Skip to content

Commit 3d4e981

Browse files
hunkimhunkim
committed
Fixed missing feed_dict and ad .travis
1 parent 93cd9b2 commit 3d4e981

5 files changed

Lines changed: 117 additions & 88 deletions

File tree

‎.travis.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
# code below is taken from https://github.com/fchollet/keras/blob/master/.travis.yml
2+
sudo: required
3+
dist: trusty
4+
language: python
5+
python: # Only two versions for now
6+
- "2.7"
7+
- "3.5"
8+
# command to install dependencies
9+
# command to install dependencies
10+
install: "pip install -r requirements.txt"
11+
12+
script:
13+
- sed -i -- 's/range(100)/range(1)/g' ??_*.py # change range to 1 for quick testing
14+
- python lab-07-2-learning_rate_and_evaluation.py # run this first to download the MNIST file
15+
# run all python files in parallel, http://stackoverflow.com/questions/5015316
16+
- ls ??_*.py|xargs -n 1 -P 3 python

‎README.md‎

Lines changed: 13 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -9,12 +9,17 @@ However, we call for your comments and pull requests. Check out our style guide
99
* More Pythonic: fully leverage the powe of python
1010
* Readability (over efficiency): Since it's for instruction purposes, we prefer *readability* over others.
1111
* Understandability (over everything): Understanding TF key concepts is the main goal of this code.
12+
* KISS: Keep It Simple Stupid!
1213

1314
## File naming rule:
1415

1516
* klab-XX-X-[name].py: Keras labs code
1617
* lab-XX-X-[name].py: TensorFlow lab code
1718

19+
## Install requirements
20+
```bash
21+
pip install -r requirements.txt
22+
```
1823

