ORTSeq2SeqTrainer refactoring - Inference with ORTModel #359
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* Refactorization of ORTOptimizer * Refactorization of ORTModel * Adapt examples according to refactorization * Adapt tests * Fix style * Remove quantizer modification * Fix style * Apply modifications from #270 for quantizer and optimizer to have same behavior * Add test for optimization of Seq2Seq models * Fix style * Add ort config saving when optimizing a model * Add ort config saving when quantizing a model * Add tests * Fix style * Adapt optimization examples * Fix readme * Remove unused parameter * Adapt quantization examples * Fix quantized model and ort config saving * Add documentation * Add model configuration saving to simplify loading of optimized model * Fix style * Fix description * Fix quantization tests * Remove opset argument which is onnx config default opset when exporting with ORTModels
* fix(optimization): handle empty file suffix * fix(quantization): handle empty file suffix * use pathlibfor save_dir * run test again * Update optimum/onnxruntime/quantization.py Co-authored-by: Ella Charlaix <80481427+echarlaix@users.noreply.github.com> * ReRun test that failed because of cache (network) Co-authored-by: Ella Charlaix <80481427+echarlaix@users.noreply.github.com>
* fix class * Update optimization.mdx
JingyaHuang
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Sep 19, 2022
…189) * Inference with ORTModel * Clean up unused imports * Replace Inference session by ort model * Inference with ORTModel * Replace in evaluation_loop * refactoring prediction_loop * ORTSeq2SeqTrainer refactoring - Inference with ORTModel (#359) * Override export of ORTSeq2SeqTrainer * Update OnnxConfigWithLoss wrapper * Fix ORTTrainer inference ort subclass parsing * Override the evaluation and prediction loop in ORTSeq2SeqTrainer * detect labels from input names * Detect loss from output names * Put back decoder with past * Put past key values in the correct place * remove if/else statement * Revert the inference code
JingyaHuang
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Oct 2, 2022
* Inference with ORTModel * Clean up unused imports * Replace Inference session by ort model * Inference with ORTModel * Clean up unused imports * Replace Inference session by ort model * Update modeling for custom tasks * Replace in evaluation_loop * refectoring prediction_loop * ORTSeq2SeqTrainer refactoring - Inference with ORTModel (#359) * Override export of ORTSeq2SeqTrainer * Do not force download by default in ORTModel (#356) * Update OnnxConfigWithLoss wrapper * ORT optimizer refactorization (#294) * Refactorization of ORTOptimizer * Refactorization of ORTModel * Adapt examples according to refactorization * Fix ORTTrainer inference ort subclass parsing * Replace datasets.load_metric by evaluate * Add summarization example * Enable ORT inference * Fix inference args * Mention ORT inference in READMEs * Remove repetitve code in Trainer * Update examples to trfrs 4.22.1 * Fix qa example prediction error * Update summarization/README.md * Fix logger consistency * Make readme consistent with trfrs * Put back onnx config with past and loss test
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What does this PR do?
ORTSeq2SeqTrainerby leveraging subclasses ofORTModelfor sequence to sequence tasks.