From 079694db4a92279a4c21bfac1be7691cfbf47568 Mon Sep 17 00:00:00 2001 From: Chang Xu Date: Fri, 9 Sep 2022 09:58:33 +0800 Subject: [PATCH] Update Acc in ACT imagenet (#1416) --- example/auto_compression/image_classification/README.md | 8 ++++---- .../configs/EfficientNetB0/qat_dis.yaml | 3 +++ .../configs/MobileNetV3_large_x1_0/qat_dis.yaml | 3 +++ .../configs/PPHGNet_tiny/qat_dis.yaml | 3 +++ .../configs/PPLCNetV2_base/qat_dis.yaml | 3 +++ .../image_classification/configs/ResNet50_vd/qat_dis.yaml | 3 +++ 6 files changed, 19 insertions(+), 4 deletions(-) diff --git a/example/auto_compression/image_classification/README.md b/example/auto_compression/image_classification/README.md index 082da0f4..23a0e381 100644 --- a/example/auto_compression/image_classification/README.md +++ b/example/auto_compression/image_classification/README.md @@ -32,17 +32,17 @@ | SqueezeNet1_0 | Baseline | 59.60 | - | 35.98 | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/SqueezeNet1_0_infer.tar) | | SqueezeNet1_0 | 量化+蒸馏 | 59.45 | - | 16.96 | [Config](./configs/SqueezeNet1_0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/SqueezeNet1_0_QAT.tar) | | PPLCNetV2_base | Baseline | 76.86 | - | 36.50 | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNetV2_base_infer.tar) | -| PPLCNetV2_base | 量化+蒸馏 | 76.43 | - | 15.79 | [Config](./configs/PPLCNetV2_base/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/PPLCNetV2_base_QAT.tar) | +| PPLCNetV2_base | 量化+蒸馏 | 76.39 | - | 15.79 | [Config](./configs/PPLCNetV2_base/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/PPLCNetV2_base_QAT.tar) | | PPHGNet_tiny | Baseline | 79.59 | 2.82 | - | - |[Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_tiny_infer.tar) | -| PPHGNet_tiny | 量化+蒸馏 | 79.20 | 0.98 | - | [Config](./configs/PPHGNet_tiny/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/PPHGNet_tiny_QAT.tar) | +| PPHGNet_tiny | 量化+蒸馏 | 79.24 | 0.98 | - | [Config](./configs/PPHGNet_tiny/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/PPHGNet_tiny_QAT.tar) | | InceptionV3 | Baseline | 79.14 | 4.79 | - | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/InceptionV3_infer.tar) | | InceptionV3 | 量化+蒸馏 | 78.32 | 1.47 | - | [Config](./configs/InceptionV3/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/InceptionV3_QAT.tar) | | EfficientNetB0 | Baseline | 77.02 | 1.95 | - | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/EfficientNetB0_infer.tar) | -| EfficientNetB0 | 量化+蒸馏 | 75.39 | 1.44 | - | [Config](./configs/EfficientNetB0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/EfficientNetB0_QAT.tar) | +| EfficientNetB0 | 量化+蒸馏 | 75.27 | 1.44 | - | [Config](./configs/EfficientNetB0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/EfficientNetB0_QAT.tar) | | GhostNet_x1_0 | Baseline | 74.02 | 2.93 | - | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/GhostNet_x1_0_infer.tar) | | GhostNet_x1_0 | 量化+蒸馏 | 72.62 | 1.03 | - | [Config](./configs/GhostNet_x1_0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/GhostNet_x1_0_QAT.tar) | | MobileNetV3_large_x1_0 | Baseline | 75.32 | - | 16.62 | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileNetV3_large_x1_0_infer.tar) | -| MobileNetV3_large_x1_0 | 量化+蒸馏 | 74.41 | - | 9.85 | [Config](./configs/MobileNetV3_large_x1_0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/MobileNetV3_large_x1_0_QAT.tar) | +| MobileNetV3_large_x1_0 | 量化+蒸馏 | 74.04 | - | 9.85 | [Config](./configs/MobileNetV3_large_x1_0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/MobileNetV3_large_x1_0_QAT.tar) | | MobileNetV3_large_x1_0_ssld | Baseline | 78.96 | - | 16.62 | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileNetV3_large_x1_0_ssld_infer.tar) | | MobileNetV3_large_x1_0_ssld | 量化+蒸馏 | 77.17 | - | 9.85 | [Config](./configs/MobileNetV3_large_x1_0/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/MobileNetV3_large_x1_0_ssld_QAT.tar) | diff --git a/example/auto_compression/image_classification/configs/EfficientNetB0/qat_dis.yaml b/example/auto_compression/image_classification/configs/EfficientNetB0/qat_dis.yaml index a8f79643..c74e0321 100644 --- a/example/auto_compression/image_classification/configs/EfficientNetB0/qat_dis.yaml +++ b/example/auto_compression/image_classification/configs/EfficientNetB0/qat_dis.yaml @@ -11,10 +11,12 @@ Distillation: loss: l2 node: - softmax_1.tmp_0 + Quantization: use_pact: true activation_bits: 8 is_full_quantize: false + onnx_format: True activation_quantize_type: moving_average_abs_max weight_quantize_type: channel_wise_abs_max not_quant_pattern: @@ -23,6 +25,7 @@ Quantization: - conv2d - depthwise_conv2d weight_bits: 8 + TrainConfig: epochs: 1 eval_iter: 500 diff --git a/example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0/qat_dis.yaml b/example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0/qat_dis.yaml index e9344a56..f4780e0b 100644 --- a/example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0/qat_dis.yaml +++ b/example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0/qat_dis.yaml @@ -9,10 +9,12 @@ Global: Distillation: alpha: 1.0 loss: soft_label + Quantization: use_pact: true activation_bits: 8 is_full_quantize: false + onnx_format: True activation_quantize_type: moving_average_abs_max weight_quantize_type: channel_wise_abs_max not_quant_pattern: @@ -22,6 +24,7 @@ Quantization: - depthwise_conv2d - matmul weight_bits: 8 + TrainConfig: epochs: 2 eval_iter: 5000 diff --git a/example/auto_compression/image_classification/configs/PPHGNet_tiny/qat_dis.yaml b/example/auto_compression/image_classification/configs/PPHGNet_tiny/qat_dis.yaml index 85f568e9..fb1535e7 100644 --- a/example/auto_compression/image_classification/configs/PPHGNet_tiny/qat_dis.yaml +++ b/example/auto_compression/image_classification/configs/PPHGNet_tiny/qat_dis.yaml @@ -11,10 +11,12 @@ Distillation: loss: l2 node: - softmax_1.tmp_0 + Quantization: use_pact: true activation_bits: 8 is_full_quantize: false + onnx_format: True activation_quantize_type: moving_average_abs_max weight_quantize_type: channel_wise_abs_max not_quant_pattern: @@ -23,6 +25,7 @@ Quantization: - conv2d - depthwise_conv2d weight_bits: 8 + TrainConfig: epochs: 1 eval_iter: 500 diff --git a/example/auto_compression/image_classification/configs/PPLCNetV2_base/qat_dis.yaml b/example/auto_compression/image_classification/configs/PPLCNetV2_base/qat_dis.yaml index bed762c3..4be08fe3 100644 --- a/example/auto_compression/image_classification/configs/PPLCNetV2_base/qat_dis.yaml +++ b/example/auto_compression/image_classification/configs/PPLCNetV2_base/qat_dis.yaml @@ -11,10 +11,12 @@ Distillation: loss: l2 node: - softmax_1.tmp_0 + Quantization: use_pact: true activation_bits: 8 is_full_quantize: false + onnx_format: True activation_quantize_type: moving_average_abs_max weight_quantize_type: channel_wise_abs_max not_quant_pattern: @@ -23,6 +25,7 @@ Quantization: - conv2d - depthwise_conv2d weight_bits: 8 + TrainConfig: epochs: 1 eval_iter: 500 diff --git a/example/auto_compression/image_classification/configs/ResNet50_vd/qat_dis.yaml b/example/auto_compression/image_classification/configs/ResNet50_vd/qat_dis.yaml index f936cc40..4cc375ad 100644 --- a/example/auto_compression/image_classification/configs/ResNet50_vd/qat_dis.yaml +++ b/example/auto_compression/image_classification/configs/ResNet50_vd/qat_dis.yaml @@ -11,10 +11,12 @@ Distillation: loss: l2 node: - softmax_0.tmp_0 + Quantization: use_pact: true activation_bits: 8 is_full_quantize: false + onnx_format: True activation_quantize_type: moving_average_abs_max weight_quantize_type: channel_wise_abs_max not_quant_pattern: @@ -23,6 +25,7 @@ Quantization: - conv2d - depthwise_conv2d weight_bits: 8 + TrainConfig: epochs: 1 eval_iter: 500 -- GitLab