1924
## Run test and autopep8
2025
TODO: Need to add more test cases
@@ -26,3 +31,11 @@ python -m unittest discover -s tests;
2631
pip install autopep8 # if you haven't install
2732
autopep8 . --recursive --in-place --pep8-passes 2000 --verbose
2833
```
34+
## Automatically create requirements.txt
35+
36+
```bash
37+
pip install pipreqs
38+
39+
pipreqs /path/to/project
40+
```
41+
http://stackoverflow.com/questions/31684375

‎lab-11-0-cnn_basics.ipynb‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -282,7 +282,7 @@
282282
"language_info": {
283283
"codemirror_mode": {
284284
"name": "ipython",
285-
"version": 3
285+
"version": 3.0
286286
},
287287
"file_extension": ".py",
288288
"mimetype": "text/x-python",
@@ -293,5 +293,5 @@
293293
}
294294
},
295295
"nbformat": 4,
296-
"nbformat_minor": 2
297-
}
296+
"nbformat_minor": 0
297+
}

‎lab-11-2-mnist_deep_cnn.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -124,7 +124,7 @@
124124
correct_prediction = tf.equal(tf.argmax(hypothesis, 1), tf.argmax(Y, 1))
125125
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
126126
print('Accuracy:', sess.run(accuracy, feed_dict={
127-
X: mnist.test.images, Y: mnist.test.labels}))
127+
X: mnist.test.images, Y: mnist.test.labels, keep_prob: 1}))
128128

129129
# Get one and predict
130130
r = random.randint(0, mnist.test.num_examples - 1)

‎lab-12-0-rnn_basics.ipynb‎

Lines changed: 84 additions & 84 deletions
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
22
"cells": [
33
{
44
"cell_type": "code",
5-
"execution_count": 3,
5+
"execution_count": 1,
66
"metadata": {
77
"collapsed": true
88
},
@@ -22,7 +22,7 @@
2222
},
2323
{
2424
"cell_type": "code",
25-
"execution_count": 4,
25+
"execution_count": 2,
2626
"metadata": {
2727
"collapsed": false
2828
},
@@ -32,7 +32,7 @@
3232
"output_type": "stream",
3333
"text": [
3434
"5 5\n",
35-
"array([[[ 0.92823738, -0.92360902, 0.89258885, 0.99514693, -0.036708 ]]], dtype=float32)\n"
35+
"array([[[-0.04824175, -0.11266616, -0.59395987, 0.99640656, -0.66602409]]], dtype=float32)\n"
3636
]
3737
}
3838
],
@@ -52,7 +52,7 @@
5252
},
5353
{
5454
"cell_type": "code",
55-
"execution_count": 5,
55+
"execution_count": 3,
5656
"metadata": {
5757
"collapsed": false
5858
},
@@ -61,8 +61,8 @@
6161
"name": "stdout",
6262
"output_type": "stream",
6363
"text": [
64-
"array([[[ 0.5095908 , 0.73586476, 0.17925251, 0.35411239, -0.96497387],\n",
65-
" [-0.28526765, 0.97455138, 0.97645795, -0.60268986, -0.99961406]]], dtype=float32)\n"
64+
"array([[[-0.11753262, 0.82967931, 0.92287099, -0.94706255, 0.99342507],\n",
65+
" [-0.44019806, 0.9612658 , 0.98902148, -0.99947858, 0.9999997 ]]], dtype=float32)\n"
6666
]
6767
}
6868
],
@@ -80,7 +80,7 @@
8080
},
8181
{
8282
"cell_type": "code",
83-
"execution_count": 7,
83+
"execution_count": 4,
8484
"metadata": {
8585
"collapsed": false
8686
},
@@ -89,18 +89,18 @@
8989
"name": "stdout",
9090
"output_type": "stream",
9191
"text": [
92-
"array([[[ -1.51391983e-01, 8.77759010e-02, 7.22011039e-03,\n",
93-
" 3.41427065e-02, 1.61610141e-01],\n",
92+
"array([[[ -9.24924016e-02, 1.47779593e-02, 1.73619956e-01,\n",
93+
" -4.51426417e-01, -3.30132879e-02],\n",
9494
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
9595
" 0.00000000e+00, 0.00000000e+00]],\n",
9696
"\n",
97-
" [[ 3.34553033e-01, -3.43819201e-01, 1.82304037e-04,\n",
98-
" 1.33128243e-03, 6.40465990e-02],\n",
99-
" [ 7.24730372e-01, -5.43702006e-01, 1.41877981e-05,\n",
100-
" 2.95121019e-04, 3.15410048e-02]],\n",
97+
" [[ -2.11092457e-03, 1.20736848e-04, 3.24320495e-02,\n",
98+
" -7.11563170e-01, -1.55489382e-04],\n",
99+
" [ -1.72451473e-04, 1.67748312e-05, 1.05808750e-02,\n",
100+
" -9.04355943e-01, -1.40012504e-04]],\n",
