flowzl/deeplearn-torch
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
main
deeplearn-torch/Chapter_1.ipynb
flowerstonezl 2502e18330 初始化
2026-01-14 15:19:22 +08:00

2670 lines
122 KiB
Plaintext
Raw Permalink Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
{
"cells": [
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.107372Z",
"start_time": "2021-03-22T05:32:53.400242Z"
},
"tags": [
"remove_output"
]
},
"outputs": [],
"source": [
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from tqdm.autonotebook import tqdm\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.114216Z",
"start_time": "2021-03-22T05:32:54.109474Z"
},
"tags": [
"remove_cell"
]
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib_inline\n",
"matplotlib_inline.backend_inline.set_matplotlib_formats('svg')"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.669963Z",
"start_time": "2021-03-22T05:32:54.116147Z"
}
},
"outputs": [],
"source": [
"import torch"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.676062Z",
"start_time": "2021-03-22T05:32:54.671481Z"
}
},
"outputs": [],
"source": [
"torch_scalar = torch.tensor(3.14)\n",
"torch_vector = torch.tensor([1, 2, 3, 4])\n",
"torch_matrix = torch.tensor([[1, 2,],\n",
" [3, 4,],\n",
" [5, 6,], \n",
" [7, 8,]])\n",
"#You don't have to format it like I did, thats just for clarity\n",
"torch_tensor3d = torch.tensor([\n",
" [\n",
" [ 1, 2, 3], \n",
" [ 4, 5, 6],\n",
" ],\n",
" [\n",
" [ 7, 8, 9], \n",
" [10, 11, 12],\n",
" ],\n",
" [\n",
" [13, 14, 15], \n",
" [16, 17, 18],\n",
" ],\n",
" [\n",
" [19, 20, 21], \n",
" [22, 23, 24],\n",
" ]\n",
" ])"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.688664Z",
"start_time": "2021-03-22T05:32:54.677220Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([])\n",
"torch.Size([4])\n",
"torch.Size([4, 2])\n",
"torch.Size([4, 2, 3])\n"
]
}
],
"source": [
"print(torch_scalar.shape)\n",
"print(torch_vector.shape)\n",
"print(torch_matrix.shape)\n",
"print(torch_tensor3d.shape)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.694456Z",
"start_time": "2021-03-22T05:32:54.690164Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[0.13200003 0.0054197 0.24716025 0.08458665]\n",
" [0.51738806 0.517676 0.33316974 0.07034239]\n",
" [0.53272871 0.51833686 0.73074206 0.82302625]\n",
" [0.37334327 0.59914251 0.82853404 0.51186258]]\n"
]
}
],
"source": [
"x_np = np.random.random((4,4))\n",
"print(x_np)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.701736Z",
"start_time": "2021-03-22T05:32:54.697048Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[0.1320, 0.0054, 0.2472, 0.0846],\n",
" [0.5174, 0.5177, 0.3332, 0.0703],\n",
" [0.5327, 0.5183, 0.7307, 0.8230],\n",
" [0.3733, 0.5991, 0.8285, 0.5119]], dtype=torch.float64)\n"
]
}
],
"source": [
"x_pt = torch.tensor(x_np)\n",
"print(x_pt)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.708524Z",
"start_time": "2021-03-22T05:32:54.703648Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"float64 torch.float64\n"
]
}
],
"source": [
"print(x_np.dtype, x_pt.dtype)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.715713Z",
"start_time": "2021-03-22T05:32:54.710165Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"float32 torch.float32\n"
]
}
],
"source": [
"#Lets force them to be 32-bit floats\n",
"x_np = np.asarray(x_np, dtype=np.float32)\n",
"x_pt = torch.tensor(x_np, dtype=torch.float32)\n",
"print(x_np.dtype, x_pt.dtype)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.722368Z",
"start_time": "2021-03-22T05:32:54.717373Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[False False False False]\n",
" [ True True False False]\n",
" [ True True True True]\n",
" [False True True True]]\n",
"bool\n"
]
}
],
"source": [
"b_np = (x_np > 0.5)\n",
"print(b_np)\n",
"print(b_np.dtype)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.729593Z",
"start_time": "2021-03-22T05:32:54.724132Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[False, False, False, False],\n",
" [ True, True, False, False],\n",
" [ True, True, True, True],\n",
" [False, True, True, True]])\n",
"torch.bool\n"
]
}
],
"source": [
"b_pt = (x_pt > 0.5)\n",
"print(b_pt)\n",
"print(b_pt.dtype)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.737835Z",
"start_time": "2021-03-22T05:32:54.730952Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"np.float32(6.8254595)"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sum(x_np)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.743037Z",
"start_time": "2021-03-22T05:32:54.739198Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"tensor(6.8255)"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"torch.sum(x_pt)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.747879Z",
"start_time": "2021-03-22T05:32:54.744383Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.13200003, 0.51738805, 0.53272873, 0.37334326],\n",
" [0.0054197 , 0.517676 , 0.5183369 , 0.5991425 ],\n",
" [0.24716026, 0.33316973, 0.73074204, 0.82853407],\n",
" [0.08458665, 0.07034239, 0.82302624, 0.5118626 ]], dtype=float32)"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.transpose(x_np)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.755058Z",
"start_time": "2021-03-22T05:32:54.749723Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"tensor([[0.1320, 0.5174, 0.5327, 0.3733],\n",
" [0.0054, 0.5177, 0.5183, 0.5991],\n",
" [0.2472, 0.3332, 0.7307, 0.8285],\n",
" [0.0846, 0.0703, 0.8230, 0.5119]])"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"torch.transpose(x_pt, 0, 1)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:54.763796Z",
"start_time": "2021-03-22T05:32:54.756945Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([3, 2, 4])\n"
]
}
],
"source": [
"print(torch.transpose(torch_tensor3d, 0, 2).shape)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:59.532902Z",
"start_time": "2021-03-22T05:32:54.765163Z"
}
},
"outputs": [],
"source": [
"import timeit\n",
"x = torch.rand(2**11, 2**11)\n",
"time_cpu = timeit.timeit(\"x@x\", globals=globals(), number=100)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:32:59.578188Z",
"start_time": "2021-03-22T05:32:59.539627Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Is CUDA available? : True\n"
]
}
],
"source": [
"print(\"Is CUDA available? :\", torch.cuda.is_available())\n",
"device = torch.device(\"cuda\")"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:01.740576Z",
"start_time": "2021-03-22T05:32:59.580308Z"
}
},
"outputs": [],
"source": [
"x = x.to(device)\n",
"time_gpu = timeit.timeit(\"x@x\", globals=globals(), number=100)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:01.957208Z",
"start_time": "2021-03-22T05:33:01.750393Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[tensor(1), tensor(2)]\n",
"[tensor(1, device='cuda:0'), tensor(2, device='cuda:0')]\n"
]
}
],
"source": [
"def moveTo(obj, device):\n",
" \"\"\"\n",
" obj: the python object to move to a device, or to move its contents to a device\n",
" device: the compute device to move objects to\n",
" \"\"\"\n",
" if isinstance(obj, list):\n",
" return [moveTo(x, device) for x in obj]\n",
" elif isinstance(obj, tuple):\n",
" return tuple(moveTo(list(obj), device))\n",
" elif isinstance(obj, set):\n",
" return set(moveTo(list(obj), device))\n",
" elif isinstance(obj, dict):\n",
" to_ret = dict()\n",
" for key, value in obj.items():\n",
" to_ret[moveTo(key, device)] = moveTo(value, device)\n",
" return to_ret\n",
" elif hasattr(obj, \"to\"):\n",
" return obj.to(device)\n",
" else:\n",
" return obj\n",
" \n",
"some_tensors = [torch.tensor(1), torch.tensor(2)]\n",
"print(some_tensors)\n",
"print(moveTo(some_tensors, device))"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.498610Z",
"start_time": "2021-03-22T05:33:01.960934Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/svg+xml": [
"<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
"<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
"<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"391.245pt\" height=\"297.190125pt\" viewBox=\"0 0 391.245 297.190125\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n",
" <metadata>\n",
" <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
" <cc:Work>\n",
" <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
" <dc:date>2026-01-13T20:15:58.092532</dc:date>\n",
" <dc:format>image/svg+xml</dc:format>\n",
" <dc:creator>\n",
" <cc:Agent>\n",
" <dc:title>Matplotlib v3.10.7, https://matplotlib.org/</dc:title>\n",
" </cc:Agent>\n",
" </dc:creator>\n",
" </cc:Work>\n",
" </rdf:RDF>\n",
" </metadata>\n",
" <defs>\n",
" <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n",
" </defs>\n",
" <g id=\"figure_1\">\n",
" <g id=\"patch_1\">\n",
" <path d=\"M 0 297.190125 \n",
"L 391.245 297.190125 \n",
"L 391.245 0 \n",
"L 0 0 \n",
"z\n",
"\" style=\"fill: #ffffff\"/>\n",
" </g>\n",
" <g id=\"axes_1\">\n",
" <g id=\"patch_2\">\n",
" <path d=\"M 26.925 273.312 \n",
"L 384.045 273.312 \n",
"L 384.045 7.2 \n",
"L 26.925 7.2 \n",
"z\n",
"\" style=\"fill: #ffffff\"/>\n",
" </g>\n",
" <g id=\"FillBetweenPolyCollection_1\"/>\n",
" <g id=\"matplotlib.axis_1\">\n",
" <g id=\"xtick_1\">\n",
" <g id=\"line2d_1\">\n",
" <defs>\n",
" <path id=\"ma0e1805e84\" d=\"M 0 0 \n",
"L 0 3.5 \n",
