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debugging APIs to run 1 vector at a time
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@charlesmartin14
charlesmartin14 committed Oct 31, 2016
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Showing 1 changed file with 66 additions and 95 deletions.
161 changes: 66 additions & 95 deletions EMF_RBM_Test.ipynb
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Expand Up @@ -1586,68 +1586,22 @@
"\n",
"(info statements added into monitor; I should find a way to add to test code )\n",
"\n",
"INFO: FE <1-5>[-90.41392263605844 -98.57232874119751 -96.67160538171822 -99.72457836849503 -89.84668949506056] \n",
"INFO: m vis, hid 11.117791807149395 8.936583879865992 \n",
"INFO: denoised m vis, hid 11.11779180715007 8.936583879865992 \n",
"INFO: S 68.78612279502707 \n",
"INFO: U -48.601136204614065 \n",
"INFO: O -3.049134288108069e-6 \n",
"INFO: FE TAP <1-5>[-117.38187025746029 -117.39051762052955 -117.39024519247155 -117.39408456128287 -117.37959261213285]\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T18:27:10.108836",
"start_time": "2016-10-30T18:27:10.106650"
}
},
"source": [
"### debugging"
]
},
{
"cell_type": "code",
"execution_count": 125,
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T19:14:09.276228",
"start_time": "2016-10-30T19:14:09.161870"
},
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"FE [-90.41430007 -98.57310576 -96.67241536 -99.72444618 -89.84836508]\n",
"FE tap mv, mh 210.70743088 169.423349905\n",
"denoised mv, mh 210.70743088 169.423349905\n",
"S 68.8462453122\n",
"U -48.5352968521\n",
"O -2.95284953624e-06\n",
"[-117.38220776 -117.3908557 -117.39058326 -117.39442185 -117.3799317 ]\n"
]
}
],
"source": [
"X = Xdigits.copy()\n",
"rbm = EMF_RBM(n_iter=1, n_components=64, decay=0.001, sigma=0.0000000000000001, neq_steps=5)\n",
"rbm.fit(X) \n",
"print \"FE \", rbm._free_energy(X)[0:5]\n",
"print \"FE tap\", rbm._free_energy_TAP(X)[0:5]"
"S [68.92548157440935,68.67917042062827,68.7382937888165,68.6467445638933,68.94092201361534] \n",
"FE <1-5>[-90.41392263605844 -98.57232874119751 -96.67160538171822 -99.72457836849503 -89.84668949506056] \n",
"FE TAP <1-5>[-117.38187025746029 -117.39051762052955 -117.39024519247155 -117.39408456128287 -117.37959261213285]\n",
"\n",
"\n",
"?? m vis, hid 11.117791807149395 8.936583879865992 \n",
"?? denoised m vis, hid 11.11779180715007 8.936583879865992 "
]
},
{
"cell_type": "code",
"execution_count": 128,
"execution_count": 130,
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T19:15:44.346987",
"start_time": "2016-10-30T19:15:44.232423"
"end_time": "2016-10-30T19:29:43.666350",
"start_time": "2016-10-30T19:29:43.512668"
},
"collapsed": false
},
Expand All @@ -1656,13 +1610,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"free energies, old [-90.41429534 -98.57310211 -96.67241201 -99.72444296 -89.84835955]\n",
"mv, mh 210.707426723 169.423341602\n",
"denoised mv, mh 210.707426723 169.423341602\n",
"S 68.8462459118\n",
"U -48.5352931731\n",
"O -2.9528800398e-06\n",
"TAP free energies [-117.38220468 -117.39085262 -117.39058018 -117.39441877 -117.37992862]\n"
"entropy [ 68.92500812 68.67868513 68.73780754 68.64628658 68.94040984]\n",
"free energies, old [-90.41429712 -98.57310481 -96.67241348 -99.72444489 -89.84836316]\n",
"mv, mh 210.707428877 169.423346805\n",
"denoised mv, mh 210.707428877 169.423346805\n",
"S 68.8462458135\n",
"U -48.5352952066\n",
"O -2.95285368833e-06\n",
"TAP free energies [-117.38220661 -117.39085455 -117.39058211 -117.3944207 -117.37993056]\n"
]
}
],
Expand All @@ -1671,13 +1626,19 @@
" X = Xdigits.copy()\n",
" rbm = EMF_RBM(n_iter=1, n_components=64, decay=0.001, sigma=0.0000000000000001, neq_steps=5)\n",
" rbm.fit(X) \n",
" \n",
" s = rbm._entropy(X)\n",
" print \"entropy \", s[0:5]\n",
" \n",
" fe = rbm._free_energy(X)\n",
" print \"free energies, old \" , fe[0:5]\n",
" \n",
" fe_tap = rbm._free_energy_TAP(X)\n",
" print \"TAP free energies \", fe_tap[0:5]\n",
" \n",
" assert_almost_equal(s[0], 68.92548, decimal=3)\n",
" assert_almost_equal(s[1], 68.679170, decimal=3) # a bit more off\n",
" \n",
" assert_almost_equal(fe[0], -90.4139, decimal=3)\n",
" assert_almost_equal(fe[1], -98.5723, decimal=2) # a bit more off\n",
" \n",
Expand All @@ -1703,83 +1664,93 @@
},
{
"cell_type": "code",
"execution_count": 113,
"execution_count": 137,
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T18:45:06.320502",
"start_time": "2016-10-30T18:45:06.315556"
"end_time": "2016-10-30T19:34:38.154506",
"start_time": "2016-10-30T19:34:38.009643"
},
"collapsed": false
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
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"text/plain": [
"EMF_RBM(batch_size=100, decay=0.001, learning_rate=0.005, momentum=0.5,\n",
" n_components=64, n_iter=1, neq_steps=3,\n",
