From 190397a0edb9a36cf0748119e3a0330ed9acf09e Mon Sep 17 00:00:00 2001
From: Markus Holzer <markus.holzer@fau.de>
Date: Mon, 10 Oct 2022 13:36:31 +0200
Subject: [PATCH] Upgrade max SymPy
---
.../01_tutorial_getting_started.ipynb | 501 ++++--------------
setup.py | 2 +-
2 files changed, 94 insertions(+), 409 deletions(-)
diff --git a/doc/notebooks/01_tutorial_getting_started.ipynb b/doc/notebooks/01_tutorial_getting_started.ipynb
index 5cb9acd72..bceef66c5 100644
--- a/doc/notebooks/01_tutorial_getting_started.ipynb
+++ b/doc/notebooks/01_tutorial_getting_started.ipynb
@@ -70,7 +70,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "4.65 ms ± 22.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+ "4.92 ms ± 124 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
@@ -120,14 +120,12 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
- "<Figure size 216x216 with 1 Axes>"
+ "<Figure size 300x300 with 1 Axes>"
]
},
- "metadata": {
- "needs_background": "light"
- },
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -181,7 +179,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "951 µs ± 15 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
+ "1.01 ms ± 24.6 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
]
}
],
@@ -262,7 +260,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2}$"
],
@@ -295,7 +293,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAI0AAAAXCAYAAAA2o8yAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAABJ0AAASdAHeZh94AAAFBklEQVR4nO2aa4hVVRTHf44WTRmFREhkDyrsg5qVpkmKPSYrCUUrSLImNDKUNDNzylr9yVJTa7AwJCKtvpQivSYzNEJMC6V8ZGVYDRRYJo6iaC+dPqx983rmzuPM3feRzB+Gzex99tr/tc66e6299unU2NhIBzqQBl3ymSxpInA/cEHo2g7MMrO6PHkVFJJqgFFAT+BP4HOgxsy+LimxMkFr9qnIU/4vwAzgSqAf8AnwjqQ+ecotNIYCi4BBwHXAP8BqSd1KSaqMMJQW7NMpdniStBf3ysVRBRcQkroC+4GRZvZ+qfmUG5L2ySs8JQR3Bu4AugLrY8ktEk7Hd929pSbSVkgaDEzBd4NuOPdtQK2ZfRh5uePsk7fTSOoNbABOAQ7g3rgtX7lFRi2wGY/dZQ9JM4GngT3AB8Au4Czgcjy0xHaaWrLsE2On2QH0Bc4ERgOvSxqaNqmUVA28BlxrZp9G4NXWdecBQ4DBZnakSGtW005dJd2OO8xqYJSZHUiMnxSJZkZeE/t0STzwMVAFjDazFVn9nXAl7wHmmtmMzJiZ/QXsDP9uktQf3zbHxyTfGtrDXdIC4C785e1MiETSw8B8YJqZLcgx3hPYCnxhZkMiq9QEkiqAucAhYEzSYQDM7O8c81LbJozntE/y9PQIcBSYFXKUDOYHwa8kBedABR6qio1U3CUt5JhBvmlG5rrQDmxm/EWgMzApH+IpMAi4EA8/DZKGS3pU0mRJV7cwL/V7bck+x+00ZrZF0htB0FhgiaTHgKnA28CEhOA5QB3wM54sjcFj6vDW9Y+LNNwlLcINMhLYK6l7GDpoZgezxH4JHAYGJNcLYaIKWGhmW+NrlBP9Q/tb4NY7wWktcJuZ/Z7d34732qJ9ctVpZgJ/AE9JmgQ8A6wCxprZ0cSz3YE38bxmTVDqZjNb2SYTxEdbuT+AO/kaPInM/E3LFha2+o1AD0nnZPolnQY8D+wGniyYNk1xdmgnAJXADbgevXA9hwDLmpmb5r22aJ+cdRpJs/GiHfjxucrMDqVWsRlIqgfOTzFlqZlVt1F2VO6SngVqyMoHJM0FpgP3mtmSVubXE0lXSc9xLNRcYWZbssYqge+Bc4FBZrYhx/wotmnu9JS9vY2L6TABtfhpKxt9gRHAUqA+MbY5hezY3D8L7QBghaRLgYfwMsPSNsyvJZ6uDaH9MdthAMzssKRVwDjgqsAviSi2aeI0ku7EE6Rf8fAzGd+uosHManOsW40bckl7j9wF4r4eaORYMvwSnvxONLNWy+mRdd0