"\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </defs>\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"63.448636\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_1\">\n",
" <!-- −6 -->\n",
" <g transform=\"translate(56.077543 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-2212\" d=\"M 678 2272 \n",
"L 4684 2272 \n",
"L 4684 1741 \n",
"L 678 1741 \n",
"L 678 2272 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-36\" d=\"M 2113 2584 \n",
"Q 1688 2584 1439 2293 \n",
"Q 1191 2003 1191 1497 \n",
"Q 1191 994 1439 701 \n",
"Q 1688 409 2113 409 \n",
"Q 2538 409 2786 701 \n",
"Q 3034 994 3034 1497 \n",
"Q 3034 2003 2786 2293 \n",
"Q 2538 2584 2113 2584 \n",
"z\n",
"M 3366 4563 \n",
"L 3366 3988 \n",
"Q 3128 4100 2886 4159 \n",
"Q 2644 4219 2406 4219 \n",
"Q 1781 4219 1451 3797 \n",
"Q 1122 3375 1075 2522 \n",
"Q 1259 2794 1537 2939 \n",
"Q 1816 3084 2150 3084 \n",
"Q 2853 3084 3261 2657 \n",
"Q 3669 2231 3669 1497 \n",
"Q 3669 778 3244 343 \n",
"Q 2819 -91 2113 -91 \n",
"Q 1303 -91 875 529 \n",
"Q 447 1150 447 2328 \n",
"Q 447 3434 972 4092 \n",
"Q 1497 4750 2381 4750 \n",
"Q 2619 4750 2861 4703 \n",
"Q 3103 4656 3366 4563 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-36\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_2\">\n",
" <g id=\"line2d_2\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"104.030455\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_2\">\n",
" <!-- −4 -->\n",
" <g transform=\"translate(96.659361 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n",
"L 825 1625 \n",
"L 2419 1625 \n",
"L 2419 4116 \n",
"z\n",
"M 2253 4666 \n",
"L 3047 4666 \n",
"L 3047 1625 \n",
"L 3713 1625 \n",
"L 3713 1100 \n",
"L 3047 1100 \n",
"L 3047 0 \n",
"L 2419 0 \n",
"L 2419 1100 \n",
"L 313 1100 \n",
"L 313 1709 \n",
"L 2253 4666 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-34\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_3\">\n",
" <g id=\"line2d_3\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"144.612273\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_3\">\n",
" <!-- −2 -->\n",
" <g transform=\"translate(137.241179 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n",
"L 3431 531 \n",
"L 3431 0 \n",
"L 469 0 \n",
"L 469 531 \n",
"Q 828 903 1448 1529 \n",
"Q 2069 2156 2228 2338 \n",
"Q 2531 2678 2651 2914 \n",
"Q 2772 3150 2772 3378 \n",
"Q 2772 3750 2511 3984 \n",
"Q 2250 4219 1831 4219 \n",
"Q 1534 4219 1204 4116 \n",
"Q 875 4013 500 3803 \n",
"L 500 4441 \n",
"Q 881 4594 1212 4672 \n",
"Q 1544 4750 1819 4750 \n",
"Q 2544 4750 2975 4387 \n",
"Q 3406 4025 3406 3419 \n",
"Q 3406 3131 3298 2873 \n",
"Q 3191 2616 2906 2266 \n",
"Q 2828 2175 2409 1742 \n",
"Q 1991 1309 1228 531 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_4\">\n",
" <g id=\"line2d_4\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"185.194091\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_4\">\n",
" <!-- 0 -->\n",
" <g transform=\"translate(182.012841 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n",
"Q 1547 4250 1301 3770 \n",
"Q 1056 3291 1056 2328 \n",
"Q 1056 1369 1301 889 \n",
"Q 1547 409 2034 409 \n",
"Q 2525 409 2770 889 \n",
"Q 3016 1369 3016 2328 \n",
"Q 3016 3291 2770 3770 \n",
"Q 2525 4250 2034 4250 \n",
"z\n",
"M 2034 4750 \n",
"Q 2819 4750 3233 4129 \n",
"Q 3647 3509 3647 2328 \n",
"Q 3647 1150 3233 529 \n",
"Q 2819 -91 2034 -91 \n",
"Q 1250 -91 836 529 \n",
"Q 422 1150 422 2328 \n",
"Q 422 3509 836 4129 \n",
"Q 1250 4750 2034 4750 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-30\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_5\">\n",
" <g id=\"line2d_5\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"225.775909\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_5\">\n",
" <!-- 2 -->\n",
" <g transform=\"translate(222.594659 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-32\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_6\">\n",
" <g id=\"line2d_6\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"266.357727\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_6\">\n",
" <!-- 4 -->\n",
" <g transform=\"translate(263.176477 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-34\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_7\">\n",
" <g id=\"line2d_7\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"306.939545\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_7\">\n",
" <!-- 6 -->\n",
" <g transform=\"translate(303.758295 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-36\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_8\">\n",
" <g id=\"line2d_8\">\n",
" <g>\n",
" <use xlink:href=\"#ma0e1805e84\" x=\"347.521364\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_8\">\n",
" <!-- 8 -->\n",
" <g transform=\"translate(344.340114 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-38\" d=\"M 2034 2216 \n",
"Q 1584 2216 1326 1975 \n",
"Q 1069 1734 1069 1313 \n",
"Q 1069 891 1326 650 \n",
"Q 1584 409 2034 409 \n",
"Q 2484 409 2743 651 \n",
"Q 3003 894 3003 1313 \n",
"Q 3003 1734 2745 1975 \n",
"Q 2488 2216 2034 2216 \n",
"z\n",
"M 1403 2484 \n",
"Q 997 2584 770 2862 \n",
"Q 544 3141 544 3541 \n",
"Q 544 4100 942 4425 \n",
"Q 1341 4750 2034 4750 \n",
"Q 2731 4750 3128 4425 \n",
"Q 3525 4100 3525 3541 \n",
"Q 3525 3141 3298 2862 \n",
"Q 3072 2584 2669 2484 \n",
"Q 3125 2378 3379 2068 \n",
"Q 3634 1759 3634 1313 \n",
"Q 3634 634 3220 271 \n",
"Q 2806 -91 2034 -91 \n",
"Q 1263 -91 848 271 \n",
"Q 434 634 434 1313 \n",
"Q 434 1759 690 2068 \n",
"Q 947 2378 1403 2484 \n",
"z\n",
"M 1172 3481 \n",
"Q 1172 3119 1398 2916 \n",
"Q 1625 2713 2034 2713 \n",
"Q 2441 2713 2670 2916 \n",
"Q 2900 3119 2900 3481 \n",
"Q 2900 3844 2670 4047 \n",
"Q 2441 4250 2034 4250 \n",
"Q 1625 4250 1398 4047 \n",
"Q 1172 3844 1172 3481 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-38\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"matplotlib.axis_2\">\n",
" <g id=\"ytick_1\">\n",
" <g id=\"line2d_9\">\n",
" <defs>\n",
" <path id=\"m896a207479\" d=\"M 0 0 \n",
"L -3.5 0 \n",
"\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </defs>\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"261.223619\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_9\">\n",
" <!-- 0 -->\n",
" <g transform=\"translate(13.5625 265.022837) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-30\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_2\">\n",
" <g id=\"line2d_10\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"231.356011\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_10\">\n",
" <!-- 10 -->\n",
" <g transform=\"translate(7.2 235.15523) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-31\" d=\"M 794 531 \n",
"L 1825 531 \n",
"L 1825 4091 \n",
"L 703 3866 \n",
"L 703 4441 \n",
"L 1819 4666 \n",
"L 2450 4666 \n",
"L 2450 531 \n",
"L 3481 531 \n",
"L 3481 0 \n",
"L 794 0 \n",
"L 794 531 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-31\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_3\">\n",
" <g id=\"line2d_11\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"201.488404\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_11\">\n",
" <!-- 20 -->\n",
" <g transform=\"translate(7.2 205.287623) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-32\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_4\">\n",
" <g id=\"line2d_12\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"171.620797\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_12\">\n",
" <!-- 30 -->\n",
" <g transform=\"translate(7.2 175.420016) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-33\" d=\"M 2597 2516 \n",
"Q 3050 2419 3304 2112 \n",
"Q 3559 1806 3559 1356 \n",
"Q 3559 666 3084 287 \n",
"Q 2609 -91 1734 -91 \n",
"Q 1441 -91 1130 -33 \n",
"Q 819 25 488 141 \n",
"L 488 750 \n",
"Q 750 597 1062 519 \n",
"Q 1375 441 1716 441 \n",
"Q 2309 441 2620 675 \n",
"Q 2931 909 2931 1356 \n",
"Q 2931 1769 2642 2001 \n",
"Q 2353 2234 1838 2234 \n",
"L 1294 2234 \n",
"L 1294 2753 \n",
"L 1863 2753 \n",
"Q 2328 2753 2575 2939 \n",
"Q 2822 3125 2822 3475 \n",
"Q 2822 3834 2567 4026 \n",
"Q 2313 4219 1838 4219 \n",
"Q 1578 4219 1281 4162 \n",
"Q 984 4106 628 3988 \n",
"L 628 4550 \n",
"Q 988 4650 1302 4700 \n",
"Q 1616 4750 1894 4750 \n",
"Q 2613 4750 3031 4423 \n",
"Q 3450 4097 3450 3541 \n",
"Q 3450 3153 3228 2886 \n",
"Q 3006 2619 2597 2516 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-33\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_5\">\n",
" <g id=\"line2d_13\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"141.75319\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_13\">\n",
" <!-- 40 -->\n",
" <g transform=\"translate(7.2 145.552408) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-34\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_6\">\n",
" <g id=\"line2d_14\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"111.885582\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_14\">\n",
" <!-- 50 -->\n",
" <g transform=\"translate(7.2 115.684801) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-35\" d=\"M 691 4666 \n",
"L 3169 4666 \n",
"L 3169 4134 \n",
"L 1269 4134 \n",
"L 1269 2991 \n",
"Q 1406 3038 1543 3061 \n",
"Q 1681 3084 1819 3084 \n",
"Q 2600 3084 3056 2656 \n",
"Q 3513 2228 3513 1497 \n",
"Q 3513 744 3044 326 \n",
"Q 2575 -91 1722 -91 \n",
"Q 1428 -91 1123 -41 \n",
"Q 819 9 494 109 \n",
"L 494 744 \n",
"Q 775 591 1075 516 \n",
"Q 1375 441 1709 441 \n",
