SOFTMAX 在 MNIST 数据集上的使用

lijin-THU · lijin-THU · commit 593c301d9948 · 2015-10-13T13:03:44.000+08:00
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diff --git a/.gitignore b/.gitignore
@@ -2,3 +2,4 @@
 /.ipynb_checkpoints/*
 *-checkpoint.ipynb
 *.pyc
+/*/mnist/*
diff --git a/09. theano/09.07 softmax on mnist.ipynb.REMOVED.git-id b/09. theano/09.07 softmax on mnist.ipynb.REMOVED.git-id
@@ -0,0 +1 @@
+e742f36bb55ffc69bcd84b3a7e8cb4d486a918a4
diff --git a/09. theano/download_mnist.py b/09. theano/download_mnist.py
@@ -0,0 +1,20 @@
+import os
+import os.path
+import urllib
+import gzip
+import shutil
+
+if not os.path.exists('mnist'):
+    os.mkdir('mnist')
+
+def download_and_gzip(name):
+    if not os.path.exists(name + '.gz'):
+        urllib.urlretrieve('http://yann.lecun.com/exdb/' + name + '.gz', name + '.gz')
+    if not os.path.exists(name):
+        with gzip.open(name + '.gz', 'rb') as f_in, open(name, 'wb') as f_out:
+            shutil.copyfileobj(f_in, f_out)
+            
+download_and_gzip('mnist/train-images-idx3-ubyte')
+download_and_gzip('mnist/train-labels-idx1-ubyte')
+download_and_gzip('mnist/t10k-images-idx3-ubyte')
+download_and_gzip('mnist/t10k-labels-idx1-ubyte')
diff --git a/09. theano/load.py b/09. theano/load.py
@@ -0,0 +1,48 @@
+import numpy as np
+import os
+
+datasets_dir = './'
+
+def one_hot(x,n):
+	if type(x) == list:
+		x = np.array(x)
+	x = x.flatten()
+	o_h = np.zeros((len(x),n))
+	o_h[np.arange(len(x)),x] = 1
+	return o_h
+
+def mnist(ntrain=60000,ntest=10000,onehot=True):
+	data_dir = os.path.join(datasets_dir,'mnist/')
+	fd = open(os.path.join(data_dir,'train-images-idx3-ubyte'))
+	loaded = np.fromfile(file=fd,dtype=np.uint8)
+	trX = loaded[16:].reshape((60000,28*28)).astype(float)
+
+	fd = open(os.path.join(data_dir,'train-labels-idx1-ubyte'))
+	loaded = np.fromfile(file=fd,dtype=np.uint8)
+	trY = loaded[8:].reshape((60000))
+
+	fd = open(os.path.join(data_dir,'t10k-images-idx3-ubyte'))
+	loaded = np.fromfile(file=fd,dtype=np.uint8)
+	teX = loaded[16:].reshape((10000,28*28)).astype(float)
+
+	fd = open(os.path.join(data_dir,'t10k-labels-idx1-ubyte'))
+	loaded = np.fromfile(file=fd,dtype=np.uint8)
+	teY = loaded[8:].reshape((10000))
+
+	trX = trX/255.
+	teX = teX/255.
+
+	trX = trX[:ntrain]
+	trY = trY[:ntrain]
+
+	teX = teX[:ntest]
+	teY = teY[:ntest]
+
+	if onehot:
+		trY = one_hot(trY, 10)
+		teY = one_hot(teY, 10)
+	else:
+		trY = np.asarray(trY)
+		teY = np.asarray(teY)
+
+	return trX,teX,trY,teY

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