101101
"\n",
102-
" [[ 6.80008650e-01, -4.49257314e-01, 6.61273702e-07,\n",
103-
" 1.35716846e-05, 1.15950974e-02],\n",
102+
" [[ -2.60747729e-05, 5.85509952e-07, 2.34753476e-03,\n",
103+
" -7.55022943e-01, -5.58087777e-07],\n",
104104
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
105105
" 0.00000000e+00, 0.00000000e+00]]], dtype=float32)\n"
106106
]
@@ -126,7 +126,7 @@
126126
},
127127
{
128128
"cell_type": "code",
129-
"execution_count": 8,
129+
"execution_count": 5,
130130
"metadata": {
131131
"collapsed": false
132132
},
@@ -135,20 +135,20 @@
135135
"name": "stdout",
136136
"output_type": "stream",
137137
"text": [
138-
"array([[[ 7.10822791e-02, 1.63086936e-01, 8.90568942e-02,\n",
139-
" -1.24750927e-01, 2.00498208e-01],\n",
140-
" [ 4.70112897e-02, 3.78391862e-01, 2.16491129e-02,\n",
141-
" -1.13115773e-01, 4.86367106e-01]],\n",
138+
"array([[[ 1.20581007e-02, 9.10249818e-03, -5.73653318e-02,\n",
139+
" -2.28022784e-01, 1.06247095e-02],\n",
140+
" [ 1.96108937e-01, 4.87912744e-02, -1.93600245e-02,\n",
141+
" -4.58395869e-01, -7.03926757e-02]],\n",
142142
"\n",
143-
" [[ 4.97021899e-03, 4.12906766e-01, 3.03682452e-03,\n",
144-
" -1.65634304e-02, 5.91667116e-01],\n",
145-
" [ 7.24130834e-04, 4.93083537e-01, 5.39101311e-04,\n",
146-
" -5.02394000e-03, 6.94591641e-01]],\n",
143+
" [[ 1.33064032e-01, 1.99696813e-02, -7.78979913e-04,\n",
144+
" -5.71957648e-01, -1.44965827e-01],\n",
145+
" [ 2.38348722e-01, 1.22230034e-02, -7.75410153e-05,\n",
146+
" -5.95831394e-01, -1.84057772e-01]],\n",
147147
"\n",
148-
" [[ 1.03420047e-04, 4.54885125e-01, 7.90608392e-05,\n",
149-
" -6.74612937e-04, 7.19891727e-01],\n",
150-
" [ 1.22139072e-05, 5.20960569e-01, 1.35747678e-05,\n",
151-
" -1.44462858e-04, 7.46716678e-01]]], dtype=float32)\n"
148+
" [[ 5.16901910e-02, 1.88314938e-03, -6.19996081e-06,\n",
149+
" -6.81139827e-01, -1.17535137e-01],\n",
150+
" [ 8.82856771e-02, 7.83236872e-04, -5.80701567e-07,\n",
151+
" -6.80091798e-01, -1.14115342e-01]]], dtype=float32)\n"
152152
]
153153
}
154154
],
@@ -175,7 +175,7 @@
175175
},
176176
{
177177
"cell_type": "code",
178-
"execution_count": 9,
178+
"execution_count": 6,
179179
"metadata": {
180180
"collapsed": false
181181
},
@@ -204,7 +204,7 @@
204204
},
205205
{
206206
"cell_type": "code",
207-
"execution_count": 10,
207+
"execution_count": 7,
208208
"metadata": {
209209
"collapsed": false
210210
},
@@ -214,15 +214,15 @@
214214
"output_type": "stream",
215215
"text": [
216216
"dynamic rnn: Tensor(\"MultiRNNCell/rnn/transpose:0\", shape=(2, 4, 5), dtype=float32)\n",
217-
"array([[[-0.00081725, -0.00386185, 0.00659794, -0.0023129 , 0.00170874],\n",
218-
" [ 0.00209906, -0.0158419 , 0.01976709, -0.00896045, 0.007729 ],\n",
219-
" [ 0.00951714, -0.03161216, 0.03275521, -0.01422561, 0.01544347],\n",
220-
" [ 0.01877232, -0.04602807, 0.04267565, -0.01718889, 0.02373555]],\n",
217+
"array([[[-0.00159773, -0.00278636, 0.00216246, 0.00038013, -0.00024984],\n",
218+
" [-0.00624782, -0.00809411, 0.00787236, 0.0043 , -0.00170721],\n",
219+
" [-0.01344065, -0.01426034, 0.01710082, 0.01179738, -0.00482255],\n",
220+
" [-0.02229064, -0.0205432 , 0.02860553, 0.02171124, -0.00901885]],\n",
221221
"\n",
222-
" [[ 0.00509292, -0.00707487, 0.00062936, -0.0039078 , 0.0031513 ],\n",
223-
" [ 0.01397658, -0.01832587, 0.00351024, -0.00880949, 0.00907965],\n",
224-
" [ 0.02361906, -0.02915494, 0.00721703, -0.01298102, 0.01674998],\n",
225-
" [ 0.03231562, -0.03762392, 0.0104991 , -0.01586265, 0.02497061]]], dtype=float32)\n"
222+
" [[-0.00217091, -0.00350074, 0.00534471, 0.00142277, -0.003283 ],\n",
223+
" [-0.0062384 , -0.00876253, 0.01459183, 0.00550701, -0.00811026],\n",
224+
