In [1]:

    

import numpy as np


    

In [10]:

    

x = np.array([0,0,0,0,0,0,0,0,0])


    

In [11]:

    

x


    

    
Out[11]:





array([0, 0, 0, 0, 0, 0, 0, 0, 0])

In [14]:

    

idx = np.random.choice(x,5,replace = False)


    

In [16]:

    

idx


    

    
Out[16]:





array([0, 0, 0, 0, 0])

In [17]:

    

np.arange(len(x))


    

    
Out[17]:





array([0, 1, 2, 3, 4, 5, 6, 7, 8])

In [20]:

    

t = np.random.choice(np.arange(len(x)),5,replace = True)


    

In [21]:

    

t


    

    
Out[21]:





array([7, 3, 3, 2, 4])

In [22]:

    

x[t]


    

    
Out[22]:





array([0, 0, 0, 0, 0])

In [23]:

    

x = np.array([[1,1,1,1],[2,2,2,2],[3,3,3,3],[4,4,4,4]])


    

In [24]:

    

x


    

    
Out[24]:





array([[1, 1, 1, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3],
       [4, 4, 4, 4]])

In [25]:

    

t = np.random.choice(np.arange(len(x)),5,replace = True)


    

In [26]:

    

t


    

    
Out[26]:





array([3, 0, 3, 3, 2])

In [27]:

    

x[t,:]


    

    
Out[27]:





array([[4, 4, 4, 4],
       [1, 1, 1, 1],
       [4, 4, 4, 4],
       [4, 4, 4, 4],
       [3, 3, 3, 3]])

In [31]:

    

x[0,2] = 5


    

In [33]:

    

np.argmax(x,axis=0)


    

    
Out[33]:





array([3, 3, 0, 3], dtype=int64)

In [34]:

    

x


    

    
Out[34]:





array([[1, 1, 5, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3],
       [4, 4, 4, 4]])

In [1]:

    

import numpy as np


    

In [36]:

    

x = np.array([1,2,3,4,5,6])


    

In [37]:

    

np.exp(x)


    

    
Out[37]:





array([   2.71828183,    7.3890561 ,   20.08553692,   54.59815003,
        148.4131591 ,  403.42879349])

In [2]:

    

x = np.rand((5,5))


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-7f52e51b3f93> in <module>()
----> 1 x = np.rand((5,5))

AttributeError: 'module' object has no attribute 'rand'

In [6]:

    

np.random.randn(5,5)


    

    
Out[6]:





array([[-0.44848151,  0.96502332,  0.61610453,  0.35158466,  0.82428406],
       [-1.97643952, -0.75227204,  0.23570676, -0.68976733, -1.58864503],
       [-0.28514507, -1.14815048,  0.62006344,  0.2626151 , -1.85030856],
       [ 0.60290351, -1.88334705, -1.18899365,  1.16799447,  0.78233971],
       [ 0.7521398 , -0.15458736,  0.59434215,  1.8364121 , -1.70602337]])

In [9]:

    

X = np.random.randn(500,3073)


    

In [8]:

    

y = np.random.randn(500,1)


    

In [13]:

    

W = W = np.random.randn(3073, 10)


    

In [15]:

    

scores = X[1,:].dot(W)


    

In [18]:

    

scores = np.exp(scores)
# normalize
scores_sum = np.sum(scores)
scores = scores / scores_sum


    

In [19]:

    

scores.shape


    

    
Out[19]:





(10L,)

In [27]:

    

scores[2] #2=y[i]


    

    
Out[27]:





1.2099666370668609e-51

In [29]:

    

np.exp


    

    
Out[29]:





<ufunc 'exp'>

In [30]:

    

exp()


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-30-2a06c663e383> in <module>()
----> 1 exp()

NameError: name 'exp' is not defined

In [32]:

    

np.log(2)


    

    
Out[32]:





0.69314718055994529

In [34]:

    

range(0,5) ==


    

    
Out[34]:





[0, 1, 2, 3, 4]

In [35]:

    

np.zeros(5)


    

    
Out[35]:





array([ 0.,  0.,  0.,  0.,  0.])