"Q 2250 441 2565 725 \n",
"Q 2881 1009 2881 1497 \n",
"Q 2881 1984 2565 2268 \n",
"Q 2250 2553 1709 2553 \n",
"Q 1456 2553 1204 2497 \n",
"Q 953 2441 691 2322 \n",
"L 691 4666 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-35\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_7\">\n",
" <g id=\"line2d_15\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"82.017975\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_15\">\n",
" <!-- 60 -->\n",
" <g transform=\"translate(7.2 85.817194) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-36\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_8\">\n",
" <g id=\"line2d_16\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"52.150368\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_16\">\n",
" <!-- 70 -->\n",
" <g transform=\"translate(7.2 55.949587) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-37\" d=\"M 525 4666 \n",
"L 3525 4666 \n",
"L 3525 4397 \n",
"L 1831 0 \n",
"L 1172 0 \n",
"L 2766 4134 \n",
"L 525 4134 \n",
"L 525 4666 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-37\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_9\">\n",
" <g id=\"line2d_17\">\n",
" <g>\n",
" <use xlink:href=\"#m896a207479\" x=\"26.925\" y=\"22.282761\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_17\">\n",
" <!-- 80 -->\n",
" <g transform=\"translate(7.2 26.081979) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-38\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"line2d_18\">\n",
" <path d=\"M 43.157727 19.296 \n",
"L 46.437066 27.906745 \n",
"L 49.716405 36.361463 \n",
"L 52.995744 44.660153 \n",
"L 56.275083 52.802817 \n",
"L 59.554421 60.789454 \n",
"L 62.83376 68.620063 \n",
"L 66.113099 76.294646 \n",
"L 69.392438 83.813201 \n",
"L 72.671777 91.175729 \n",
"L 75.951116 98.38223 \n",
"L 79.230455 105.432704 \n",
"L 82.509793 112.327151 \n",
"L 85.789132 119.065571 \n",
"L 89.068471 125.647964 \n",
"L 92.34781 132.07433 \n",
"L 95.627149 138.344668 \n",
"L 98.906488 144.45898 \n",
"L 102.185826 150.417264 \n",
"L 105.465165 156.219521 \n",
"L 108.744504 161.865752 \n",
"L 112.023843 167.355955 \n",
"L 115.303182 172.690131 \n",
"L 118.582521 177.86828 \n",
"L 121.86186 182.890402 \n",
"L 125.141198 187.756497 \n",
"L 128.420537 192.466564 \n",
"L 131.699876 197.020605 \n",
"L 134.979215 201.418619 \n",
"L 138.258554 205.660605 \n",
"L 141.537893 209.746564 \n",
"L 144.817231 213.676497 \n",
"L 148.09657 217.450402 \n",
"L 151.375909 221.06828 \n",
"L 154.655248 224.530131 \n",
"L 157.934587 227.835955 \n",
"L 161.213926 230.985752 \n",
"L 164.493264 233.979521 \n",
"L 167.772603 236.817264 \n",
"L 171.051942 239.49898 \n",
"L 174.331281 242.024668 \n",
"L 177.61062 244.39433 \n",
"L 180.889959 246.607964 \n",
"L 184.169298 248.665571 \n",
"L 187.448636 250.567151 \n",
"L 190.727975 252.312704 \n",
"L 194.007314 253.90223 \n",
"L 197.286653 255.335729 \n",
"L 200.565992 256.613201 \n",
"L 203.845331 257.734646 \n",
"L 207.124669 258.700063 \n",
"L 210.404008 259.509454 \n",
"L 213.683347 260.162817 \n",
"L 216.962686 260.660153 \n",
"L 220.242025 261.001463 \n",
"L 223.521364 261.186745 \n",
"L 226.800702 261.216 \n",
"L 230.080041 261.089228 \n",
"L 233.35938 260.806429 \n",
"L 236.638719 260.367603 \n",
"L 239.918058 259.772749 \n",
"L 243.197397 259.021869 \n",
"L 246.476736 258.114962 \n",
"L 249.756074 257.052027 \n",
"L 253.035413 255.833065 \n",
"L 256.314752 254.458077 \n",
"L 259.594091 252.927061 \n",
"L 262.87343 251.240018 \n",
"L 266.152769 249.396948 \n",
"L 269.432107 247.397851 \n",
"L 272.711446 245.242727 \n",
"L 275.990785 242.931576 \n",
"L 279.270124 240.464397 \n",
"L 282.549463 237.841192 \n",
"L 285.828802 235.061959 \n",
"L 289.10814 232.1267 \n",
"L 292.387479 229.035413 \n",
"L 295.666818 225.788099 \n",
"L 298.946157 222.384758 \n",
"L 302.225496 218.825391 \n",
"L 305.504835 215.109995 \n",
"L 308.784174 211.238573 \n",
"L 312.063512 207.211124 \n",
"L 315.342851 203.027648 \n",
"L 318.62219 198.688144 \n",
"L 321.901529 194.192614 \n",
"L 325.180868 189.541056 \n",
"L 328.460207 184.733472 \n",
"L 331.739545 179.76986 \n",
"L 335.018884 174.650221 \n",
"L 338.298223 169.374555 \n",
"L 341.577562 163.942862 \n",
"L 344.856901 158.355142 \n",
"L 348.13624 152.611395 \n",
"L 351.415579 146.711621 \n",
"L 354.694917 140.655819 \n",
"L 357.974256 134.443991 \n",
"L 361.253595 128.076135 \n",
"L 364.532934 121.552253 \n",
"L 367.812273 114.872343 \n",
"\" clip-path=\"url(#p674c4daeaf)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_3\">\n",
" <path d=\"M 26.925 273.312 \n",
"L 26.925 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_4\">\n",
" <path d=\"M 384.045 273.312 \n",
"L 384.045 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_5\">\n",
" <path d=\"M 26.925 273.312 \n",
"L 384.045 273.312 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_6\">\n",
" <path d=\"M 26.925 7.2 \n",
"L 384.045 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"legend_1\">\n",
" <g id=\"patch_7\">\n",
" <path d=\"M 278.345 30.7 \n",
"L 377.045 30.7 \n",
"Q 379.045 30.7 379.045 28.7 \n",
"L 379.045 14.2 \n",
"Q 379.045 12.2 377.045 12.2 \n",
"L 278.345 12.2 \n",
"Q 276.345 12.2 276.345 14.2 \n",
"L 276.345 28.7 \n",
"Q 276.345 30.7 278.345 30.7 \n",
"z\n",
"\" style=\"fill: #ffffff; opacity: 0.8; stroke: #cccccc; stroke-linejoin: miter\"/>\n",
" </g>\n",
" <g id=\"line2d_19\">\n",
" <path d=\"M 280.345 21.120312 \n",
"L 290.345 21.120312 \n",
"L 300.345 21.120312 \n",
"\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"text_18\">\n",
" <!-- $f(x)=(x-2)^2$ -->\n",
" <g transform=\"translate(308.345 24.620312) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-Oblique-66\" d=\"M 3059 4863 \n",
"L 2969 4384 \n",
"L 2419 4384 \n",
"Q 2106 4384 1964 4261 \n",
"Q 1822 4138 1753 3809 \n",
"L 1691 3500 \n",
"L 2638 3500 \n",
"L 2553 3053 \n",
"L 1606 3053 \n",
"L 1013 0 \n",
"L 434 0 \n",
"L 1031 3053 \n",
"L 481 3053 \n",
"L 563 3500 \n",
"L 1113 3500 \n",
"L 1159 3744 \n",
"Q 1278 4363 1576 4613 \n",
"Q 1875 4863 2516 4863 \n",
"L 3059 4863 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-28\" d=\"M 1984 4856 \n",
"Q 1566 4138 1362 3434 \n",
"Q 1159 2731 1159 2009 \n",
"Q 1159 1288 1364 580 \n",
"Q 1569 -128 1984 -844 \n",
"L 1484 -844 \n",
"Q 1016 -109 783 600 \n",
"Q 550 1309 550 2009 \n",
"Q 550 2706 781 3412 \n",
"Q 1013 4119 1484 4856 \n",
"L 1984 4856 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-Oblique-78\" d=\"M 3841 3500 \n",
"L 2234 1784 \n",
"L 3219 0 \n",
"L 2559 0 \n",
"L 1819 1388 \n",
"L 531 0 \n",
"L -166 0 \n",
"L 1556 1844 \n",
"L 641 3500 \n",
"L 1300 3500 \n",
"L 1972 2234 \n",
"L 3144 3500 \n",
"L 3841 3500 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-29\" d=\"M 513 4856 \n",
"L 1013 4856 \n",
"Q 1481 4119 1714 3412 \n",
"Q 1947 2706 1947 2009 \n",
"Q 1947 1309 1714 600 \n",
"Q 1481 -109 1013 -844 \n",
"L 513 -844 \n",
"Q 928 -128 1133 580 \n",
"Q 1338 1288 1338 2009 \n",
"Q 1338 2731 1133 3434 \n",
"Q 928 4138 513 4856 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-3d\" d=\"M 678 2906 \n",
"L 4684 2906 \n",
"L 4684 2381 \n",
"L 678 2381 \n",
"L 678 2906 \n",
"z\n",
"M 678 1631 \n",
"L 4684 1631 \n",
"L 4684 1100 \n",
"L 678 1100 \n",
"L 678 1631 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-66\" transform=\"translate(0 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-28\" transform=\"translate(35.205078 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(74.21875 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-29\" transform=\"translate(133.398438 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-3d\" transform=\"translate(191.894531 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-28\" transform=\"translate(295.166016 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(334.179688 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-2212\" transform=\"translate(412.841797 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(516.113281 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-29\" transform=\"translate(579.736328 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(619.707031 39.046875) scale(0.7)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <defs>\n",
" <clipPath id=\"p674c4daeaf\">\n",
" <rect x=\"26.925\" y=\"7.2\" width=\"357.12\" height=\"266.112\"/>\n",
" </clipPath>\n",
" </defs>\n",
"</svg>\n"
],
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def f(x):\n",
" return torch.pow((x-2.0), 2)\n",
"\n",
"x_axis_vals = np.linspace(-7,9,100) \n",
"y_axis_vals = f(torch.tensor(x_axis_vals)).numpy()\n",
"\n",
"sns.lineplot(x=x_axis_vals, y=y_axis_vals, label='$f(x)=(x-2)^2$')"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.866511Z",
"start_time": "2021-03-22T05:33:02.501436Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/svg+xml": [
"<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
"<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
"<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"399.624687pt\" height=\"297.190125pt\" viewBox=\"0 0 399.624687 297.190125\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n",
" <metadata>\n",
" <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
" <cc:Work>\n",
" <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
" <dc:date>2026-01-13T20:15:58.198134</dc:date>\n",