R2n3NjGecqjLHmtFsc1xOI+kW3Pu3A32A74Dx4ddV1igUdzNrAL4F+kkaA1wPLDazr/Kk3B6sxe+BLpF0co7xXqGtz+6MbZv/nEbSNcBy/BLyxpCBP4HvRnPaI7xYKAL3dcCpwGK8CjszgszUMLM9wFvAGSQScElVwDD8juijrP7otqkIgi/Dy9H78eRoVyC5HNgEjAh3HWWHInHP5DVd8cvYUt5RTcWLqY9LWitpvqRlwErgCHCfme2DwtmmQtLF+NGrERhmZj8knqkJ7by0wguNInL/KbQbgVfzlJUXzGw3npS/APQAHsQ/X6jDS/3LoLC2if5pxIkISe/hBcuBZrax1HxKjXw/wjrhEZLfW4GXOxzGEe17mhMJks7Dr0QuAu7GTx3TS0qqjNDhNLlxEzAbr4e8C0wpQIHzf4uOnKYDqfEvcwBygSAVIEgAAAAASUVORK5CYII=\n",
"text/latex": [
"$\\displaystyle x^{3} + x^{2} y + 6 x^{2}$"
],
@@ -320,7 +318,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 6\\right)$"
],
@@ -345,7 +343,7 @@
"outputs": [
{
"data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAANoAAAAYCAYAAACcPeNkAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAGaUlEQVR4Ae2c7ZHUOBCGvVsEAGwEQAZ8RABkwEcELBlA7b/9R0EGQAR3kAEQAbAZHBfBcZPB8j4et9B4JI9t2fKYcVdpJbWkVuuVWmrJA0eXl5dFVzo/P7+qNmdVu5tV/Ez8VVdZS/0FgT8FgSa7uNJzkK8l9Lm1Vfqt0t8VbhlviRcEDhCBqF0c9wTjVMb1wGv7Wumb4t32eEtyQeDQEIjaRV9D4zT7loqiDNPczlRRB9E+Ba+UtlOAOzd9K4yidtHL0ATCOwX/PkYHP8S7aDspqvtCdZcTsCVgA+CFxwHmk5P02Jp38a4q+Bvv3ujbFjDpH7WLXobmd1yB9ki8Oz6/Ka021D9R/LGp3lK2RmAIvCTjM9IUn+4Brl+kx6XC9yr8I5244/803cTfJ31Nrdax9GczcXaRZGgSxg7E/eyO0v4JF1VI9coXS8Uvo5WWAofAkHhJ1hsJfl7JdH1MkMCgWC8sRtYDG+7WGtojfaVee5LeW3bR99WxqIS9VPwQFao88Y8dKmGYvFJmIenDow1uyLssHQ7fydB4gT0y3atxV5UHwPRCMh637Hcf9G2pqrODLbvodaIJJCwWAN4qfZugNCeUO/qVjtET1c+56NkxCXOlQfGqsEdmCibZMJ2TvtI1ahd9TzT8acAmdqSOGndJleOz7jrxnLxDT4yIF3PwRCHnhpcynXPRN2oXztA0qRiOXZTvKf1MAQt9qgB9VZ3y8ULxtTWr81/czPKSG2rZRYdQ+zF4lU64WitPvsMCnleHSz3Eh/sP4ruxKs2pjxuLHLCGnorf9Ig0Fl7ohezJDE3jZq2Bw4kC6+yVeLFX68n0lU7omGwXxxJixFftNwQxviq8V3igPC4hnbHYUumuBNhiDMnKoUOo3yBPY2cB/KvwCRwqLD4p/15pDKeoYnYyp7t4nOzUL5/TFZf4KQZfnoANZ/hNNBZezAFjm4oY998VDqwvAi+QbEQhmlJfN69SrLddlIamAWKxviGtlMfNsx3veq1c2V4EwMF7XEYduij+QZX5Puh/hjDjACOIOh9Vp+4Ss3iYJAwSg7mrtLVVtqRdj0Jj4cUcTGZowuGhguFXKA12nFoxPCbRV3oNZhfmOn6rBlvOvv7gzvAyVIKhuO0LkbWPxRisA7hWKUkH6cgkhXZE+ixUHro/Rl+/VJ9FjpFwwjsSH6MzF5pyFiw73QapHrLh4R5yurFY/lfMguJUxDg3ZItXp7HwYmEzvkaSfoNi2tjZ+u6OB8ULcX3TmkrfpDXpj7c0NA3swmcqzUX5VY03ajZVB7UPGVIhPiczk7drUdfHZzv+f/UCL291YpsHVTFGiM3rTAF98B447XAjg3qrvJHULmXOmgzY9RvTTfy+mBZqyyZzXXHsbhraACbRVzqmYOxwJHG8kVNGwjkVGKxzl8Tj5zEhAOrNd+XZ1XfKGVmHXTpaue2qTf8iweo0jQnXszRIxZxstxSO1AkGdqq0GaL168dj4YW+yJ6CcKNDeGFMhfCoL27YU+pL/+iVZBfHEoARcdlHEMQCWClviwjemfIrEomETDsFnCjJzqmD67cpUY2XSWdhbJHKHylQDi684G2QygxP7nAYk71clfVUzv2XzSwov6y0dqfGwItF7c9v1V2WiFM8tHmBF251iLLrKx0HXZOcaAyQ8BPhxAqOxKNs6w7iKnRLsDD5dFCnnDrU+27KczfF7awbCa4fY4HuK/ABGGPyiTq8LtriYbMCX5/IW7nPt/RYeJV3cOskc8yPHDYePZS3HzvH3gKm0HfQNXlFIDPR7K4ILjRofgvHCQcYPFtjgM6NpE4C/aW27PB1yqlDve9oXuPG7buhCtynwMM+TbBYyhNBMY8eLATcQk43iFOIvBkRfDA+FU9RSSf6i9ymk2UsvJjrXnfDter9/zJeBcMTQZxWbO43xDf84Ps0hb6DrsmjPv+VgY9A17TAZLE+VmwnQlcRneqrn94X904djVR5aLwkj02AjTTkvrUaRU5M56ZvDEBcx9yES5VzN2WXjO2Uucfep7+h8Sq/7/VRxGuTE9O56evB9DuZ/USja+1SPPHioja5Tb+1PPDUUHhJDqcZbu/W480+Qjw3fZswnOJEQx8uvRsX4iYll7LB8ALznN5E6tTNTd/oeCc50dCm2q14Iu/6ITk6mD+5IBUvtedlj1+jzMKLmJu+u9beLyVaXHuoS3odAAAAAElFTkSuQmCC\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + \\cos{\\left(x \\right)} + 5\\right) + x^{2}$"
