_classification(self):
def test_image_classification(self):
with tempfile.TemporaryDirectory() as tmp_dir:
test_args = f"""
run_image_classification.py
--model_name_or_path nateraw/vit-base-beans
--dataset_name beans
--max_train_samples 10
--max_eval_samples 2
--remove_unused_columns False
run_image_classification.py
--model_name_or_path nateraw/vit-base-beans
--dataset_name beans
--max_train_samples 10
--max_eval_samples 2
--remove_unused_columns False
--do_train
--do_eval
--learning_rate 2e-5
--num_train_epochs 1
--logging_strategy steps
--logging_steps 1
--evaluation_strategy epoch
--save_strategy epoch
--save_total_limit 1
--do_eval
--learning_rate 2e-5
--num_train_epochs 1
--logging_strategy steps
--logging_steps 1
--evaluation_strategy epoch
--save_strategy epoch
--save_total_limit 1
--seed 1337
--output_dir {tmp_dir}
""".split()
Expand All @@ -95,23 +96,23 @@ def test_image_classification(self):

def test_text_classification(self):
with tempfile.TemporaryDirectory() as tmp_dir:
test_args = f"""
run_glue.py
--model_name_or_path hf-internal-testing/tiny-random-DistilBertForSequenceClassification
--task_name sst2
--max_train_samples 10
--max_eval_samples 2
--overwrite_output_dir
test_args = f"""
run_glue.py
--model_name_or_path hf-internal-testing/tiny-random-DistilBertForSequenceClassification
--task_name sst2
--max_train_samples 10
--max_eval_samples 2
--overwrite_output_dir
--do_train
--do_eval
--max_seq_length 128
--learning_rate 1e-5
--optim adamw_torch
--num_train_epochs 1
--logging_steps 1
--evaluation_strategy steps
--eval_steps 1
--save_strategy epoch
--do_eval
--max_seq_length 128
--learning_rate 1e-5
--optim adamw_torch
--num_train_epochs 1
--logging_steps 1
--evaluation_strategy steps
--eval_steps 1
--save_strategy epoch
--seed 42
--output_dir {tmp_dir}
""".split()
Expand All @@ -122,17 +123,17 @@ def test_text_classification(self):
def test_question_answering(self):
with tempfile.TemporaryDirectory() as tmp_dir:
test_args = f"""
run_qa.py
--model_name_or_path hf-internal-testing/tiny-random-DistilBertForQuestionAnswering
--dataset_name squad
--do_train
--do_eval
--max_train_samples 10
--max_eval_samples 2
--learning_rate 3e-5
--num_train_epochs 1
--max_seq_length 384
--doc_stride 128
run_qa.py
--model_name_or_path hf-internal-testing/tiny-random-DistilBertForQuestionAnswering
--dataset_name squad
--do_train
--do_eval
--max_train_samples 10
--max_eval_samples 2
--learning_rate 3e-5
--num_train_epochs 1
--max_seq_length 384
--doc_stride 128
--overwrite_output_dir
--output_dir {tmp_dir}
""".split()
Expand All @@ -142,4 +143,4 @@ def test_question_answering(self):


if __name__ == "__main__":
unittest.main()
unittest.main()
8 changes: 2 additions & 6 deletions notebooks/openvino/stable_diffusion_optimization.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -69,9 +69,7 @@
"metadata": {},
"outputs": [],
"source": [
"quantized_pipe = OVStableDiffusionPipeline.from_pretrained(\n",
" \"OpenVINO/Stable-Diffusion-Pokemon-en-quantized\", compile=False\n",
")\n",
"quantized_pipe = OVStableDiffusionPipeline.from_pretrained(\"OpenVINO/Stable-Diffusion-Pokemon-en-quantized\", compile=False)\n",
"quantized_pipe.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)\n",
"quantized_pipe.compile()"
]
Expand Down Expand Up @@ -104,9 +102,7 @@
"metadata": {},
"outputs": [],
"source": [
"optimized_pipe = OVStableDiffusionPipeline.from_pretrained(\n",
" \"OpenVINO/stable-diffusion-pokemons-tome-quantized\", compile=False\n",
")\n",
"optimized_pipe = OVStableDiffusionPipeline.from_pretrained(\"OpenVINO/stable-diffusion-pokemons-tome-quantized\", compile=False)\n",
"optimized_pipe.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)\n",
"optimized_pipe.compile()"
]
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