" <dc:format>image/svg+xml</dc:format>\n",
" <dc:creator>\n",
" <cc:Agent>\n",
" <dc:title>Matplotlib v3.10.7, https://matplotlib.org/</dc:title>\n",
" </cc:Agent>\n",
" </dc:creator>\n",
" </cc:Work>\n",
" </rdf:RDF>\n",
" </metadata>\n",
" <defs>\n",
" <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: butt}</style>\n",
" </defs>\n",
" <g id=\"figure_1\">\n",
" <g id=\"patch_1\">\n",
" <path d=\"M 0 297.190125 \n",
"L 399.624687 297.190125 \n",
"L 399.624687 0 \n",
"L 0 0 \n",
"z\n",
"\" style=\"fill: #ffffff\"/>\n",
" </g>\n",
" <g id=\"axes_1\">\n",
" <g id=\"patch_2\">\n",
" <path d=\"M 35.304688 273.312 \n",
"L 392.424688 273.312 \n",
"L 392.424688 7.2 \n",
"L 35.304688 7.2 \n",
"z\n",
"\" style=\"fill: #ffffff\"/>\n",
" </g>\n",
" <g id=\"FillBetweenPolyCollection_1\"/>\n",
" <g id=\"FillBetweenPolyCollection_2\"/>\n",
" <g id=\"FillBetweenPolyCollection_3\"/>\n",
" <g id=\"matplotlib.axis_1\">\n",
" <g id=\"xtick_1\">\n",
" <g id=\"line2d_1\">\n",
" <defs>\n",
" <path id=\"mc8e19cfe9e\" d=\"M 0 0 \n",
"L 0 3.5 \n",
"\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </defs>\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"71.828324\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_1\">\n",
" <!-- −6 -->\n",
" <g transform=\"translate(64.45723 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-2212\" d=\"M 678 2272 \n",
"L 4684 2272 \n",
"L 4684 1741 \n",
"L 678 1741 \n",
"L 678 2272 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-36\" d=\"M 2113 2584 \n",
"Q 1688 2584 1439 2293 \n",
"Q 1191 2003 1191 1497 \n",
"Q 1191 994 1439 701 \n",
"Q 1688 409 2113 409 \n",
"Q 2538 409 2786 701 \n",
"Q 3034 994 3034 1497 \n",
"Q 3034 2003 2786 2293 \n",
"Q 2538 2584 2113 2584 \n",
"z\n",
"M 3366 4563 \n",
"L 3366 3988 \n",
"Q 3128 4100 2886 4159 \n",
"Q 2644 4219 2406 4219 \n",
"Q 1781 4219 1451 3797 \n",
"Q 1122 3375 1075 2522 \n",
"Q 1259 2794 1537 2939 \n",
"Q 1816 3084 2150 3084 \n",
"Q 2853 3084 3261 2657 \n",
"Q 3669 2231 3669 1497 \n",
"Q 3669 778 3244 343 \n",
"Q 2819 -91 2113 -91 \n",
"Q 1303 -91 875 529 \n",
"Q 447 1150 447 2328 \n",
"Q 447 3434 972 4092 \n",
"Q 1497 4750 2381 4750 \n",
"Q 2619 4750 2861 4703 \n",
"Q 3103 4656 3366 4563 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-36\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_2\">\n",
" <g id=\"line2d_2\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"112.410142\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_2\">\n",
" <!-- −4 -->\n",
" <g transform=\"translate(105.039048 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-34\" d=\"M 2419 4116 \n",
"L 825 1625 \n",
"L 2419 1625 \n",
"L 2419 4116 \n",
"z\n",
"M 2253 4666 \n",
"L 3047 4666 \n",
"L 3047 1625 \n",
"L 3713 1625 \n",
"L 3713 1100 \n",
"L 3047 1100 \n",
"L 3047 0 \n",
"L 2419 0 \n",
"L 2419 1100 \n",
"L 313 1100 \n",
"L 313 1709 \n",
"L 2253 4666 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-34\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_3\">\n",
" <g id=\"line2d_3\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"152.99196\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_3\">\n",
" <!-- −2 -->\n",
" <g transform=\"translate(145.620866 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-32\" d=\"M 1228 531 \n",
"L 3431 531 \n",
"L 3431 0 \n",
"L 469 0 \n",
"L 469 531 \n",
"Q 828 903 1448 1529 \n",
"Q 2069 2156 2228 2338 \n",
"Q 2531 2678 2651 2914 \n",
"Q 2772 3150 2772 3378 \n",
"Q 2772 3750 2511 3984 \n",
"Q 2250 4219 1831 4219 \n",
"Q 1534 4219 1204 4116 \n",
"Q 875 4013 500 3803 \n",
"L 500 4441 \n",
"Q 881 4594 1212 4672 \n",
"Q 1544 4750 1819 4750 \n",
"Q 2544 4750 2975 4387 \n",
"Q 3406 4025 3406 3419 \n",
"Q 3406 3131 3298 2873 \n",
"Q 3191 2616 2906 2266 \n",
"Q 2828 2175 2409 1742 \n",
"Q 1991 1309 1228 531 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(83.789062 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_4\">\n",
" <g id=\"line2d_4\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"193.573778\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_4\">\n",
" <!-- 0 -->\n",
" <g transform=\"translate(190.392528 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-30\" d=\"M 2034 4250 \n",
"Q 1547 4250 1301 3770 \n",
"Q 1056 3291 1056 2328 \n",
"Q 1056 1369 1301 889 \n",
"Q 1547 409 2034 409 \n",
"Q 2525 409 2770 889 \n",
"Q 3016 1369 3016 2328 \n",
"Q 3016 3291 2770 3770 \n",
"Q 2525 4250 2034 4250 \n",
"z\n",
"M 2034 4750 \n",
"Q 2819 4750 3233 4129 \n",
"Q 3647 3509 3647 2328 \n",
"Q 3647 1150 3233 529 \n",
"Q 2819 -91 2034 -91 \n",
"Q 1250 -91 836 529 \n",
"Q 422 1150 422 2328 \n",
"Q 422 3509 836 4129 \n",
"Q 1250 4750 2034 4750 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-30\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_5\">\n",
" <g id=\"line2d_5\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"234.155597\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_5\">\n",
" <!-- 2 -->\n",
" <g transform=\"translate(230.974347 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-32\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_6\">\n",
" <g id=\"line2d_6\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"274.737415\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_6\">\n",
" <!-- 4 -->\n",
" <g transform=\"translate(271.556165 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-34\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_7\">\n",
" <g id=\"line2d_7\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"315.319233\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_7\">\n",
" <!-- 6 -->\n",
" <g transform=\"translate(312.137983 287.910437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-36\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"xtick_8\">\n",
" <g id=\"line2d_8\">\n",
" <g>\n",
" <use xlink:href=\"#mc8e19cfe9e\" x=\"355.901051\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_8\">\n",
" <!-- 8 -->\n",
" <g transform=\"translate(352.719801 287.910437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-38\" d=\"M 2034 2216 \n",
"Q 1584 2216 1326 1975 \n",
"Q 1069 1734 1069 1313 \n",
"Q 1069 891 1326 650 \n",
"Q 1584 409 2034 409 \n",
"Q 2484 409 2743 651 \n",
"Q 3003 894 3003 1313 \n",
"Q 3003 1734 2745 1975 \n",
"Q 2488 2216 2034 2216 \n",
"z\n",
"M 1403 2484 \n",
"Q 997 2584 770 2862 \n",
"Q 544 3141 544 3541 \n",
"Q 544 4100 942 4425 \n",
"Q 1341 4750 2034 4750 \n",
"Q 2731 4750 3128 4425 \n",
"Q 3525 4100 3525 3541 \n",
"Q 3525 3141 3298 2862 \n",
"Q 3072 2584 2669 2484 \n",
"Q 3125 2378 3379 2068 \n",
"Q 3634 1759 3634 1313 \n",
"Q 3634 634 3220 271 \n",
"Q 2806 -91 2034 -91 \n",
"Q 1263 -91 848 271 \n",
"Q 434 634 434 1313 \n",
"Q 434 1759 690 2068 \n",
"Q 947 2378 1403 2484 \n",
"z\n",
"M 1172 3481 \n",
"Q 1172 3119 1398 2916 \n",
"Q 1625 2713 2034 2713 \n",
"Q 2441 2713 2670 2916 \n",
"Q 2900 3119 2900 3481 \n",
"Q 2900 3844 2670 4047 \n",
"Q 2441 4250 2034 4250 \n",
"Q 1625 4250 1398 4047 \n",
"Q 1172 3844 1172 3481 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-38\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"matplotlib.axis_2\">\n",
" <g id=\"ytick_1\">\n",
" <g id=\"line2d_9\">\n",
" <defs>\n",
" <path id=\"m0577ed6c04\" d=\"M 0 0 \n",
"L -3.5 0 \n",
"\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </defs>\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"266.103273\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_9\">\n",
" <!-- −20 -->\n",
" <g transform=\"translate(7.2 269.902491) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-2212\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(83.789062 0)\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(147.412109 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_2\">\n",
" <g id=\"line2d_10\">\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"217.230545\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_10\">\n",
" <!-- 0 -->\n",
" <g transform=\"translate(21.942187 221.029764) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-30\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_3\">\n",
" <g id=\"line2d_11\">\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"168.357818\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_11\">\n",
" <!-- 20 -->\n",
" <g transform=\"translate(15.579687 172.157037) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-32\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_4\">\n",
" <g id=\"line2d_12\">\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"119.485091\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_12\">\n",
" <!-- 40 -->\n",
" <g transform=\"translate(15.579687 123.28431) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-34\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_5\">\n",
" <g id=\"line2d_13\">\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"70.612364\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_13\">\n",
" <!-- 60 -->\n",
" <g transform=\"translate(15.579687 74.411582) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-36\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"ytick_6\">\n",
" <g id=\"line2d_14\">\n",
" <g>\n",
" <use xlink:href=\"#m0577ed6c04\" x=\"35.304688\" y=\"21.739636\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"text_14\">\n",
" <!-- 80 -->\n",