],
@@ -377,7 +375,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2} = 1$"
],
@@ -403,7 +401,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\left[ - x - 6 + \\frac{1}{x^{2}}\\right]$"
],
@@ -437,7 +435,7 @@
"outputs": [
{
"data": {
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"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2}$"
],
@@ -461,166 +459,11 @@
"metadata": {},
"outputs": [
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- "<title>Pow(Symbol('x'), Integer(2))_(1, 0)->Symbol('x')_(1, 0, 0)</title>\n",
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- "<!-- Pow(Symbol('x'), Integer(2))_(1, 0)->Integer(2)_(1, 0, 1) -->\n",
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- "<!-- Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('y')_(1, 1, 2) -->\n",
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- "<title>Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('y')_(1, 1, 2)</title>\n",
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- "</svg>\n"
- ],
- "text/plain": [
- "<graphviz.sources.Source at 0x7fc1288673a0>"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "graphviz is not installed. Visualizing the AST is not available\n"
+ ]
}
],
"source": [
@@ -662,7 +505,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\left( x^{2}, \\ x^{2} \\left(x + y + 5\\right)\\right)$"
],
@@ -719,7 +562,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAC0AAAAaCAYAAAAjZdWPAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAABJ0AAASdAHeZh94AAADAklEQVR4nM3YXYgWZRQH8N+bFW1fYEikRGwQUUHfdiPlReRFGhFEFNGFEBGJhQRChXA4UkEIQlQWWlBUF4HdeNG6EiRUYoFtHxSCShSxIS1BeFGItl3MvMvD7OzurO6+9L955vk/5zz858x5zpyZ3uTkpC7IzNXYjNuxHA9FxO5OzguMc+ZhexG+w8ZF0tIZ57aRmXkpXsT9WIHz8FxEbKnXByawDa2i8SHuwyf4AKewZ1Ci5sI00Zl5nUrwaESsG7ykudGW03fX48eDFDIfTEU6Mx9EWQ12ZubO+vr6iDg8UGWzoEyP35HYgKV4qeYncWTAumZFr6zTmbkEJ3A0Im4qDTPzYlxTT8dUNftT/BkRvw5GboXmQbwBQ/imxXYlPivm2+rxPaxfcGWzoCn6tnqcJjoi9qO32IK6oFk9+qLHBi1kPmiL9CS+bRpm5lIcxqqIOLb40sjM3TgQEdtLvix5PdyMIxFxomWPF7C3L3ghGqjM3FDvsRw/YlNEfF6YbMX+zHwnIv7qk2V6XItLtKRGZl6IJ/B2QZ9VA5WZD+NVvIxb8SVGMvOqvk1EfI+f8VjpW6bHjIcQ6/Avvig2HMFILeBMdD+LdyNiVz1/JjPvxVN4vrDbg0fxRp8oIz2b6DtxKCK6Nd9zIDPPV6XVvsbSPqxqcF/hjswc6hNTkY6Izar8asMwxs9WbIFlWILjDf447mlw46rWeAWO0f0j4AL8c+YaZ0TzyfVauL/rcSrSXUVPqPqRhcIETuOKBn+56dG/rB7/6BNdRY+pXvELgog4iUNY01hagwMN7kaMR8TUzcz05dLEKF7JzGURMcG0BgqGM/MW3Ruo7Xg/M79WlbsnVXn7VsNuNfaWRKdIR8QPqlP8SEGvVD2Bfl3fVl9v7Rtk5vrMnMzM4ZY9P8ImbFG9ge/C2oj4pfAfwgPYVfp2jTRVr/1aZr4ZEac7NlBX4yf81rYYETuwYxb/x3EwIg6WZOdfCBExitdxZVcfrMXGiDg1D58SJ/F0k+x1/Vnzf8J/lSTmjUVQzcoAAAAASUVORK5CYII=\n",
