add fpgm pruning scripts for ResNet34, MobileNetV1, MobileNetV2 test=…

…develop (PaddlePaddle#240)

demo/prune/fpgm_mobilenetv1_f-50_train.sh

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+#!/bin/bash  
+export CUDA_VISIBLE_DEVICES=0,1
+export FLAGS_fraction_of_gpu_memory_to_use=0.98
+python train.py \
+    --model="MobileNet" \
+    --pretrained_model="/workspace/models/MobileNetV1_pretrained" \
+    --data="imagenet" \
+    --pruned_ratio=0.3125 \
+    --lr=0.1 \
+    --num_epochs=120 \
+    --test_period=10 \
+    --step_epochs 30 60 90\
+    --l2_decay=3e-5 \
+    --lr_strategy="piecewise_decay" \
+    --criterion="geometry_median" \
+    --model_path="./fpgm_mobilenetv1_models" \
+    2>&1 | tee fpgm_mobilenetv1_train.log

demo/prune/fpgm_mobilenetv2_f-50_train.sh

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+#!/bin/bash  
+export CUDA_VISIBLE_DEVICES=0,1
+export FLAGS_fraction_of_gpu_memory_to_use=0.98
+python train.py \
+    --model="MobileNetV2" \
+    --pretrained_model="/workspace/models/MobileNetV2_pretrained" \
+    --data="imagenet" \
+    --pruned_ratio=0.325 \
+    --lr=0.001 \
+    --num_epochs=90 \
+    --test_period=5 \
+    --step_epochs 30 60 80\
+    --l2_decay=1e-4 \
+    --lr_strategy="piecewise_decay" \
+    --criterion="geometry_median" \
+    --model_path="./fpgm_mobilenetv2_models" \
+    2>&1 | tee fpgm_mobilenetv2_train.log

demo/prune/fpgm_resnet34_f-42_train.sh

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+#!/bin/bash  
+export CUDA_VISIBLE_DEVICES=0,1,2,3
+export FLAGS_fraction_of_gpu_memory_to_use=0.98
+python train.py \
+    --model="ResNet34" \
+    --pretrained_model="/workspace/models/ResNet34_pretrained" \
+    --data="imagenet" \
+    --pruned_ratio=0.25 \
+    --lr_strategy="cosine_decay" \
+    --criterion="geometry_median" \
+    --model_path="./fpgm_resnet34_025_120_models" \
+    2>&1 | tee fpgm_resnet025_120_train.log

demo/prune/fpgm_resnet34_f-50_train.sh

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+#!/bin/bash  
+export CUDA_VISIBLE_DEVICES=0,1
+export FLAGS_fraction_of_gpu_memory_to_use=0.98
+python train.py \
+    --model="ResNet34" \
+    --pretrained_model="/workspace/models/ResNet34_pretrained" \
+    --data="imagenet" \
+    --pruned_ratio=0.3125 \
+    --lr=0.001 \
+    --num_epochs=70 \
+    --test_period=5 \
+    --step_epochs 30 60 \
+    --l2_decay=1e-4 \
+    --lr_strategy="piecewise_decay" \
+    --criterion="geometry_median" \
+    --model_path="./fpgm_resnet34_models" \
+    2>&1 | tee fpgm_resnet03_train.log