" <g transform=\"translate(15.579687 25.538855) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-38\"/>\n",
" <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(63.623047 0)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <g id=\"line2d_15\">\n",
" <path d=\"M 51.537415 217.230545 \n",
"L 54.816754 217.230545 \n",
"L 58.096092 217.230545 \n",
"L 61.375431 217.230545 \n",
"L 64.65477 217.230545 \n",
"L 67.934109 217.230545 \n",
"L 71.213448 217.230545 \n",
"L 74.492787 217.230545 \n",
"L 77.772126 217.230545 \n",
"L 81.051464 217.230545 \n",
"L 84.330803 217.230545 \n",
"L 87.610142 217.230545 \n",
"L 90.889481 217.230545 \n",
"L 94.16882 217.230545 \n",
"L 97.448159 217.230545 \n",
"L 100.727497 217.230545 \n",
"L 104.006836 217.230545 \n",
"L 107.286175 217.230545 \n",
"L 110.565514 217.230545 \n",
"L 113.844853 217.230545 \n",
"L 117.124192 217.230545 \n",
"L 120.40353 217.230545 \n",
"L 123.682869 217.230545 \n",
"L 126.962208 217.230545 \n",
"L 130.241547 217.230545 \n",
"L 133.520886 217.230545 \n",
"L 136.800225 217.230545 \n",
"L 140.079564 217.230545 \n",
"L 143.358902 217.230545 \n",
"L 146.638241 217.230545 \n",
"L 149.91758 217.230545 \n",
"L 153.196919 217.230545 \n",
"L 156.476258 217.230545 \n",
"L 159.755597 217.230545 \n",
"L 163.034935 217.230545 \n",
"L 166.314274 217.230545 \n",
"L 169.593613 217.230545 \n",
"L 172.872952 217.230545 \n",
"L 176.152291 217.230545 \n",
"L 179.43163 217.230545 \n",
"L 182.710968 217.230545 \n",
"L 185.990307 217.230545 \n",
"L 189.269646 217.230545 \n",
"L 192.548985 217.230545 \n",
"L 195.828324 217.230545 \n",
"L 199.107663 217.230545 \n",
"L 202.387002 217.230545 \n",
"L 205.66634 217.230545 \n",
"L 208.945679 217.230545 \n",
"L 212.225018 217.230545 \n",
"L 215.504357 217.230545 \n",
"L 218.783696 217.230545 \n",
"L 222.063035 217.230545 \n",
"L 225.342373 217.230545 \n",
"L 228.621712 217.230545 \n",
"L 231.901051 217.230545 \n",
"L 235.18039 217.230545 \n",
"L 238.459729 217.230545 \n",
"L 241.739068 217.230545 \n",
"L 245.018407 217.230545 \n",
"L 248.297745 217.230545 \n",
"L 251.577084 217.230545 \n",
"L 254.856423 217.230545 \n",
"L 258.135762 217.230545 \n",
"L 261.415101 217.230545 \n",
"L 264.69444 217.230545 \n",
"L 267.973778 217.230545 \n",
"L 271.253117 217.230545 \n",
"L 274.532456 217.230545 \n",
"L 277.811795 217.230545 \n",
"L 281.091134 217.230545 \n",
"L 284.370473 217.230545 \n",
"L 287.649811 217.230545 \n",
"L 290.92915 217.230545 \n",
"L 294.208489 217.230545 \n",
"L 297.487828 217.230545 \n",
"L 300.767167 217.230545 \n",
"L 304.046506 217.230545 \n",
"L 307.325845 217.230545 \n",
"L 310.605183 217.230545 \n",
"L 313.884522 217.230545 \n",
"L 317.163861 217.230545 \n",
"L 320.4432 217.230545 \n",
"L 323.722539 217.230545 \n",
"L 327.001878 217.230545 \n",
"L 330.281216 217.230545 \n",
"L 333.560555 217.230545 \n",
"L 336.839894 217.230545 \n",
"L 340.119233 217.230545 \n",
"L 343.398572 217.230545 \n",
"L 346.677911 217.230545 \n",
"L 349.957249 217.230545 \n",
"L 353.236588 217.230545 \n",
"L 356.515927 217.230545 \n",
"L 359.795266 217.230545 \n",
"L 363.074605 217.230545 \n",
"L 366.353944 217.230545 \n",
"L 369.633283 217.230545 \n",
"L 372.912621 217.230545 \n",
"L 376.19196 217.230545 \n",
"\" clip-path=\"url(#p1e332790a2)\" style=\"fill: none; stroke: #000000; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"line2d_16\">\n",
" <path d=\"M 51.537415 19.296 \n",
"L 54.816754 26.340933 \n",
"L 58.096092 33.258212 \n",
"L 61.375431 40.047836 \n",
"L 64.65477 46.709805 \n",
"L 67.934109 53.24412 \n",
"L 71.213448 59.650781 \n",
"L 74.492787 65.929787 \n",
"L 77.772126 72.081138 \n",
"L 81.051464 78.104835 \n",
"L 84.330803 84.000878 \n",
"L 87.610142 89.769266 \n",
"L 90.889481 95.409999 \n",
"L 94.16882 100.923078 \n",
"L 97.448159 106.308503 \n",
"L 100.727497 111.566273 \n",
"L 104.006836 116.696388 \n",
"L 107.286175 121.698849 \n",
"L 110.565514 126.573656 \n",
"L 113.844853 131.320808 \n",
"L 117.124192 135.940305 \n",
"L 120.40353 140.432148 \n",
"L 123.682869 144.796337 \n",
"L 126.962208 149.032871 \n",
"L 130.241547 153.14175 \n",
"L 133.520886 157.122975 \n",
"L 136.800225 160.976545 \n",
"L 140.079564 164.702461 \n",
"L 143.358902 168.300723 \n",
"L 146.638241 171.77133 \n",
"L 149.91758 175.114282 \n",
"L 153.196919 178.32958 \n",
"L 156.476258 181.417223 \n",
"L 159.755597 184.377212 \n",
"L 163.034935 187.209546 \n",
"L 166.314274 189.914226 \n",
"L 169.593613 192.491252 \n",
"L 172.872952 194.940623 \n",
"L 176.152291 197.262339 \n",
"L 179.43163 199.456401 \n",
"L 182.710968 201.522808 \n",
"L 185.990307 203.461561 \n",
"L 189.269646 205.272659 \n",
"L 192.548985 206.956103 \n",
"L 195.828324 208.511892 \n",
"L 199.107663 209.940027 \n",
"L 202.387002 211.240507 \n",
"L 205.66634 212.413333 \n",
"L 208.945679 213.458504 \n",
"L 212.225018 214.376021 \n",
"L 215.504357 215.165883 \n",
"L 218.783696 215.828091 \n",
"L 222.063035 216.362644 \n",
"L 225.342373 216.769543 \n",
"L 228.621712 217.048787 \n",
"L 231.901051 217.200377 \n",
"L 235.18039 217.224312 \n",
"L 238.459729 217.120593 \n",
"L 241.739068 216.889219 \n",
"L 245.018407 216.530191 \n",
"L 248.297745 216.043508 \n",
"L 251.577084 215.429171 \n",
"L 254.856423 214.687179 \n",
"L 258.135762 213.817533 \n",
"L 261.415101 212.820232 \n",
"L 264.69444 211.695277 \n",
"L 267.973778 210.442667 \n",
"L 271.253117 209.062402 \n",
"L 274.532456 207.554483 \n",
"L 277.811795 205.91891 \n",
"L 281.091134 204.155682 \n",
"L 284.370473 202.2648 \n",
"L 287.649811 200.246263 \n",
"L 290.92915 198.100072 \n",
"L 294.208489 195.826226 \n",
"L 297.487828 193.424725 \n",
"L 300.767167 190.89557 \n",
"L 304.046506 188.238761 \n",
"L 307.325845 185.454297 \n",
"L 310.605183 182.542179 \n",
"L 313.884522 179.502406 \n",
"L 317.163861 176.334978 \n",
"L 320.4432 173.039896 \n",
"L 323.722539 169.61716 \n",
"L 327.001878 166.066769 \n",
"L 330.281216 162.388723 \n",
"L 333.560555 158.583023 \n",
"L 336.839894 154.649669 \n",
"L 340.119233 150.58866 \n",
"L 343.398572 146.399996 \n",
"L 346.677911 142.083678 \n",
"L 349.957249 137.639706 \n",
"L 353.236588 133.068079 \n",
"L 356.515927 128.368797 \n",
"L 359.795266 123.541861 \n",
"L 363.074605 118.587271 \n",
"L 366.353944 113.505026 \n",
"L 369.633283 108.295126 \n",
"L 372.912621 102.957572 \n",
"L 376.19196 97.492364 \n",
"\" clip-path=\"url(#p1e332790a2)\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"line2d_17\">\n",
" <path d=\"M 51.537415 261.216 \n",
"L 54.816754 260.426138 \n",
"L 58.096092 259.636275 \n",
"L 61.375431 258.846413 \n",
"L 64.65477 258.056551 \n",
"L 67.934109 257.266689 \n",
"L 71.213448 256.476826 \n",
"L 74.492787 255.686964 \n",
"L 77.772126 254.897102 \n",
"L 81.051464 254.10724 \n",
"L 84.330803 253.317377 \n",
"L 87.610142 252.527515 \n",
"L 90.889481 251.737653 \n",
"L 94.16882 250.947791 \n",
"L 97.448159 250.157928 \n",
"L 100.727497 249.368066 \n",
"L 104.006836 248.578204 \n",
"L 107.286175 247.788342 \n",
"L 110.565514 246.998479 \n",
"L 113.844853 246.208617 \n",
"L 117.124192 245.418755 \n",
"L 120.40353 244.628893 \n",
"L 123.682869 243.83903 \n",
"L 126.962208 243.049168 \n",
"L 130.241547 242.259306 \n",
"L 133.520886 241.469444 \n",
"L 136.800225 240.679581 \n",
"L 140.079564 239.889719 \n",
"L 143.358902 239.099857 \n",
"L 146.638241 238.309994 \n",
"L 149.91758 237.520132 \n",
"L 153.196919 236.73027 \n",
"L 156.476258 235.940408 \n",
"L 159.755597 235.150545 \n",
"L 163.034935 234.360683 \n",
"L 166.314274 233.570821 \n",
"L 169.593613 232.780959 \n",
"L 172.872952 231.991096 \n",
"L 176.152291 231.201234 \n",
"L 179.43163 230.411372 \n",
"L 182.710968 229.62151 \n",
"L 185.990307 228.831647 \n",
"L 189.269646 228.041785 \n",
"L 192.548985 227.251923 \n",
"L 195.828324 226.462061 \n",
"L 199.107663 225.672198 \n",
"L 202.387002 224.882336 \n",
"L 205.66634 224.092474 \n",
"L 208.945679 223.302612 \n",
"L 212.225018 222.512749 \n",
"L 215.504357 221.722887 \n",
"L 218.783696 220.933025 \n",
"L 222.063035 220.143163 \n",
"L 225.342373 219.3533 \n",
"L 228.621712 218.563438 \n",
"L 231.901051 217.773576 \n",
"L 235.18039 216.983713 \n",
"L 238.459729 216.193851 \n",
"L 241.739068 215.403989 \n",
"L 245.018407 214.614127 \n",
"L 248.297745 213.824264 \n",
"L 251.577084 213.034402 \n",
"L 254.856423 212.24454 \n",
"L 258.135762 211.454678 \n",
"L 261.415101 210.664815 \n",
"L 264.69444 209.874953 \n",
"L 267.973778 209.085091 \n",
"L 271.253117 208.295229 \n",
"L 274.532456 207.505366 \n",
"L 277.811795 206.715504 \n",
"L 281.091134 205.925642 \n",
"L 284.370473 205.13578 \n",
"L 287.649811 204.345917 \n",
"L 290.92915 203.556055 \n",
"L 294.208489 202.766193 \n",
"L 297.487828 201.976331 \n",
"L 300.767167 201.186468 \n",
"L 304.046506 200.396606 \n",
"L 307.325845 199.606744 \n",
"L 310.605183 198.816882 \n",
"L 313.884522 198.027019 \n",
"L 317.163861 197.237157 \n",
"L 320.4432 196.447295 \n",
"L 323.722539 195.657433 \n",
"L 327.001878 194.86757 \n",
"L 330.281216 194.077708 \n",
"L 333.560555 193.287846 \n",
"L 336.839894 192.497983 \n",
"L 340.119233 191.708121 \n",
"L 343.398572 190.918259 \n",
"L 346.677911 190.128397 \n",
"L 349.957249 189.338534 \n",
"L 353.236588 188.548672 \n",
"L 356.515927 187.75881 \n",
"L 359.795266 186.968948 \n",
"L 363.074605 186.179085 \n",
"L 366.353944 185.389223 \n",
"L 369.633283 184.599361 \n",
"L 372.912621 183.809499 \n",
