From d3046d1131d36113eebaa959ba1567b64feab115 Mon Sep 17 00:00:00 2001
From: c <lianghongkey@gmail.com>
Date: Thu, 2 Jan 2020 15:51:24 +0800
Subject: [PATCH] fix as 4 kernels in first layer.

---
 FilterEvaluator/EvaluatorUnsuper.py           |   2 +-
 FilterEvaluator/TrainNetwork.py               |   4 ++--
 FilterEvaluator/bestweightEntropySearch.npy   | Bin 272 -> 272 bytes
 ...tweightEntropySearch_entropy=-3.975601.npy | Bin 0 -> 272 bytes
 FilterEvaluator/checkpointEntropySearch.pkl   | Bin 1548 -> 1548 bytes
 5 files changed, 3 insertions(+), 3 deletions(-)
 create mode 100644 FilterEvaluator/bestweightEntropySearch_entropy=-3.975601.npy

diff --git a/FilterEvaluator/EvaluatorUnsuper.py b/FilterEvaluator/EvaluatorUnsuper.py
index 62669d5..3283e52 100644
--- a/FilterEvaluator/EvaluatorUnsuper.py
+++ b/FilterEvaluator/EvaluatorUnsuper.py
@@ -232,7 +232,7 @@ def UnsuperLearnSearchBestWeight(netmodel, layer, dataloader, databatchs=128, st
             if hasdata > 0:
                 entropys = []
                 for i in range(len(indexs)):
-                    histced = bitted[:,i].histc(256,0,255).type(torch.float32)
+                    histced = bitted[:,i].histc(15,0,15).type(torch.float32)
                     histced = histced[histced>0]
                     histced = histced/histced.sum()
                     entropy = (histced.log2()*histced).sum()
diff --git a/FilterEvaluator/TrainNetwork.py b/FilterEvaluator/TrainNetwork.py
index d4b51f9..fc0c5bf 100644
--- a/FilterEvaluator/TrainNetwork.py
+++ b/FilterEvaluator/TrainNetwork.py
@@ -40,7 +40,7 @@ batchsize = 128
 
 
 # traindata, testdata = Loader.MNIST(batchsize, num_workers=4, trainsize=5000)
-traindata, testdata = Loader.MNIST(batchsize, resize=7, trainsize=50000)
+traindata, testdata = Loader.MNIST(batchsize, resize=7, trainsize=500)
 # traindata, testdata = Loader.RandomMnist(batchsize, num_workers=4, style="Vertical")
 # traindata, testdata = Loader.RandomMnist(batchsize, num_workers=4, style="Horizontal")
 # traindata, testdata = Loader.RandomMnist(batchsize, num_workers=4, style="VerticalOneLine")
@@ -97,7 +97,7 @@ Train.TrainEpochs(model,traindata,optimizer,testdata,3000,10,lineNoPre)
 # optimizer = optim.SGD(model.parameters(), lr=0.1)
 # Train.TrainEpochs(model,traindata,optimizer,testdata,3000,10,linePretrainSearch)
 
-model = utils.SetDevice(Model.Net3Grad33())
+model = utils.SetDevice(Model.Net333())
 model = utils.LoadModel(model, CurrentPath+"/checkpointEntropySearch.pkl")
 optimizer = optim.SGD(model.parameters(), lr=0.1)
 Train.TrainEpochs(model,traindata,optimizer,testdata,3000,10,linePreAllGrad)
diff --git a/FilterEvaluator/bestweightEntropySearch.npy b/FilterEvaluator/bestweightEntropySearch.npy
index 8bd7c5a242a11c34bfbfe957b104cc7ae4af9e24..cc471203af63154a8603d8372b6168e871df79bf 100644
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diff --git a/FilterEvaluator/bestweightEntropySearch_entropy=-3.975601.npy b/FilterEvaluator/bestweightEntropySearch_entropy=-3.975601.npy
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diff --git a/FilterEvaluator/checkpointEntropySearch.pkl b/FilterEvaluator/checkpointEntropySearch.pkl
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