" [-0.01145217, -0.01450423, 0.02608694, 0.01158843, -0.01365107],\n",
225+
" [-0.01722418, -0.02011818, 0.038624 , 0.01883249, -0.01951919]]], dtype=float32)\n"
226226
]
227227
}
228228
],
@@ -241,7 +241,7 @@
241241
},
242242
{
243243
"cell_type": "code",
244-
"execution_count": 11,
244+
"execution_count": 8,
245245
"metadata": {
246246
"collapsed": false
247247
},
@@ -251,21 +251,21 @@
251251
"output_type": "stream",
252252
"text": [
253253
"dynamic rnn: Tensor(\"dynamic_rnn/rnn/transpose:0\", shape=(2, 4, 5), dtype=float32)\n",
254-
"array([[[ 1.44729763e-01, 8.68124291e-02, 2.04916492e-01,\n",
255-
" 2.09573627e-01, -5.28967381e-02],\n",
254+
"array([[[ 1.55049935e-01, -8.28458890e-02, -1.36540994e-01,\n",
255+
" -2.43278760e-02, 1.60975546e-01],\n",
256256
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
257257
" 0.00000000e+00, 0.00000000e+00],\n",
258258
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
259259
" 0.00000000e+00, 0.00000000e+00],\n",
260260
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
261261
" 0.00000000e+00, 0.00000000e+00]],\n",
262262
"\n",
263-
" [[ 6.69837773e-01, 6.55202800e-03, 5.15428901e-01,\n",
264-
" 6.26000166e-01, 1.09414861e-03],\n",
265-
" [ 7.37198949e-01, 2.45613419e-03, 7.56947041e-01,\n",
266-
" 6.68402612e-01, 3.07928160e-04],\n",
267-
" [ 7.48316824e-01, 7.88202335e-04, 8.19158375e-01,\n",
268-
" 6.95138216e-01, 7.53321801e-05],\n",
263+
" [[ 6.44681007e-02, -4.09913715e-03, -4.74524111e-01,\n",
264+
" 2.25839461e-03, 5.23494780e-01],\n",
265+
" [ 1.16558671e-01, -1.04439410e-03, -7.71331191e-01,\n",
266+
" 8.13173072e-04, 8.47356856e-01],\n",
267+
" [ 1.55143157e-01, -2.68030766e-04, -9.02186215e-01,\n",
268+
" 3.48752073e-04, 9.62113023e-01],\n",
269269
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
270270
" 0.00000000e+00, 0.00000000e+00]]], dtype=float32)\n"
271271
]
@@ -283,7 +283,7 @@
283283
},
284284
{
285285
"cell_type": "code",
286-
"execution_count": 12,
286+
"execution_count": 9,
287287
"metadata": {
288288
"collapsed": false
289289
},
@@ -292,54 +292,54 @@
292292
"name": "stdout",
293293
"output_type": "stream",
294294
"text": [
295-
"( array([[[ -9.65677872e-02, 8.78366530e-02, -4.63173576e-02,\n",
296-
" 1.70627236e-01, -4.50006984e-02],\n",
297-
" [ -2.88367927e-01, -2.20536790e-03, -2.47096375e-01,\n",
298-
" 2.39439070e-01, -6.13145940e-02],\n",
295+
"( array([[[ 4.45090048e-02, -5.48573909e-03, 1.76832363e-01,\n",
296+
" -6.30143331e-03, 8.78377333e-02],\n",
297+
" [ -1.48050860e-01, -9.71930625e-04, 4.88166243e-01,\n",
298+
" 1.77669868e-01, 4.02208827e-02],\n",
299299
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
300300
" 0.00000000e+00, 0.00000000e+00],\n",
301301
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
302302
" 0.00000000e+00, 0.00000000e+00]],\n",
303303
"\n",
304-
" [[ -2.34570522e-02, -2.30789676e-01, -8.99251401e-02,\n",
305-
" 4.12213095e-02, -5.51276535e-05],\n",
306-
" [ -2.83833817e-02, -3.16335082e-01, -1.49197981e-01,\n",
307-
" 2.10800320e-02, -5.10345890e-05],\n",
308-
" [ -2.71350183e-02, -3.37247968e-01, -1.85490116e-01,\n",
309-
" 1.06039764e-02, -4.90470229e-05],\n",
304+
" [[ -1.47792948e-02, -1.10883569e-08, 5.36434472e-01,\n",
305+
" 1.19788200e-01, 2.63353104e-06],\n",
306+
" [ -8.44009034e-03, -1.02014619e-09, 8.31147254e-01,\n",
307+
" 1.08465023e-01, 1.45638040e-07],\n",
308+
" [ -3.89013323e-03, -1.10596886e-10, 9.46177483e-01,\n",
309+
" 7.38197416e-02, 7.62108421e-09],\n",
310310
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
311311
" 0.00000000e+00, 0.00000000e+00]]], dtype=float32),\n",
312-
" array([[[ 1.84126094e-01, -2.18982220e-01, 1.39720485e-01,\n",
313-