In [38]:

    

(3==3)*1


    

    
Out[38]:





1

In [52]:

    

X = np.array([[0,1,2,3],[0,1,2,3],[0,1,2,3]])


    

In [55]:

    

scores = (X.T - np.max(X,axis=1)).T


    

In [48]:

    

scores = np.exp(scores)


    

In [57]:

    

sum_s = np.sum(scores,axis=1)


    

In [62]:

    

(scores.T / sum_s).T


    

    
Out[62]:





array([[ 0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.]])

In [70]:

    

scores


    

    
Out[70]:





array([[-3, -2, -1,  0],
       [-3, -2, -1,  0],
       [-3, -2, -1,  0]])

In [73]:

    

scores = (scores.T*1.0/sum_s).T


    

In [72]:

    

y = [2,3,0]


    

In [75]:

    

scores[range(len(scores)),y]


    

    
Out[75]:





array([ 0.16666667, -0.        ,  0.5       ])

In [76]:

    

scores


    

    
Out[76]:





array([[ 0.5       ,  0.33333333,  0.16666667, -0.        ],
       [ 0.5       ,  0.33333333,  0.16666667, -0.        ],
       [ 0.5       ,  0.33333333,  0.16666667, -0.        ]])

In [77]:

    

scores.shape


    

    
Out[77]:





(3L, 4L)

In [3]:

    

xrange(1e-7,1e-4,10)


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-f637cc6d3b94> in <module>()
----> 1 xrange(1e-7,1e-4,10)

TypeError: integer argument expected, got float

In [1]:

    

import numpy as np


    

In [10]:

    

np.arange(1e-7,1e-5,0.01)


    

    
Out[10]:





array([  1.00000000e-07])

In [27]:

    

np.linspace(1e-5,1e-7,10)


    

    
Out[27]:





array([  1.00000000e-05,   8.90000000e-06,   7.80000000e-06,
         6.70000000e-06,   5.60000000e-06,   4.50000000e-06,
         3.40000000e-06,   2.30000000e-06,   1.20000000e-06,
         1.00000000e-07])

In [2]:

    

x = np.array([[1,1,1,1],[2,2,2,2],[3,3,3,3]])


    

In [3]:

    

x


    

    
Out[3]:





array([[1, 1, 1, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3]])

In [4]:

    

x + np.array([1,1,1,1])


    

    
Out[4]:





array([[2, 2, 2, 2],
       [3, 3, 3, 3],
       [4, 4, 4, 4]])

In [5]:

    

f = lambda x: np.max(0,x)


    

In [12]:

    

x[0,0] = -5


    

In [13]:

    

np.maximum(x,0)


    

    
Out[13]:





array([[0, 1, 1, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3]])

In [17]:

    

x**2


    

    
Out[17]:





array([[25,  1,  1,  1],
       [ 4,  4,  4,  4],
       [ 9,  9,  9,  9]])

In [20]:

    

s = np.ones((5,4))


    

In [21]:

    

t = np.ones(5)


    

In [22]:

    

t


    

    
Out[22]:





array([ 1.,  1.,  1.,  1.,  1.])

In [25]:

    

s.T * t


    

    
Out[25]:





array([[ 1.,  1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.,  1.]])

In [28]:

    

s.shape


    

    
Out[28]:





(5L, 4L)

In [29]:

    

t.shape


    

    
Out[29]:





(5L,)

In [30]:

    

s*t


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-30-f93fe870a2c7> in <module>()
----> 1 s*t

ValueError: operands could not be broadcast together with shapes (5,4) (5,) 

In [32]:

    

s


    

    
Out[32]:





array([[ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.]])

In [33]:

    

t


    

    
Out[33]:





array([ 1.,  1.,  1.,  1.,  1.])

In [34]:

    

t.dot(s)


    

    
Out[34]:





array([ 5.,  5.,  5.,  5.])

In [ ]: