update ACT configs (#1653)

* set onnx_format: True

* set onnx_format: True

* update qat_dis.yaml

* update configs

* Update prune_dis.yaml

* Update qat_dis.yaml

* Update README.md

example/auto_compression/image_classification/README.md

@@ -44,7 +44,7 @@
 | 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 | 74.04 | - | 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) |
+| MobileNetV3_large_x1_0_ssld | 量化+蒸馏 | 77.17 | - | 9.85 | [Config](./configs/MobileNetV3_large_x1_0_ssld/qat_dis.yaml) | [Model](https://paddle-slim-models.bj.bcebos.com/act/MobileNetV3_large_x1_0_ssld_QAT.tar) |
 | ViT_base_patch16_224 | Baseline | 81.89 | 367.17(batch_size=40) | - | - | [Model](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ViT_base_patch16_224_infer.tar) |
 | ViT_base_patch16_224 | 量化+蒸馏 | 82.05 | 51.70(batch_size=40) | - | [Config](./configs/VIT/qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ViT_base_patch16_224_QAT.tar) |
 

example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0/qat_dis.yaml

 Global:
-  model_dir: MobileNetV3_large_x1_0_ssld_infer
+  model_dir: MobileNetV3_large_x1_0_infer
   model_filename: inference.pdmodel
   params_filename: inference.pdiparams
   batch_size: 128

example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0_ssld/prune_dis.yaml

+Global:
+  model_dir: MobileNetV3_large_x1_0_ssld_infer
+  model_filename: inference.pdmodel
+  params_filename: inference.pdiparams
+  batch_size: 32
+  data_dir: ./ILSVRC2012
+
+Distillation:
+  alpha: 1.0
+  loss: l2
+  node:
+  - softmax_0.tmp_0
+UnstructurePrune:
+  prune_strategy: gmp
+  prune_mode: ratio
+  ratio: 0.75
+  gmp_config: 
+    stable_iterations: 0
+    pruning_iterations: 4500
+    tunning_iterations: 4500
+    resume_iteration: -1
+    pruning_steps: 100
+    initial_ratio: 0.15
+  prune_params_type: conv1x1_only
+  local_sparsity: True
+TrainConfig:
+  epochs: 1
+  eval_iter: 500
+  learning_rate: 
+    type: CosineAnnealingDecay 
+    learning_rate: 0.015
+  optimizer_builder:
+    optimizer:
+      type: Momentum
+    weight_decay: 0.00002
+  origin_metric: 0.7532

example/auto_compression/image_classification/configs/MobileNetV3_large_x1_0_ssld/qat_dis.yaml

+Global:
+  model_dir: MobileNetV3_large_x1_0_ssld_infer
+  model_filename: inference.pdmodel
+  params_filename: inference.pdiparams
+  batch_size: 128
+  data_dir: ./ILSVRC2012
+
+Distillation:
+  alpha: 1.0
+  loss: soft_label
+
+QuantAware:
+  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:
+  - skip_quant
+  quantize_op_types:
+  - conv2d
+  - depthwise_conv2d
+  - matmul
+  - matmul_v2
+  weight_bits: 8
+
+TrainConfig:
+  epochs: 2
+  eval_iter: 5000
+  learning_rate: 0.001
+  optimizer_builder:
+    optimizer:
+      type: Momentum
+    weight_decay: 0.00002
+  origin_metric: 0.7896