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Morten Hjorth-Jensen
2024-09-11 05:31:05 +02:00
parent cfc54d407a
commit e192ace15c
12 changed files with 156 additions and 105 deletions
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doc/LectureNotes/_build/.doctrees/chapter1.doctree
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doc/LectureNotes/_build/jupyter_execute/chapter1.ipynb
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doc/LectureNotes/_build/jupyter_execute/chapter10.ipynb
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@@ -869,7 +869,13 @@
" 1.10378326e-04 5.08318298e-09 2.03256632e-04 1.92507116e-03\n",
" 9.84443254e-01 3.11507992e-04]\n",
"probabilities sum up to: 1.0\n",
"\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"predictions = (n_inputs) = (1437,)\n",
"prediction for image 0: 8\n",
"correct label for image 0: 6\n"
@@ -1077,7 +1083,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1655,7 +1661,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1673,7 +1679,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1691,7 +1697,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1709,7 +1715,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1727,7 +1733,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1745,7 +1751,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1763,7 +1769,7 @@
"name": "stderr",
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"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1781,11 +1787,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1803,11 +1809,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1825,11 +1831,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1847,11 +1853,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1869,11 +1875,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1891,7 +1897,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n"
]
},
@@ -1909,11 +1915,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1931,11 +1937,11 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
@@ -1953,11 +1959,55 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_1323/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Learning rate = 10.0\n",
"Lambda = 0.0001\n",
"Accuracy score on test set: 0.07777777777777778\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Learning rate = 10.0\n",
"Lambda = 0.001\n",
"Accuracy score on test set: 0.07777777777777778\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/953065564.py:4: RuntimeWarning: overflow encountered in exp\n",
" return 1/(1 + np.exp(-x))\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:43: RuntimeWarning: overflow encountered in exp\n",
" exp_term = np.exp(self.z_o)\n",
"/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_6316/1630775253.py:44: RuntimeWarning: invalid value encountered in true_divide\n",
" self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n"
]
},
doc/LectureNotes/_build/jupyter_execute/chapter11.ipynb
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@@ -3000,13 +3000,14 @@
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/wrap_util.py:15\u001b[0m, in \u001b[0;36munary_to_nary.<locals>.nary_operator.<locals>.nary_f.<locals>.unary_f\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 14\u001b[0m subargs \u001b[38;5;241m=\u001b[39m subvals(args, \u001b[38;5;28mzip\u001b[39m(argnum, x))\n\u001b[0;32m---> 15\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msubargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/wrap_util.py:15\u001b[0m, in \u001b[0;36munary_to_nary.<locals>.nary_operator.<locals>.nary_f.<locals>.unary_f\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 14\u001b[0m subargs \u001b[38;5;241m=\u001b[39m subvals(args, \u001b[38;5;28mzip\u001b[39m(argnum, x))\n\u001b[0;32m---> 15\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msubargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"Cell \u001b[0;32mIn[9], line 61\u001b[0m, in \u001b[0;36mg_trial\u001b[0;34m(point, P)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mg_trial\u001b[39m(point,P):\n\u001b[1;32m 60\u001b[0m x,t \u001b[38;5;241m=\u001b[39m point\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mt)\u001b[38;5;241m*\u001b[39mu(x) \u001b[38;5;241m+\u001b[39m x\u001b[38;5;241m*\u001b[39m(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39mx)\u001b[38;5;241m*\u001b[39mt\u001b[38;5;241m*\u001b[39m\u001b[43mdeep_neural_network\u001b[49m\u001b[43m(\u001b[49m\u001b[43mP\u001b[49m\u001b[43m,\u001b[49m\u001b[43mpoint\u001b[49m\u001b[43m)\u001b[49m\n",
"Cell \u001b[0;32mIn[9], line 48\u001b[0m, in \u001b[0;36mdeep_neural_network\u001b[0;34m(deep_params, x)\u001b[0m\n\u001b[1;32m 45\u001b[0m w_output \u001b[38;5;241m=\u001b[39m deep_params[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m 47\u001b[0m \u001b[38;5;66;03m# Include bias:\u001b[39;00m\n\u001b[0;32m---> 48\u001b[0m x_prev \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcatenate\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mones\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mnum_points\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx_prev\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 50\u001b[0m z_output \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmatmul(w_output, x_prev)\n\u001b[1;32m 51\u001b[0m x_output \u001b[38;5;241m=\u001b[39m z_output\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/numpy/numpy_wrapper.py:38\u001b[0m, in \u001b[0;36m<lambda>\u001b[0;34m(arr_list, axis)\u001b[0m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;129m@primitive\u001b[39m\n\u001b[1;32m 36\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconcatenate_args\u001b[39m(axis, \u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 37\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _np\u001b[38;5;241m.