" 3.44079107e-01, -6.56911135e-02],\n",
314-
" [ 2.34281030e-02, -4.09570515e-01, 3.16434465e-02,\n",
315-
" 2.89640844e-01, -9.31795407e-03],\n",
312+
" array([[[ -3.23204733e-02, -4.90211964e-01, 2.18950495e-01,\n",
313+
" -3.21291387e-01, 1.23527162e-01],\n",
314+
" [ -5.38012991e-03, -5.11050522e-01, 1.21017464e-01,\n",
315+
" -2.43347496e-01, 1.47201996e-02],\n",
316316
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
317317
" 0.00000000e+00, 0.00000000e+00],\n",
318318
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
319319
" 0.00000000e+00, 0.00000000e+00]],\n",
320320
"\n",
321-
" [[ 9.89461478e-05, -9.68605280e-01, 1.78079389e-03,\n",
322-
" 9.17775705e-02, -1.23107475e-05],\n",
323-
" [ 1.38388314e-05, -9.52976823e-01, 4.37916460e-04,\n",
324-
" 4.84855957e-02, -1.01028343e-06],\n",
325-
" [ 1.65542781e-06, -7.56663740e-01, 8.35553292e-05,\n",
326-
" 2.30717342e-02, -7.84334802e-08],\n",
321+
" [[ 1.25866393e-06, -9.94447768e-01, 1.79808959e-02,\n",
322+
" -7.70908415e-01, -1.87044188e-05],\n",
323+
" [ 5.34545137e-08, -9.62274730e-01, 8.88943300e-03,\n",
324+
" -6.21487617e-01, -3.74239767e-06],\n",
325+
" [ -1.88121074e-09, -7.57771075e-01, 4.22352366e-03,\n",
326+
" -3.46370369e-01, -5.74246997e-07],\n",
327327
" [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
328328
" 0.00000000e+00, 0.00000000e+00]]], dtype=float32))\n",
329-
"( LSTMStateTuple(c=array([[ -3.84970158e-01, -3.97752970e-03, -4.83172476e-01,\n",
330-
" 1.04605925e+00, -1.07953459e-01],\n",
331-
" [ -2.73253117e-02, -4.81255978e-01, -3.63608897e-01,\n",
332-
" 1.01591361e+00, -5.55281949e-05]], dtype=float32), h=array([[ -2.88367927e-01, -2.20536790e-03, -2.47096375e-01,\n",
333-
" 2.39439070e-01, -6.13145940e-02],\n",
334-
" [ -2.71350183e-02, -3.37247968e-01, -1.85490116e-01,\n",
335-
" 1.06039764e-02, -4.90470229e-05]], dtype=float32)),\n",
336-
" LSTMStateTuple(c=array([[ 6.56227529e-01, -4.65519607e-01, 2.68523991e-01,\n",
337-
" 6.16178215e-01, -2.59547949e-01],\n",
338-
" [ 4.95457828e-01, -2.95244336e+00, 2.51722569e-03,\n",
339-
" 9.25346762e-02, -1.46322316e-02]], dtype=float32), h=array([[ 1.84126094e-01, -2.18982220e-01, 1.39720485e-01,\n",
340-
" 3.44079107e-01, -6.56911135e-02],\n",
341-
" [ 9.89461478e-05, -9.68605280e-01, 1.78079389e-03,\n",
342-
" 9.17775705e-02, -1.23107475e-05]], dtype=float32)))\n"
329+
"( LSTMStateTuple(c=array([[ -7.79454410e-01, -1.55422129e-02, 7.31548727e-01,\n",
330+
" 1.87914044e-01, 1.74398974e-01],\n",
331+
" [ -2.79949379e+00, -2.41239013e-05, 1.81525278e+00,\n",
332+
" 7.39543140e-02, 1.22194501e-06]], dtype=float32), h=array([[ -1.48050860e-01, -9.71930625e-04, 4.88166243e-01,\n",
333+
" 1.77669868e-01, 4.02208827e-02],\n",
334+
" [ -3.89013323e-03, -1.10596886e-10, 9.46177483e-01,\n",
335+
" 7.38197416e-02, 7.62108421e-09]], dtype=float32)),\n",
336+
" LSTMStateTuple(c=array([[ -7.40298331e-02, -8.43536377e-01, 8.64924848e-01,\n",
337+
" -5.29330730e-01, 2.28457481e-01],\n",
338+
" [ 7.39789248e-05, -2.94868517e+00, 1.64265728e+00,\n",
339+
" -1.14800954e+00, -2.38284156e-05]], dtype=float32), h=array([[ -3.23204733e-02, -4.90211964e-01, 2.18950495e-01,\n",
340+
" -3.21291387e-01, 1.23527162e-01],\n",
341+
" [ 1.25866393e-06, -9.94447768e-01, 1.79808959e-02,\n",
342+
" -7.70908415e-01, -1.87044188e-05]], dtype=float32)))\n"
343343
]
344344
}
345345
],
@@ -462,7 +462,7 @@
462462
"language_info": {
463463
"codemirror_mode": {
464464
"name": "ipython",
465-
"version": 3
465+
"version": 3.0
466466
},
467467
"file_extension": ".py",
468468
"mimetype": "text/x-python",
@@ -474,4 +474,4 @@
474474
},
475475
"nbformat": 4,
476476
"nbformat_minor": 0
477-
}
477+
}

0 commit comments

Comments
 (0)