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@ -4,52 +4,52 @@ import numpy |
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import onnx |
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import onnxruntime |
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import os |
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from pathlib import Path |
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import warnings |
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import logging |
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import platform |
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import psutil |
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# full_models = AutoTransformers.supported_model_names() |
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# checked_models = AutoTransformers.supported_model_names(format='onnx') |
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# models = [x for x in full_models if x not in checked_models] |
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models = ['distilbert-base-cased'] |
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atol = 1e-3 |
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log_path = 'transformers_onnx.log' |
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warnings.filterwarnings('ignore') |
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logger = logging.getLogger('transformers_onnx') |
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logger.setLevel(logging.DEBUG) |
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') |
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fh = logging.FileHandler(log_path) |
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fh.setLevel(logging.DEBUG) |
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fh.setFormatter(formatter) |
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logger.addHandler(fh) |
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ch = logging.StreamHandler() |
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ch.setLevel(logging.ERROR) |
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ch.setFormatter(formatter) |
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logger.addHandler(ch) |
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log_path = './transformers_onnx.log' |
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logger = logging.getLogger() |
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if Path(log_path).exists: |
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handler = logging.FileHandler(log_path) |
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else: |
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handler = logging.StreamHandler() |
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logger.handlers.append(handler) |
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logging.basicConfig(filename=log_path, |
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filemode='a', |
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format='%(asctime)s, %(msecs)d %(name)s %(levelname)s %(message)s', |
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datefmt='%H:%M:%S', |
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level=logging.info) |
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logging.info("Test") |
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logger.debug(f'machine: {platform.platform()}-{platform.processor()}') |
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logger.debug(f'free/available/total mem: {round(psutil.virtual_memory().free / (1024.0 **3))}' |
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f'/{round(psutil.virtual_memory().available / (1024.0 **3))}' |
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f'/{round(psutil.virtual_memory().total / (1024.0 **3))} GB') |
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logger.debug(f'cpu: {psutil.cpu_count()}') |
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for name in models: |
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print(f'Model {name}:') |
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logger.info(f'***{name}***') |
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saved_name = name.replace('/', '-') |
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logging.info(f'\nConverting model {name} to {saved_name}:') |
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try: |
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op = AutoTransformers(model_name=name) |
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out1 = op('hello, world.') |
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logging.info('OP LOADED.') |
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logger.info('OP LOADED.') |
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except Exception as e: |
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logging.error(f'FAIL TO LOAD OP: {e}') |
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logger.error(f'FAIL TO LOAD OP: {e}') |
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continue |
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try: |
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op.save_model(format='onnx') |
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logging.info('ONNX SAVED.') |
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logger.info('ONNX SAVED.') |
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except Exception as e: |
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logging.info(f'FAIL TO SAVE ONNX: {e}') |
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logger.error(f'FAIL TO SAVE ONNX: {e}') |
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continue |
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try: |
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try: |
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@ -58,22 +58,22 @@ for name in models: |
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except Exception: |
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saved_onnx = onnx.load(f'saved/onnx/{saved_name}.onnx', load_external_data=False) |
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onnx.checker.check_model(saved_onnx) |
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logging.info('ONNX CHECKED.') |
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logger.info('ONNX CHECKED.') |
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except Exception as e: |
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logging.error(f'FAIL TO CHECK ONNX: {e}') |
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logger.error(f'FAIL TO CHECK ONNX: {e}') |
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continue |
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try: |
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sess = onnxruntime.InferenceSession(f'saved/onnx/{saved_name}.onnx', |
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providers=onnxruntime.get_available_providers()) |
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inputs = op.tokenizer('hello, world.', return_tensors='np') |
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out2 = sess.run(output_names=["last_hidden_state"], input_feed=dict(inputs)) |
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logging.info('ONNX WORKED.') |
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if numpy.allclose(out1, out2, atol=1e-3): |
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logging.info('Check accuracy: OK') |
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logger.info('ONNX WORKED.') |
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if numpy.allclose(out1, out2, atol=atol): |
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logger.info('Check accuracy: OK') |
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else: |
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logging.info('Check accuracy: atol is larger than 1e-3.') |
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logger.info(f'Check accuracy: atol is larger than {atol}.') |
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except Exception as e: |
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logging.error(f'FAIL TO RUN ONNX: {e}') |
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logger.error(f'FAIL TO RUN ONNX: {e}') |
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continue |
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print('Finished.') |
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