\u001b[39mconcatenate(args, axis)\u001b[38;5;241m.\u001b[39mview(ndarray)\n\u001b[0;32m---> 38\u001b[0m concatenate \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m arr_list, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m : \u001b[43mconcatenate_args\u001b[49m\u001b[43m(\u001b[49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43marr_list\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 39\u001b[0m vstack \u001b[38;5;241m=\u001b[39m row_stack \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m tup: concatenate([atleast_2d(_m) \u001b[38;5;28;01mfor\u001b[39;00m _m \u001b[38;5;129;01min\u001b[39;00m tup], axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhstack\u001b[39m(tup):\n",
"Cell \u001b[0;32mIn[9], line 37\u001b[0m, in \u001b[0;36mdeep_neural_network\u001b[0;34m(deep_params, x)\u001b[0m\n\u001b[1;32m 34\u001b[0m x_prev \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mconcatenate((np\u001b[38;5;241m.\u001b[39mones((\u001b[38;5;241m1\u001b[39m,num_points)), x_prev ), axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m 36\u001b[0m z_hidden \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmatmul(w_hidden, x_prev)\n\u001b[0;32m---> 37\u001b[0m x_hidden \u001b[38;5;241m=\u001b[39m \u001b[43msigmoid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz_hidden\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 39\u001b[0m \u001b[38;5;66;03m# Update x_prev such that next layer can use the output from this layer\u001b[39;00m\n\u001b[1;32m 40\u001b[0m x_prev \u001b[38;5;241m=\u001b[39m x_hidden\n",
"Cell \u001b[0;32mIn[9], line 11\u001b[0m, in \u001b[0;36msigmoid\u001b[0;34m(z)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msigmoid\u001b[39m(z):\n\u001b[0;32m---> 11\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexp\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/numpy/numpy_boxes.py:39\u001b[0m, in \u001b[0;36mArrayBox.__rtruediv__\u001b[0;34m(self, other)\u001b[0m\n\u001b[0;32m---> 39\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__rtruediv__\u001b[39m(\u001b[38;5;28mself\u001b[39m, other): \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43manp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrue_divide\u001b[49m\u001b[43m(\u001b[49m\u001b[43mother\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/tracer.py:45\u001b[0m, in \u001b[0;36mprimitive.<locals>.f_wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 43\u001b[0m argnums \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(argnum \u001b[38;5;28;01mfor\u001b[39;00m argnum, _ \u001b[38;5;129;01min\u001b[39;00m boxed_args)\n\u001b[1;32m 44\u001b[0m ans \u001b[38;5;241m=\u001b[39m f_wrapped(\u001b[38;5;241m*\u001b[39margvals, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m---> 45\u001b[0m node \u001b[38;5;241m=\u001b[39m \u001b[43mnode_constructor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mans\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_wrapped\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margvals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margnums\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparents\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 46\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m new_box(ans, trace, node)\n\u001b[1;32m 47\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/core.py:36\u001b[0m, in \u001b[0;36mVJPNode.__init__\u001b[0;34m(self, value, fun, args, kwargs, parent_argnums, parents)\u001b[0m\n\u001b[1;32m 33\u001b[0m fun_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(fun, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__name__\u001b[39m\u001b[38;5;124m'\u001b[39m, fun)\n\u001b[1;32m 34\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mVJP of \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m wrt argnums \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m not defined\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 35\u001b[0m \u001b[38;5;241m.\u001b[39mformat(fun_name, parent_argnums))\n\u001b[0;32m---> 36\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvjp \u001b[38;5;241m=\u001b[39m \u001b[43mvjpmaker\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparent_argnums\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/core.py:48\u001b[0m, in \u001b[0;36mdefvjp_argnum.<locals>.vjp_argnums\u001b[0;34m(argnums, *args)\u001b[0m\n\u001b[1;32m 47\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvjp_argnums\u001b[39m(argnums, \u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m---> 48\u001b[0m vjps \u001b[38;5;241m=\u001b[39m [vjpmaker(argnum, \u001b[38;5;241m*\u001b[39margs) \u001b[38;5;28;01mfor\u001b[39;00m argnum \u001b[38;5;129;01min\u001b[39;00m argnums]\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m g: (vjp(g) \u001b[38;5;28;01mfor\u001b[39;00m vjp \u001b[38;5;129;01min\u001b[39;00m vjps)\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/core.py:48\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 47\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvjp_argnums\u001b[39m(argnums, \u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m---> 48\u001b[0m vjps \u001b[38;5;241m=\u001b[39m [\u001b[43mvjpmaker\u001b[49m\u001b[43m(\u001b[49m\u001b[43margnum\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m argnum \u001b[38;5;129;01min\u001b[39;00m argnums]\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m g: (vjp(g) \u001b[38;5;28;01mfor\u001b[39;00m vjp \u001b[38;5;129;01min\u001b[39;00m vjps)\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/numpy/numpy_vjps.py:537\u001b[0m, in \u001b[0;36mgrad_concatenate_args\u001b[0;34m(argnum, ans, axis_args, kwargs)\u001b[0m\n\u001b[1;32m 532\u001b[0m defvjp(tensordot_adjoint_1, \u001b[38;5;28;01mlambda\u001b[39;00m ans, A, G, axes, An, Bn: \u001b[38;5;28;01mlambda\u001b[39;00m B: match_complex(A, tensordot_adjoint_0(B, G, axes, An, Bn)),\n\u001b[1;32m 533\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, A, G, axes, An, Bn: \u001b[38;5;28;01mlambda\u001b[39;00m B: match_complex(G, anp\u001b[38;5;241m.