"L 376.19196 183.019636 \n",
"\" clip-path=\"url(#p1e332790a2)\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_3\">\n",
" <path d=\"M 35.304688 273.312 \n",
"L 35.304688 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_4\">\n",
" <path d=\"M 392.424688 273.312 \n",
"L 392.424688 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_5\">\n",
" <path d=\"M 35.304688 273.312 \n",
"L 392.424688 273.312 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"patch_6\">\n",
" <path d=\"M 35.304688 7.2 \n",
"L 392.424688 7.2 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"legend_1\">\n",
" <g id=\"patch_7\">\n",
" <path d=\"M 286.724688 60.05625 \n",
"L 385.424688 60.05625 \n",
"Q 387.424688 60.05625 387.424688 58.05625 \n",
"L 387.424688 14.2 \n",
"Q 387.424688 12.2 385.424688 12.2 \n",
"L 286.724688 12.2 \n",
"Q 284.724688 12.2 284.724688 14.2 \n",
"L 284.724688 58.05625 \n",
"Q 284.724688 60.05625 286.724688 60.05625 \n",
"z\n",
"\" style=\"fill: #ffffff; opacity: 0.8; stroke: #cccccc; stroke-linejoin: miter\"/>\n",
" </g>\n",
" <g id=\"line2d_18\">\n",
" <path d=\"M 288.724688 20.298437 \n",
"L 298.724688 20.298437 \n",
"L 308.724688 20.298437 \n",
"\" style=\"fill: none; stroke: #000000; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"text_15\">\n",
" <!-- 0 -->\n",
" <g transform=\"translate(316.724688 23.798437) scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-30\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"line2d_19\">\n",
" <path d=\"M 288.724688 35.798437 \n",
"L 298.724688 35.798437 \n",
"L 308.724688 35.798437 \n",
"\" style=\"fill: none; stroke: #1f77b4; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"text_16\">\n",
" <!-- $f(x) = (x-2)^2$ -->\n",
" <g transform=\"translate(316.724688 39.298437) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"DejaVuSans-Oblique-66\" d=\"M 3059 4863 \n",
"L 2969 4384 \n",
"L 2419 4384 \n",
"Q 2106 4384 1964 4261 \n",
"Q 1822 4138 1753 3809 \n",
"L 1691 3500 \n",
"L 2638 3500 \n",
"L 2553 3053 \n",
"L 1606 3053 \n",
"L 1013 0 \n",
"L 434 0 \n",
"L 1031 3053 \n",
"L 481 3053 \n",
"L 563 3500 \n",
"L 1113 3500 \n",
"L 1159 3744 \n",
"Q 1278 4363 1576 4613 \n",
"Q 1875 4863 2516 4863 \n",
"L 3059 4863 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-28\" d=\"M 1984 4856 \n",
"Q 1566 4138 1362 3434 \n",
"Q 1159 2731 1159 2009 \n",
"Q 1159 1288 1364 580 \n",
"Q 1569 -128 1984 -844 \n",
"L 1484 -844 \n",
"Q 1016 -109 783 600 \n",
"Q 550 1309 550 2009 \n",
"Q 550 2706 781 3412 \n",
"Q 1013 4119 1484 4856 \n",
"L 1984 4856 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-Oblique-78\" d=\"M 3841 3500 \n",
"L 2234 1784 \n",
"L 3219 0 \n",
"L 2559 0 \n",
"L 1819 1388 \n",
"L 531 0 \n",
"L -166 0 \n",
"L 1556 1844 \n",
"L 641 3500 \n",
"L 1300 3500 \n",
"L 1972 2234 \n",
"L 3144 3500 \n",
"L 3841 3500 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-29\" d=\"M 513 4856 \n",
"L 1013 4856 \n",
"Q 1481 4119 1714 3412 \n",
"Q 1947 2706 1947 2009 \n",
"Q 1947 1309 1714 600 \n",
"Q 1481 -109 1013 -844 \n",
"L 513 -844 \n",
"Q 928 -128 1133 580 \n",
"Q 1338 1288 1338 2009 \n",
"Q 1338 2731 1133 3434 \n",
"Q 928 4138 513 4856 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" <path id=\"DejaVuSans-3d\" d=\"M 678 2906 \n",
"L 4684 2906 \n",
"L 4684 2381 \n",
"L 678 2381 \n",
"L 678 2906 \n",
"z\n",
"M 678 1631 \n",
"L 4684 1631 \n",
"L 4684 1100 \n",
"L 678 1100 \n",
"L 678 1631 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-66\" transform=\"translate(0 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-28\" transform=\"translate(35.205078 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(74.21875 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-29\" transform=\"translate(133.398438 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-3d\" transform=\"translate(191.894531 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-28\" transform=\"translate(295.166016 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(334.179688 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-2212\" transform=\"translate(412.841797 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(516.113281 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-29\" transform=\"translate(579.736328 0.765625)\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(619.707031 39.046875) scale(0.7)\"/>\n",
" </g>\n",
" </g>\n",
" <g id=\"line2d_20\">\n",
" <path d=\"M 288.724688 50.476562 \n",
"L 298.724688 50.476562 \n",
"L 308.724688 50.476562 \n",
"\" style=\"fill: none; stroke: #ff7f0e; stroke-width: 1.5; stroke-linecap: square\"/>\n",
" </g>\n",
" <g id=\"text_17\">\n",
" <!-- $f'(x)=2 x - 4$ -->\n",
" <g transform=\"translate(316.724688 53.976562) scale(0.1 -0.1)\">\n",
" <defs>\n",
" <path id=\"Cmsy10-30\" d=\"M 225 347 \n",
"Q 184 359 184 409 \n",
"L 966 3316 \n",
"Q 1003 3434 1093 3506 \n",
"Q 1184 3578 1300 3578 \n",
"Q 1450 3578 1564 3479 \n",
"Q 1678 3381 1678 3231 \n",
"Q 1678 3166 1644 3084 \n",
"L 488 319 \n",
"Q 466 275 428 275 \n",
"Q 394 275 320 306 \n",
"Q 247 338 225 347 \n",
"z\n",
"\" transform=\"scale(0.015625)\"/>\n",
" </defs>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-66\" transform=\"translate(0 0.584375)\"/>\n",
" <use xlink:href=\"#Cmsy10-30\" transform=\"translate(42.652786 38.865625) scale(0.7)\"/>\n",
" <use xlink:href=\"#DejaVuSans-28\" transform=\"translate(64.630326 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(103.643997 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-29\" transform=\"translate(162.823685 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-3d\" transform=\"translate(221.319779 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-32\" transform=\"translate(324.591263 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(388.21431 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-2212\" transform=\"translate(466.876419 0.584375)\"/>\n",
" <use xlink:href=\"#DejaVuSans-34\" transform=\"translate(570.147904 0.584375)\"/>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" </g>\n",
" <defs>\n",
" <clipPath id=\"p1e332790a2\">\n",
" <rect x=\"35.304688\" y=\"7.2\" width=\"357.12\" height=\"266.112\"/>\n",
" </clipPath>\n",
" </defs>\n",
"</svg>\n"
],
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def fP(x): #Defining the derivative of f(x) manually\n",
" return 2*x-4\n",
"\n",
"y_axis_vals_p = fP(torch.tensor(x_axis_vals)).numpy()\n",
"\n",
"#First, lets draw a black line at 0, so that we can easily tell if something is positive or negative\n",
"sns.lineplot(x=x_axis_vals, y=[0.0]*len(x_axis_vals), label=\"0\", color='black')\n",
"sns.lineplot(x=x_axis_vals, y=y_axis_vals, label='$f(x) = (x-2)^2$')\n",
"sns.lineplot(x=x_axis_vals, y=y_axis_vals_p, label=\"$f'(x)=2 x - 4$\")"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.872628Z",
"start_time": "2021-03-22T05:33:02.868281Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"None\n"
]
}
],
"source": [
"x = torch.tensor([-3.5], requires_grad=True)\n",
"print(x.grad)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.879284Z",
"start_time": "2021-03-22T05:33:02.874597Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([30.2500], grad_fn=<PowBackward0>)\n"
]
}
],
"source": [
"value = f(x)\n",
"print(value)"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.887619Z",
"start_time": "2021-03-22T05:33:02.881506Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([-11.])\n"
]
}
],
"source": [
"value.backward()\n",
"print(x.grad)"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.906233Z",
"start_time": "2021-03-22T05:33:02.888975Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([2.0000])\n"
]
}
],
"source": [
"x = torch.tensor([-3.5], requires_grad=True)\n",
"\n",
"x_cur = x.clone()\n",
"x_prev = x_cur*100 #Make the initial \"previous\" solution larger\n",
"epsilon = 1e-5\n",
"eta = 0.1\n",
"\n",
"while torch.linalg.norm(x_cur-x_prev) > epsilon:\n",
" x_prev = x_cur.clone() #We need to make a clone here so that x_prev and x_cur don't point to the same object\n",
" \n",
" #Compute our function, gradient, and update\n",
" value = f(x)\n",
" value.backward()\n",
" x.data -= eta * x.grad\n",
" x.grad.zero_() #We need to zero out the old gradient, as py-torch will not do that for us\n",
" \n",
" #What are we currently now?\n",
" x_cur = x.data\n",
" \n",
"print(x_cur)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.911171Z",
"start_time": "2021-03-22T05:33:02.908110Z"
}
},
"outputs": [],
"source": [
"x_param = torch.nn.Parameter(torch.tensor([-3.5]), requires_grad=True)"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.916541Z",
"start_time": "2021-03-22T05:33:02.913522Z"
}
},
"outputs": [],
"source": [
"optimizer = torch.optim.SGD([x_param], lr=eta)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:02.933325Z",
"start_time": "2021-03-22T05:33:02.918744Z"
},
"tags": [
"remove_output"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([2.0000])\n"
]
}
],
"source": [
"for epoch in range(60):\n",
" optimizer.zero_grad() #x.grad.zero_()\n",
" loss_incurred = f(x_param)\n",
" loss_incurred.backward()\n",
" optimizer.step() #x.data -= eta * x.grad\n",
"print(x_param.data)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:18.679235Z",
"start_time": "2021-03-22T05:33:02.939654Z"
}
},
"outputs": [
{
"ename": "AttributeError",