" random_state=<mtrand.RandomState object at 0x10ba5f820>, sigma=1e-16,\n",
" thresh=1e-08, verbose=0, weight_decay='L1')"
"<matplotlib.figure.Figure at 0x11305f790>"
]
},
"execution_count": 113,
"metadata": {},
"output_type": "execute_result"
"output_type": "display_data"
}
],
"source": [
"rbm"
"v = X[0,:]\n",
"show_image(np.reshape(v,[8,8]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### TODO: fix APIs so they can run on 1 vector at a time"
]
},
{
"cell_type": "code",
"execution_count": 33,
"execution_count": 139,
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T18:01:05.504019",
"start_time": "2016-10-30T18:01:05.487406"
"end_time": "2016-10-30T19:34:54.719723",
"start_time": "2016-10-30T19:34:54.697803"
},
"collapsed": false,
"scrolled": true
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"mv, mh 4.9744512468 3.99674446312\n",
"denoised mv, mh 4.9744512468 3.99674446312\n"
]
},
{
"ename": "ValueError",
"evalue": "shapes (2,1) and (64,) not aligned: 1 (dim 1) != 64 (dim 0)",
"evalue": "'axis' entry is out of bounds",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-33-ae444b769d6b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msafe_sparse_dot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrbm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mv_bias\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/Users/charlesmartin14/anaconda/lib/python2.7/site-packages/sklearn/utils/extmath.pyc\u001b[0m in \u001b[0;36msafe_sparse_dot\u001b[0;34m(a, b, dense_output)\u001b[0m\n\u001b[1;32m 182\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 183\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 184\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfast_dot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 185\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: shapes (2,1) and (64,) not aligned: 1 (dim 1) != 64 (dim 0)"
"\u001b[0;32m<ipython-input-139-6f6eb4191f6d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrbm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_free_energy_TAP\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m<ipython-input-121-fb4089d53c4b>\u001b[0m in \u001b[0;36m_free_energy_TAP\u001b[0;34m(self, v)\u001b[0m\n\u001b[1;32m 424\u001b[0m U_naive = (-safe_sparse_dot(mv, self.v_bias) \n\u001b[1;32m 425\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0msafe_sparse_dot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mh_bias\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 426\u001b[0;31m -(mv.dot(self.W.T)*(mh)).sum(axis=1)) \n\u001b[0m\u001b[1;32m 427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 428\u001b[0m Entropy = ( -(mv*np.log(mv)+(1.0-mv)*np.log(1.0-mv)).sum(axis=1) \n",
"\u001b[0;32m/Users/charlesmartin14/anaconda/lib/python2.7/site-packages/numpy/core/_methods.pyc\u001b[0m in \u001b[0;36m_sum\u001b[0;34m(a, axis, dtype, out, keepdims)\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 31\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_sum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 32\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mumr_sum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 33\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_prod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: 'axis' entry is out of bounds"
]
}
],
"source": [
"safe_sparse_dot(X, rbm.v_bias)"
"rbm._free_energy_TAP(v)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"execution_count": 136,
"metadata": {
"ExecuteTime": {
"end_time": "2016-10-30T18:00:05.262830",
"start_time": "2016-10-30T18:00:05.246941"
"end_time": "2016-10-30T19:34:31.926864",
"start_time": "2016-10-30T19:34:31.922071"
},
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"ename": "ValueError",
"evalue": "shapes (1,) and (64,) not aligned: 1 (dim 0) != 64 (dim 0)",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-28-60fa5bcdab3c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrbm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mv_bias\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlogaddexp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrbm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mW\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mrbm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mh_bias\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mvv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mff\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvv\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mff\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: shapes (1,) and (64,) not aligned: 1 (dim 0) != 64 (dim 0)"
"name": "stdout",
"output_type": "stream",
"text": [
"46.0967018276 44.3172430764 90.413944904\n"
]
}
],
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