\u001b[39mtensordot(A, B, axes)))\n\u001b[1;32m 534\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mouter, \u001b[38;5;28;01mlambda\u001b[39;00m ans, a, b : \u001b[38;5;28;01mlambda\u001b[39;00m g: match_complex(a, anp\u001b[38;5;241m.\u001b[39mdot(g, b\u001b[38;5;241m.\u001b[39mT)),\n\u001b[1;32m 535\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, a, b : \u001b[38;5;28;01mlambda\u001b[39;00m g: match_complex(b, anp\u001b[38;5;241m.\u001b[39mdot(a\u001b[38;5;241m.\u001b[39mT, g)))\n\u001b[0;32m--> 537\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mgrad_concatenate_args\u001b[39m(argnum, ans, axis_args, kwargs):\n\u001b[1;32m 538\u001b[0m axis, args \u001b[38;5;241m=\u001b[39m axis_args[\u001b[38;5;241m0\u001b[39m], axis_args[\u001b[38;5;241m1\u001b[39m:]\n\u001b[1;32m 539\u001b[0m sizes \u001b[38;5;241m=\u001b[39m [anp\u001b[38;5;241m.\u001b[39mshape(a)[axis] \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m args[:argnum]]\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/core.py:66\u001b[0m, in \u001b[0;36mdefvjp.<locals>.vjp_argnums\u001b[0;34m(argnums, ans, args, kwargs)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\n\u001b[1;32m 65\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mVJP of \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m wrt argnum 0 not defined\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(fun\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m))\n\u001b[0;32m---> 66\u001b[0m vjp \u001b[38;5;241m=\u001b[39m \u001b[43mvjpfun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mans\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 67\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m g: (vjp(g),)\n\u001b[1;32m 68\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m L \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/numpy/numpy_vjps.py:53\u001b[0m, in \u001b[0;36m<lambda>\u001b[0;34m(ans, x, y)\u001b[0m\n\u001b[1;32m 48\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mlogaddexp, \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(x, \u001b[38;5;28;01mlambda\u001b[39;00m g: g \u001b[38;5;241m*\u001b[39m anp\u001b[38;5;241m.\u001b[39mexp(x\u001b[38;5;241m-\u001b[39mans)),\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(y, \u001b[38;5;28;01mlambda\u001b[39;00m g: g \u001b[38;5;241m*\u001b[39m anp\u001b[38;5;241m.\u001b[39mexp(y\u001b[38;5;241m-\u001b[39mans)))\n\u001b[1;32m 50\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mlogaddexp2, \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(x, \u001b[38;5;28;01mlambda\u001b[39;00m g: g \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m2\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m(x\u001b[38;5;241m-\u001b[39mans)),\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(y, \u001b[38;5;28;01mlambda\u001b[39;00m g: g \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m2\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m(y\u001b[38;5;241m-\u001b[39mans)))\n\u001b[1;32m 52\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mtrue_divide, \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(x, \u001b[38;5;28;01mlambda\u001b[39;00m g: g \u001b[38;5;241m/\u001b[39m y),\n\u001b[0;32m---> 53\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : \u001b[43munbroadcast_f\u001b[49m\u001b[43m(\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mg\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mg\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 54\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mmod, \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(x, \u001b[38;5;28;01mlambda\u001b[39;00m g: g),\n\u001b[1;32m 55\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(y, \u001b[38;5;28;01mlambda\u001b[39;00m g: \u001b[38;5;241m-\u001b[39mg \u001b[38;5;241m*\u001b[39m anp\u001b[38;5;241m.\u001b[39mfloor(x\u001b[38;5;241m/\u001b[39my)))\n\u001b[1;32m 56\u001b[0m defvjp(anp\u001b[38;5;241m.\u001b[39mremainder, \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(x, \u001b[38;5;28;01mlambda\u001b[39;00m g: g),\n\u001b[1;32m 57\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m ans, x, y : unbroadcast_f(y, \u001b[38;5;28;01mlambda\u001b[39;00m g: \u001b[38;5;241m-\u001b[39mg \u001b[38;5;241m*\u001b[39m anp\u001b[38;5;241m.\u001b[39mfloor(x\u001b[38;5;241m/\u001b[39my)))\n",
"File \u001b[0;32m~/miniforge3/envs/myenv/lib/python3.9/site-packages/autograd/numpy/numpy_vjps.py:658\u001b[0m, in \u001b[0;36munbroadcast_f\u001b[0;34m(target, f)\u001b[0m\n\u001b[1;32m 655\u001b[0m x \u001b[38;5;241m=\u001b[39m anp\u001b[38;5;241m.\u001b[39mreal(x)\n\u001b[1;32m 656\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m x\n\u001b[0;32m--> 658\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21munbroadcast_f\u001b[39m(target, f):\n\u001b[1;32m 659\u001b[0m target_meta \u001b[38;5;241m=\u001b[39m anp\u001b[38;5;241m.\u001b[39mmetadata(target)\n\u001b[1;32m 660\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mlambda\u001b[39;00m g: unbroadcast(f(g), target_meta)\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
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