未验证 提交 aa336f5f 编写于 作者: G Guanghua Yu 提交者: GitHub

update act detection config (#1211)

上级 f8365ada
......@@ -8,13 +8,15 @@ Global:
params_filename: model.pdiparams
Distillation:
alpha: 1.0
loss: l2
node:
- concat_15.tmp_0
- concat_14.tmp_0
Quantization:
use_pact: true
activation_quantize_type: 'range_abs_max'
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
......@@ -22,7 +24,10 @@ Quantization:
TrainConfig:
train_iter: 3000
eval_iter: 1000
learning_rate: 0.00001
learning_rate:
type: CosineAnnealingDecay
learning_rate: 0.00003
T_max: 5000
optimizer_builder:
optimizer:
type: SGD
......
......@@ -23,7 +23,7 @@
| 模型 | 策略 | 输入尺寸 | mAP<sup>val<br>0.5:0.95 | 预测时延<sup><small>FP32</small><sup><br><sup>(ms) |预测时延<sup><small>FP16</small><sup><br><sup>(ms) | 预测时延<sup><small>INT8</small><sup><br><sup>(ms) | 配置文件 | Inference模型 |
| :-------- |:-------- |:--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: |
| YOLOv5s | Base模型 | 640*640 | 37.4 | 7.8ms | 4.3ms | - | - | [Model](https://bj.bcebos.com/v1/paddle-slim-models/detection/yolov5s_infer.tar) |
| YOLOv5s | 量化+蒸馏 | 640*640 | 36.5 | - | - | 3.4ms | [config](./configs/yolov5s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov5s_quant.tar) |
| YOLOv5s | 量化+蒸馏 | 640*640 | 36.8 | - | - | 3.4ms | [config](./configs/yolov5s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov5s_quant.tar) |
说明:
- mAP的指标均在COCO val2017数据集中评测得到。
......
......@@ -11,14 +11,10 @@ Global:
Distillation:
alpha: 1.0
loss: l2
node:
- conv2d_106.tmp_1
- conv2d_113.tmp_1
- conv2d_119.tmp_1
Quantization:
use_pact: true
activation_quantize_type: 'range_abs_max'
activation_quantize_type: 'moving_average_abs_max'
quantize_op_types:
- conv2d
- depthwise_conv2d
......
......@@ -766,6 +766,7 @@ class AutoCompression:
"Not set eval function, so unable to test accuracy performance."
)
if train_config.train_iter and total_train_iter >= train_config.train_iter:
epoch_id = total_epochs
break
if 'unstructure' in self._strategy or train_config.sparse_model:
......
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