"evalue": "module 'numpy' has no attribute '_no_nep50_warning'",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[64]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mtorch\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mdata\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Dataset\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01msklearn\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mdatasets\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m fetch_openml\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# Load data from https://www.openml.org/d/554\u001b[39;00m\n\u001b[32m 5\u001b[39m X, y = fetch_openml(\u001b[33m'\u001b[39m\u001b[33mmnist_784\u001b[39m\u001b[33m'\u001b[39m, version=\u001b[32m1\u001b[39m, return_X_y=\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\sklearn\\__init__.py:73\u001b[39m\n\u001b[32m 62\u001b[39m \u001b[38;5;66;03m# `_distributor_init` allows distributors to run custom init code.\u001b[39;00m\n\u001b[32m 63\u001b[39m \u001b[38;5;66;03m# For instance, for the Windows wheel, this is used to pre-load the\u001b[39;00m\n\u001b[32m 64\u001b[39m \u001b[38;5;66;03m# vcomp shared library runtime for OpenMP embedded in the sklearn/.libs\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 67\u001b[39m \u001b[38;5;66;03m# later is linked to the OpenMP runtime to make it possible to introspect\u001b[39;00m\n\u001b[32m 68\u001b[39m \u001b[38;5;66;03m# it and importing it first would fail if the OpenMP dll cannot be found.\u001b[39;00m\n\u001b[32m 69\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m ( \u001b[38;5;66;03m# noqa: F401 E402\u001b[39;00m\n\u001b[32m 70\u001b[39m __check_build,\n\u001b[32m 71\u001b[39m _distributor_init,\n\u001b[32m 72\u001b[39m )\n\u001b[32m---> \u001b[39m\u001b[32m73\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mbase\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m clone \u001b[38;5;66;03m# noqa: E402\u001b[39;00m\n\u001b[32m 74\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_show_versions\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m show_versions \u001b[38;5;66;03m# noqa: E402\u001b[39;00m\n\u001b[32m 76\u001b[39m _submodules = [\n\u001b[32m 77\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mcalibration\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 78\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mcluster\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 114\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mcompose\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 115\u001b[39m ]\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\sklearn\\base.py:19\u001b[39m\n\u001b[32m 17\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_config\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m config_context, get_config\n\u001b[32m 18\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mexceptions\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m InconsistentVersionWarning\n\u001b[32m---> \u001b[39m\u001b[32m19\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_metadata_requests\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m _MetadataRequester, _routing_enabled\n\u001b[32m 20\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_missing\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m is_scalar_nan\n\u001b[32m 21\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_param_validation\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m validate_parameter_constraints\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\sklearn\\utils\\__init__.py:9\u001b[39m\n\u001b[32m 7\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m metadata_routing\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_bunch\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Bunch\n\u001b[32m----> \u001b[39m\u001b[32m9\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_chunking\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m gen_batches, gen_even_slices\n\u001b[32m 11\u001b[39m \u001b[38;5;66;03m# Make _safe_indexing importable from here for backward compat as this particular\u001b[39;00m\n\u001b[32m 12\u001b[39m \u001b[38;5;66;03m# helper is considered semi-private and typically very useful for third-party\u001b[39;00m\n\u001b[32m 13\u001b[39m \u001b[38;5;66;03m# libraries that want to comply with scikit-learn's estimator API. In particular,\u001b[39;00m\n\u001b[32m 14\u001b[39m \u001b[38;5;66;03m# _safe_indexing was included in our public API documentation despite the leading\u001b[39;00m\n\u001b[32m 15\u001b[39m \u001b[38;5;66;03m# `_` in its name.\u001b[39;00m\n\u001b[32m 16\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_indexing\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[32m 17\u001b[39m _safe_indexing, \u001b[38;5;66;03m# noqa: F401\u001b[39;00m\n\u001b[32m 18\u001b[39m resample,\n\u001b[32m 19\u001b[39m shuffle,\n\u001b[32m 20\u001b[39m )\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\sklearn\\utils\\_chunking.py:11\u001b[39m\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n\u001b[32m 10\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_config\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m get_config\n\u001b[32m---> \u001b[39m\u001b[32m11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_param_validation\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Interval, validate_params\n\u001b[32m 14\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mchunk_generator\u001b[39m(gen, chunksize):\n\u001b[32m 15\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Chunk generator, ``gen`` into lists of length ``chunksize``. The last\u001b[39;00m\n\u001b[32m 16\u001b[39m \u001b[33;03m chunk may have a length less than ``chunksize``.\"\"\"\u001b[39;00m\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\sklearn\\utils\\_param_validation.py:14\u001b[39m\n\u001b[32m 11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumbers\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Integral, Real\n\u001b[32m 13\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m14\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01msparse\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m csr_matrix, issparse\n\u001b[32m 16\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_config\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m config_context, get_config\n\u001b[32m 17\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01mvalidation\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m _is_arraylike_not_scalar\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\sparse\\__init__.py:304\u001b[39m\n\u001b[32m 301\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mwarnings\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m_warnings\u001b[39;00m\n\u001b[32m 302\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mimportlib\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m_importlib\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m304\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_base\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m *\n\u001b[32m 305\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_csr\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m *\n\u001b[32m 306\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_csc\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m *\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\sparse\\_base.py:8\u001b[39m\n\u001b[32m 5\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n\u001b[32m 6\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01moperator\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m8\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_sputils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (asmatrix, check_reshape_kwargs, check_shape,\n\u001b[32m 9\u001b[39m get_sum_dtype, isdense, isscalarlike, _todata,\n\u001b[32m 10\u001b[39m matrix, validateaxis, getdtype, is_pydata_spmatrix)\n\u001b[32m 11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_sparse\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m SparseABC, issparse\n\u001b[32m 13\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_matrix\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m spmatrix\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\sparse\\_sputils.py:10\u001b[39m\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mmath\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m prod\n\u001b[32m 9\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01msparse\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01msp\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_util\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m np_long, np_ulong\n\u001b[32m 13\u001b[39m __all__ = [\u001b[33m'\u001b[39m\u001b[33mupcast\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33mgetdtype\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33mgetdata\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33misscalarlike\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33misintlike\u001b[39m\u001b[33m'\u001b[39m,\n\u001b[32m 14\u001b[39m \u001b[33m'\u001b[39m\u001b[33misshape\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33missequence\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33misdense\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33mismatrix\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33mget_sum_dtype\u001b[39m\u001b[33m'\u001b[39m,\n\u001b[32m 15\u001b[39m \u001b[33m'\u001b[39m\u001b[33mbroadcast_shapes\u001b[39m\u001b[33m'\u001b[39m]\n\u001b[32m 17\u001b[39m supported_dtypes = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc,\n\u001b[32m 18\u001b[39m np.uintc, np_long, np_ulong, np.longlong, np.ulonglong,\n\u001b[32m 19\u001b[39m np.float32, np.float64, np.longdouble,\n\u001b[32m 20\u001b[39m np.complex64, np.complex128, np.clongdouble]\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\_lib\\_util.py:14\u001b[39m\n\u001b[32m 11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mtyping\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Literal, TypeAlias, TypeVar\n\u001b[32m 13\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m14\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_array_api\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (Array, array_namespace, is_lazy_array,\n\u001b[32m 15\u001b[39m is_numpy, is_marray, xp_result_device,\n\u001b[32m 16\u001b[39m xp_size, xp_result_type)\n\u001b[32m 17\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_docscrape\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m FunctionDoc, Parameter\n\u001b[32m 18\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_sparse\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m issparse\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\_lib\\_array_api.py:25\u001b[39m\n\u001b[32m 22\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mtyping\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnpt\u001b[39;00m\n\u001b[32m 24\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m array_api_compat\n\u001b[32m---> \u001b[39m\u001b[32m25\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01marray_api_compat\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[32m 26\u001b[39m is_array_api_obj,\n\u001b[32m 27\u001b[39m is_lazy_array,\n\u001b[32m 28\u001b[39m size \u001b[38;5;28;01mas\u001b[39;00m xp_size,\n\u001b[32m 29\u001b[39m numpy \u001b[38;5;28;01mas\u001b[39;00m np_compat,\n\u001b[32m 30\u001b[39m device \u001b[38;5;28;01mas\u001b[39;00m xp_device,\n\u001b[32m 31\u001b[39m is_numpy_namespace \u001b[38;5;28;01mas\u001b[39;00m is_numpy,\n\u001b[32m 32\u001b[39m is_cupy_namespace \u001b[38;5;28;01mas\u001b[39;00m is_cupy,\n\u001b[32m 33\u001b[39m is_torch_namespace \u001b[38;5;28;01mas\u001b[39;00m is_torch,\n\u001b[32m 34\u001b[39m is_jax_namespace \u001b[38;5;28;01mas\u001b[39;00m is_jax,\n\u001b[32m 35\u001b[39m is_dask_namespace \u001b[38;5;28;01mas\u001b[39;00m is_dask,\n\u001b[32m 36\u001b[39m is_array_api_strict_namespace \u001b[38;5;28;01mas\u001b[39;00m is_array_api_strict\n\u001b[32m 37\u001b[39m )\n\u001b[32m 38\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_sparse\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m issparse\n\u001b[32m 39\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mscipy\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_lib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_docscrape\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m FunctionDoc\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\scipy\\_lib\\array_api_compat\\numpy\\__init__.py:4\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# ruff: noqa: PLC0414\u001b[39;00m\n\u001b[32m 2\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mtyping\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Final\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m * \u001b[38;5;66;03m# noqa: F403 # pyright: ignore[reportWildcardImportFromLibrary]\u001b[39;00m\n\u001b[32m 6\u001b[39m \u001b[38;5;66;03m# from numpy import * doesn't overwrite these builtin names\u001b[39;00m\n\u001b[32m 7\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;28mabs\u001b[39m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;28mabs\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\numpy\\testing\\__init__.py:11\u001b[39m\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01munittest\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m TestCase\n\u001b[32m 10\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m _private\n\u001b[32m---> \u001b[39m\u001b[32m11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_private\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m *\n\u001b[32m 12\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_private\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (_assert_valid_refcount, _gen_alignment_data)\n\u001b[32m 13\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m_private\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m extbuild\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\numpy\\testing\\_private\\utils.py:465\u001b[39m\n\u001b[32m 461\u001b[39m pprint.pprint(desired, msg)\n\u001b[32m 462\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(msg.getvalue())\n\u001b[32m--> \u001b[39m\u001b[32m465\u001b[39m \u001b[38;5;129m@np\u001b[39m\u001b[43m.\u001b[49m\u001b[43m_no_nep50_warning\u001b[49m()\n\u001b[32m 466\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34massert_almost_equal\u001b[39m(actual, desired, decimal=\u001b[32m7\u001b[39m, err_msg=\u001b[33m'\u001b[39m\u001b[33m'\u001b[39m, verbose=\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[32m 467\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 468\u001b[39m \u001b[33;03m Raises an AssertionError if two items are not equal up to desired\u001b[39;00m\n\u001b[32m 469\u001b[39m \u001b[33;03m precision.\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 533\u001b[39m \n\u001b[32m 534\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m 535\u001b[39m __tracebackhide__ = \u001b[38;5;28;01mTrue\u001b[39;00m \u001b[38;5;66;03m# Hide traceback for py.test\u001b[39;00m\n",
"\u001b[36mFile \u001b[39m\u001b[32md:\\app\\miniconda\\envs\\dpl\\Lib\\site-packages\\numpy\\__init__.py:795\u001b[39m, in \u001b[36m__getattr__\u001b[39m\u001b[34m(attr)\u001b[39m\n\u001b[32m 0\u001b[39m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
"\u001b[31mAttributeError\u001b[39m: module 'numpy' has no attribute '_no_nep50_warning'"
]
}
],
"source": [
"from torch.utils.data import Dataset\n",
"from sklearn.datasets import fetch_openml\n",
"\n",
"# Load data from https://www.openml.org/d/554\n",
"X, y = fetch_openml('mnist_784', version=1, return_X_y=True)\n",
"print(X.shape)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:18.684096Z",
"start_time": "2021-03-22T05:33:18.680539Z"
}
},
"outputs": [],
"source": [
"class SimpleDataset(Dataset):\n",
" \n",
" def __init__(self, X, y):\n",
" super(SimpleDataset, self).__init__()\n",
" self.X = X\n",
" self.y = y\n",
" \n",
" def __getitem__(self, index):\n",
" #This \"work\" could have gone in the constructor, but you should get into \n",
" inputs = torch.tensor(self.X[index,:], dtype=torch.float32)\n",
" targets = torch.tensor(int(self.y[index]), dtype=torch.int64)\n",
" return inputs, targets \n",
"\n",
" def __len__(self):\n",
" return self.X.shape[0]\n",
"#Now we can make a PyTorch dataset \n",
"dataset = SimpleDataset(X, y)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:18.698359Z",
"start_time": "2021-03-22T05:33:18.685197Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Length: 70000\n",
"Features: torch.Size([784])\n",
"Label of index 0: tensor(5)\n"
]
}
],
"source": [
"print(\"Length: \", len(dataset))\n",
"example, label = dataset[0]\n",
"print(\"Features: \", example.shape) #Will return 784\n",
"print(\"Label of index 0: \", label)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:18.934961Z",
"start_time": "2021-03-22T05:33:18.700260Z"
},
"max_h": 0.3,
"max_w": 0.9
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f3d87846150>"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"application/pdf": "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\n",
"image/png": "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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(example.reshape((28,28)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2021-03-22T05:33:18.943218Z",
"start_time": "2021-03-22T05:33:18.936102Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"56000 examples for training and 14000 for testing\n"
]
}
],
"source": [
"train_size = int(len(dataset)*0.8)\n",
"test_size = len(dataset)-train_size\n",
"\n",
"train_dataset, test_dataset = torch.utils.data.random_split(dataset, (train_size, test_size))\n",
"print(\"{} examples for training and {} for testing\".format(len(train_dataset), len(test_dataset)))"
]
}
],
"metadata": {
"author": "Why PyTorch?",
"celltoolbar": "Tags",
"kernelspec": {
"display_name": "dpl",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.14"
},
"latex_envs": {
"LaTeX_envs_menu_present": true,
"autoclose": false,
"autocomplete": false,
"bibliofile": "biblio.bib",
"cite_by": "apalike",
"current_citInitial": 1,
"eqLabelWithNumbers": true,
"eqNumInitial": 1,
"hotkeys": {
"equation": "Ctrl-E",
"itemize": "Ctrl-I"
},
"labels_anchors": false,
"latex_user_defs": false,
"report_style_numbering": false,
"user_envs_cfg": false
},
"latex_metadata": {
"title": "The Mechanics of Learning"
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Reference in New Issue View Git Blame Copy Permalink