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* Add PaddleOCR Support * Add PaddleOCR Support * Add PaddleOCRv3 Support * Add PaddleOCRv3 Support * Update README.md * Update README.md * Update README.md * Update README.md * Add PaddleOCRv3 Support * Add PaddleOCRv3 Supports * Add PaddleOCRv3 Suport * Fix Rec diff * Remove useless functions * Remove useless comments * Add PaddleOCRv2 Support * Add PaddleOCRv3 & PaddleOCRv2 Support * remove useless parameters * Add utils of sorting det boxes * Fix code naming convention * Fix code naming convention * Fix code naming convention * Fix bug in the Classify process * Imporve OCR Readme * Fix diff in Cls model * Update Model Download Link in Readme * Fix diff in PPOCRv2 * Improve OCR readme * Imporve OCR readme * Improve OCR readme * Improve OCR readme * Imporve OCR readme * Improve OCR readme * Fix conflict * Add readme for OCRResult * Improve OCR readme * Add OCRResult readme * Improve OCR readme * Improve OCR readme * Add Model Quantization Demo * Fix Model Quantization Readme * Fix Model Quantization Readme * Add the function to do PTQ quantization * Improve quant tools readme * Improve quant tool readme * Improve quant tool readme * Add PaddleInference-GPU for OCR Rec model * Add QAT method to fastdeploy-quantization tool * Remove examples/slim for now * Move configs folder * Add Quantization Support for Classification Model * Imporve ways of importing preprocess * Upload YOLO Benchmark on readme * Upload YOLO Benchmark on readme * Upload YOLO Benchmark on readme * Improve Quantization configs and readme * Add support for multi-inputs model
48 lines
943 B
YAML
48 lines
943 B
YAML
Global:
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model_dir: ./ResNet50_vd_infer/
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format: 'paddle'
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model_filename: inference.pdmodel
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params_filename: inference.pdiparams
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image_path: ./ImageNet_val_640
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arch: ResNet50
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input_list: ['input']
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preprocess: cls_image_preprocess
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Distillation:
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alpha: 1.0
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loss: l2
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node:
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- softmax_0.tmp_0
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Quantization:
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use_pact: true
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activation_bits: 8
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is_full_quantize: false
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onnx_format: True
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activation_quantize_type: moving_average_abs_max
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weight_quantize_type: channel_wise_abs_max
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not_quant_pattern:
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- skip_quant
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quantize_op_types:
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- conv2d
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- depthwise_conv2d
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weight_bits: 8
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TrainConfig:
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train_iter: 5000
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learning_rate:
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type: CosineAnnealingDecay
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learning_rate: 0.015
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T_max: 8000
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optimizer_builder:
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optimizer:
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type: Momentum
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weight_decay: 0.00002
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origin_metric: 0.7912
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PTQ:
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calibration_method: 'avg' # option: avg, abs_max, hist, KL, mse
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skip_tensor_list: None
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