"text/latex": [
"$\\displaystyle {f}_{(1,0)}^{1}$"
],
@@ -789,13 +632,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\left({img}_{(1,0)}^{2} w_{2} - {img}_{(1,1)}^{2} w_{1} - {img}_{(-1,1)}^{2} w_{1} + {img}_{(1,-1)}^{2} w_{1} - {img}_{(-1,-1)}^{2} w_{1} - {img}_{(-1,0)}^{2} w_{2}\\right)^{2}$"
],
"text/plain": [
- " 2\n",
- "(img_E__2â‹…wâ‚‚ - img_NE__2â‹…wâ‚ - img_NW__2â‹…wâ‚ + img_SE__2â‹…wâ‚ - img_SW__2â‹…wâ‚ - img_W__2â‹…wâ‚‚) "
+ " \n",
+ "(img_E__2â‹…wâ‚‚ - img_NE__2â‹…wâ‚ - img_NW__2â‹…wâ‚ + img_SE__2â‹…wâ‚ - img_SW__2â‹…wâ‚ - img\n",
+ "\n",
+ " 2\n",
+ "_W__2â‹…wâ‚‚) "
]
},
"execution_count": 26,
@@ -825,13 +671,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAA04AAAAaCAYAAACAVwz9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAABJ0AAASdAHeZh94AAAPcklEQVR4nO2debAcRR2AvxAg0RAwkeKwEBJQUBCVhCNc8QXCoVgSLSkUQR+FcgUBRdQAxY9fUBEiVAgYwKO4vChRQUpATAQPDgtDMIJXgCBoEOSKRIFwxD9+M7x5/WZmZ3bn2t3+qlKb1z090zv9bU/39HTPqLVr15KEqo4GJovIA4kbNQBVnQN8CNgOeBG4C5gjIvfVmjFPz+Kd84D3wNMe3htPkXif+htf/q1R1cnAIyLySso2mc7jOi2OdUGQuOkMAAuBPYB9gJeBRao6sc5MeXqaAbxzHu+Bpz0G8N54imMA71M/M4Av/1a8AJzZYpsBMpzHUUkjTqr6SWCsiFwcE/dZ4HzgMBH5ft7cl42qbgCsAmaJyA1158fTGU33DbxzVeA98LRL093x3nQPTXcJvE9l4su/ewn6NeuIyDcybh97HtdN2HhTYDYwNWF/OwefSzLnuFrGY6NpT9edkV5AVbcA5gIHAm8EHgOuA1REnsmxn4eBrRKiHxeRzRLimu4b9IlzNbvgPehSfB3SEu9NDnw91BLvU3n48u9evg3cparXikiWcxN7HmM7TsDpwHUi8mpC/BexSmt5xsxWzXzgXuz5RE8HqOo2wB3AJsD1wF+AXYGTgANVdU8ReSrHLldh5eOyOiVN032DPnCuAS54D7qQBngDzXdnPt6bTDTAp6a7BN6nMvHl36WIyFpV/QkwBzg1Q5L5xJzHER0nVZ0AHAXskHLwR3LktVJUdR4wHdg7bRKYJzMLsQvUiSJyURioqhcAnwG+DBybY3/PishZeTLQZN+gr5yr1QXvQT2o6iBwOTBDRG5rYxe+DkmhV70pEV8PpeB9Khdf/l3PVcByVZ0nIk8kbZR2HuNGnD4MPCUiDyfsbAbwS2CeiHzeCTsf+B42AWs6MDoIP05E/qWq2wNnADOBMcBvgOPjRFTVscDJwMeBrYHHgcuAc4FngRUi8k4nzfnA4dgFvraVAFV1JvAL4GwROTMSvhtDPdfJ0XOsqt8FPgq8XUT+WmF2E1HVrYH9gYeBrzvRAhwNHKGqp4jIf0vKQ2N9C9I1wrmyqduFOA+ccF/3NJC6vQny0Ng6xHuTj7p98vVQf1NV+fdTe6Tq9rKIrFTVlcBHgAUJeUo9j3Edpw8AS1OOOyX4XBoTti3wW+Am7FnCA4FZwBhVvQT4PibRldjqFQdhvb8BJ9PjgEXANOw50guBTTEZ3w5s4OZRVRcAhwZf9E8p+a+C8HnI8U74FyL/n4hV/qjqm4BDgBua0mkK2Cf4vMV9bFNEnlPV27GL2DRgccZ9jlHVw4Etgf8Cy4Bfp9wZaaRvQbomOVc2dbsQ50E03Nc9zaRub6ChdYj3pi3q9snXQ/1N6eXfh+2ROtrLS7G+zoiOU5bzuK6TYBSwZ9zOIoSC3BMTtiswTUSWBfubCzyCVWQ7AfuJyJ1B3PrAA8B0VR0rIi9E9ncZJs2ZwJdEZG2Q5mpMqGHHV9WFWO9wFvC0qoYTOleLSNpz72URTk59TQRVfStwMDaBdRYwIbL9bGA9YF412cvMdsHn3xLil2Nluy3ZL1KbAVc7YStU9UgR+VXM9o3zLYhrmnNlU7cLcR5Ew33d00zq9gYaWId4b9qmbp98PdTfVFH+/dYeqaO9vBQ4XVVHR2+QZD2P6zg72zzI4GMpB5yCTZpc7oQBDIbCgN0BwnqJo4FTQ2GCuDXAX4FRwLhIxqcBHwOuF5GzQ2mCNIsxCWG4OMdhJ31xkPfw3+dSvkeZjBABm4j2HHBe8PdEeG1I9mjgdyLy28pymI2Ngs9VCfFh+Bsy7u9yYF/sQjUO2BGrJCYBN6nqu2LSNNE3aJ5zZVO3C3EehOHg656mUrc30Mw6xHvTHnX75Ouh/qbU8u/T9kgd7eXHsHPurqiZ6Ty6j+qFO/lP3JGCIcRtgTvCYfJI2AoRuTkm2VbYUNw1CXHPyfAVcGYHn1+OywPwFPBmbKULAERkVMK2dbEKeJVABLXl3T+ODbk+GmwzMfg8AtgYK7CO0PSlVeP4rogc3sEhw/Me/zIwBxFRJ+g+4FhVXQ2cApwFfDCMbKpvwXdpmnPD6CUX4jxwwn3dUxAtvLlV1S02rhSRwQ4O2Zd1SK95k4SvhwDvU20U6V9F5d+T7ZEW1NFeDvs4WwIPhYFZz6PbcdrQ2anLu7BRqntiwn7hbqyqk7ARrB+LyEtO3AbANsDtTrL9MTl+n5CHzYHlQU++kYgtebiKoR70SViFfiHWi4ahoceTgAeBH4fpVXUO8CHssYQXsQlyc0TkvhaHfhB7O3JWVraID+/ebZQQv6GzXbtcil2kpjvh3rf26SUX4jyIhnsXimM+I+/Wvxt7bOJKgufMI9zbYn++DukPb5Lw9ZD3qU6K9K+K8u+7sq+pvRz2cTZM2SYRt+O0fvD5YsL2aZNs4wp6akrcTjgSBsNwmwD3RocoI/Fvw4bUb3PCJ2DvcthDRB5MyHvhqOq12N2HC2KinwHGBz+OY4HvicjKIN0rwERV3R9b9v0EGT7RdQBbcvVuTKC5wCJV3V5SXtolIvsW8LWihBPvtk2If2vwmfS8eVbCJSHHOeGN9C2Iq9y5Fr4No8dcaDUht+/qnjzk9GZ+TPpBrON0heRfjtzXIV3qTRK+HvL1UJ3U6F+p5d9t7ZG8NKy9HHam10+IT8XtOP0v+HRXtwhJm2S7JGb7qSlxO8Xs6+Xg34SRmwMQLv/o9vhPA26OCqOq07HnJKdivfRDROTahP3GoqrHB/vYHLgfOFlEfhPZZC5wm6p+W0TcO1zPBN/jaOwO7tcicf/Bhh5Pxu4uXB5NKCIHOPk4AruDtidwQ57v0CG3Bp/7q+o6zvD0+CA/z9P5S9Z2Dz4fcsKb6hs4znXqW8b0ab6VTZ0utJqQ26i6Jw/em76tQ0q5ZnWK9+k1fD1UsXs58lGXf2WXf2Htkbz0YXs5HGlq65UF7uIQTzo7dZmC9dT+5IStwZ4NdgmliSvoERKKyMvYnaKtVHXYnQJVnQ0c6aZR1dcDnwK+5ex/HPAH4ISE75KKqh6KDRV+BRP8dmyy6JaR/C4DVmCrcLiEIpwM3Cgi90fiVgG7YUtVLhSR/41MPozxWFkljjaVQfAjvAWbKDvbiVbsHF8lzvsyVHUbVX2bqq4XCdtBVSfi7kR1K+Di4M/vONGN8y2Ii3OuI9+ypG/hW6m040KcB0F4XhfiPAjDm1j35MF702d1SFnXrILoOZ98PZSJJriXKR81+ldq+RfcHslLv7WXwz7OkynbJOKOOIV3V0Y8P6yqY4DtsWHEl52wZWIrhLhMAf4uInGZm4LdGfqzE34OtjToz1T1GuBfwF7YEPxfsOcYo+IchE0sG7bChojchK2lj46c0JyFz2KPpnwz+PtEVX0vNiltTmS7nwKHMfJlfKEIE7AJbVGexeYNvMBQBZ3GfGwuQad30drheOAOYEHwY/4zJvEM7Ed+ekyaxdikx8kMzYk4BPiiqt6K/Xiew57vPQgYC9xI5C5Dg32DGOc69S1H+iTfqiCvC3EeQA4X4jxwwhtX9+TBe9OXdUhZ16yO6VGffD3Ugia4lzMflfpXYfkX0h7JSx+2l8OOU1sjdMNGnIIJZ8sZek44yjuwtdPviQkbMQwZ3LXZOCFuDPYir2XivGRORL4DnAj8E3sz8Eexk7ALQ89/PhNJshewJO6Z0HZRW19/KnZnK8otwB5O2O+AXVT1dU54mMe7ZeS7IMJhyqtF5AlSUNV52ATVQ9xzVQXBHb6dgSuwi9Mp2MVlAbC7DF8NKI1bgZ9gF6/DsB/ae7Af+yeA9zsVT1N9gxKcy0GSb6VTkwtxHkTDe6ruKZF+8waaW4d0kzdJ9JtPvh5qFlX7V0n5d2F7pFvby+EqiG09xeWOOIFNPJviBorIEoaW+kwMi8T9PSXuRUy2WETkIuCiaFjw3OJErEceZRKtV+LJy8bYuvuPO+GPAzOdsJXYd3kTkd6riBwDHBO3cxEZyJIJVT0fG9acISIPZElTBiLyKEPDxFm2nxQT9ivA/UGk7aOpvkE5zmUl1reqyONCnAdBeGYXksq8IS5Moj4P8tK2NyJyBdZIbRtfhwxjEt3jTRK+HkoJD+K8T+VRqX9Vln+XtUegO9vLUxiaL5mbuI7TNcD17sTLKlDV0cAb3V6lqs4ELsHWdL/USTaWfMtN5sHtwY+KCXs++Cz0zoeqLgAOxSRwn6n1FECbvkG5zrWiFN/6nSLrHlU9C5AWh5wh+Veo6wTvTQk08JoVHv8synXQ+1QCvVAPVXTcnvOvyPZITWXfFe1lVR2FPfp3brvHi+s4hc/7zmTk0FvZbA/crao/x3qj62FfcC9sEtfBIrLaSfMkyauQtMuTwCvY0o9RNmFkrzqcXPrvog6uqguxnvMs4GlVDfOxOub7e9qnHd+gHOeyUrhvHqDYuudi4ActjvdIR7nNj/emHJpyzXIp20HvUzn0Qj1UxXF70b8i2yNVln23tZenY/OmFrV7zBEdJxF5VVVPAwapvuO0BpuQuRtwADbhbQVwHnCBiLiFALam/mCRmRCRNaq6BNgP+GEkaj/gR87mOwIrE/LWLuFbkRc74Yq9ydxTDO34BiU4l4MyfPMUWPeITQRua7WeEvHelEMjrlkuFTjofSqHrq+HKjpuL/pXWHukyrLvwvbyIPDVFnOgUhm1dm38fDJVvQUYlOAlVE1FVXfEJs9tKpGVS9RepPWW4M+l2Pryi4CnRaRlTztYXvFqbAWf27HnLz8J7BA8uxpudxXwkogcVcgX8jSeOOcK8C1Teu9bc0iqe3Luw3vTZ5R1zSoob96nLqMJ9VBReP/y04Ty75b2sqpugnXmBjrpOLnvcYpyNHBmuzuuChH5I7ZSx0ecqJ0xAcK3PM8L/j833EBVB1V1rapOitnvNdia8mdgUu4NvM+R4HXY8OA33fSe3iXBuY58y5je+9YgUuqePHhv+oyyrlkF4X3qMhpSDxWF9y8nTSj/LmovnwMc20mnCeLnOAEgIg+r6pWqupeItL0+fEUocJGqXhKekGDSW+yKJhEmYy8z+0dcpIgsBBampD8KuEtE6ni/kqdehjnXqW8Z03vfmseIuicP3pu+pZRrVqd4n7qWWuuhovD+tU3t5d/09rKqTgNukOEv122LtBEnRORO4M5OD1I2IvJzbDLcFjmTvg84QSIvNMvJGuDTbab1dDFtOud96zE6qHvy4L3pMWq8ZhWB96lhdEk9VBTeP4cuKf+6y+1uEbmuiB0lznHyeDwej8fj8Xg8Ho/xf0JqChoC1iN1AAAAAElFTkSuQmCC\n",
"text/latex": [
"$\\displaystyle \\left({img}_{(1,0)}^{2} w_{2} - 0.5 {img}_{(1,1)}^{2} - 0.5 {img}_{(-1,1)}^{2} + 0.5 {img}_{(1,-1)}^{2} - 0.5 {img}_{(-1,-1)}^{2} - {img}_{(-1,0)}^{2} w_{2}\\right)^{2}$"
],
"text/plain": [
- " 2\n",
- "(img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚) "
+ " \n",
+ "(img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…img_SW__2 -\n",
+ "\n",
+ " 2\n",
+ " img_W__2â‹…wâ‚‚) "
]
},
"execution_count": 27,
@@ -858,13 +707,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle {dst}_{(0,0)} \\leftarrow \\left({img}_{(1,0)}^{2} w_{2} - 0.5 {img}_{(1,1)}^{2} - 0.5 {img}_{(-1,1)}^{2} + 0.5 {img}_{(1,-1)}^{2} - 0.5 {img}_{(-1,-1)}^{2} - {img}_{(-1,0)}^{2} w_{2}\\right)^{2}$"
],
"text/plain": [
- " 2\n",
- "dst_C := (img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚) "
+ " \n",
+ "dst_C := (img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…im\n",
+ "\n",
+ " 2\n",
+ "g_SW__2 - img_W__2â‹…wâ‚‚) "
]
},
"execution_count": 28,
@@ -910,17 +762,20 @@
"metadata": {},
"outputs": [
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "No requests installed\n"
- ]
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
"try:\n",
" import requests\n",
- " import imageio\n",
+ " import imageio.v2 as imageio\n",
" from io import BytesIO\n",
"\n",
" response = requests.get(\"https://www.python.org/static/community_logos/python-logo-master-v3-TM.png\")\n",
@@ -928,7 +783,7 @@
" img /= img.max()\n",
" plt.imshow(img);\n",
"except ImportError:\n",
- " print(\"No requests installed\")\n",
+ " print(\"No requests or imageio installed\")\n",
" img = np.random.random((82, 290, 4))"
]
},
@@ -939,14 +794,12 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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"text/plain": [
- "<Figure size 432x288 with 1 Axes>"
+ "<Figure size 640x480 with 1 Axes>"
]
},
- "metadata": {
- "needs_background": "light"
- },
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -972,154 +825,11 @@
"metadata": {},
"outputs": [
{
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- "<text text-anchor=\"middle\" x=\"455.84\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\">_data_img_22_0m1</text>\n",
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- "<text text-anchor=\"middle\" x=\"658.84\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\">Loop over dim 1</text>\n",
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- "<title>140467585304800->140467585316992</title>\n",
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- ],
- "text/plain": [
- "<graphviz.sources.Source at 0x7fc1285aff40>"
- ]
- },
- "execution_count": 32,
- "metadata": {},
- "output_type": "execute_result"
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "graphviz is not installed. Visualizing the AST is not available\n"
+ ]
}
],
"source": [
@@ -1236,7 +946,7 @@
"<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_img_22_0m1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_data_img_22</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"n\">_size_dst_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">pow</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">],</span><span class=\"w\"> </span><span class=\"mi\">2</span><span class=\"p\">);</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]);</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
"<span class=\"p\">}</span><span class=\"w\"></span>\n",
@@ -1253,7 +963,7 @@
" double * RESTRICT _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
" for (int64_t ctr_1 = 1; ctr_1 < _size_dst_1 - 1; ctr_1 += 1)\n",
" {\n",
- " _data_dst_00[_stride_dst_1*ctr_1] = pow(w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1], 2);\n",
+ " _data_dst_00[_stride_dst_1*ctr_1] = (w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1])*(w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1]);\n",
" }\n",
" }\n",
"}"
@@ -1380,7 +1090,7 @@
"<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_img_22_0m1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_data_img_22</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"n\">_size_dst_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">pow</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">],</span><span class=\"w\"> </span><span class=\"mi\">2</span><span class=\"p\">);</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"n\">_stride_img_1</span><span class=\"p\">]);</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
@@ -1401,7 +1111,7 @@
" double * RESTRICT _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
" for (int64_t ctr_1 = 1; ctr_1 < _size_dst_1 - 1; ctr_1 += 1)\n",
" {\n",
- " _data_dst_00[_stride_dst_1*ctr_1] = pow(w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1], 2);\n",
+ " _data_dst_00[_stride_dst_1*ctr_1] = (w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1])*(w_2*-1.0*_data_img_22_0m1[_stride_img_1*ctr_1] + w_2*_data_img_22_01[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1]);\n",
" }\n",
" }\n",
" }\n",
@@ -1418,29 +1128,6 @@
"ps.show_code(ast)"
]
},
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "False"
- ]
- },
- "execution_count": 35,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "loops = list(ast.atoms(ps.astnodes.LoopOverCoordinate))\n",
- "l1 = loops[0]\n",
- "l1.prefix_lines.append(\"#pragma something\")\n",
- "l1.is_outermost_loop"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -1453,7 +1140,7 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 35,
"metadata": {},
"outputs": [
{
@@ -1547,12 +1234,12 @@
"<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span><span class=\"w\"> </span><span class=\"kt\">void</span><span class=\"w\"> </span><span class=\"n\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"k\">const</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"p\">,</span><span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"p\">{</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">81</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">202</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_01</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_0m1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">289</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">601</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_01</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_0m1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">600</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">];</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
@@ -1564,12 +1251,12 @@
"FUNC_PREFIX void kernel(double * RESTRICT const _data_I, double * RESTRICT _data_dst)\n",
"{\n",
" double * RESTRICT _data_I_21 = _data_I + 1;\n",
- " for (int64_t ctr_0 = 1; ctr_0 < 81; ctr_0 += 1)\n",
+ " for (int64_t ctr_0 = 1; ctr_0 < 202; ctr_0 += 1)\n",
" {\n",
- " double * RESTRICT _data_dst_00 = _data_dst + 290*ctr_0;\n",
- " double * RESTRICT _data_I_21_01 = _data_I_21 + 1160*ctr_0 + 1160;\n",
- " double * RESTRICT _data_I_21_0m1 = _data_I_21 + 1160*ctr_0 - 1160;\n",
- " for (int64_t ctr_1 = 1; ctr_1 < 289; ctr_1 += 1)\n",
+ " double * RESTRICT _data_dst_00 = _data_dst + 601*ctr_0;\n",
+ " double * RESTRICT _data_I_21_01 = _data_I_21 + 2404*ctr_0 + 2404;\n",
+ " double * RESTRICT _data_I_21_0m1 = _data_I_21 + 2404*ctr_0 - 2404;\n",
+ " for (int64_t ctr_1 = 1; ctr_1 < 600; ctr_1 += 1)\n",
" {\n",
" _data_dst_00[ctr_1] = -1.0*_data_I_21_01[4*ctr_1 + 4] - 1.0*_data_I_21_0m1[4*ctr_1 + 4] - 1.0*_data_I_21_0m1[4*ctr_1 - 4] - 2.0*_data_I_21_0m1[4*ctr_1] + 2.0*_data_I_21_01[4*ctr_1] + _data_I_21_01[4*ctr_1 - 4];\n",
" }\n",
@@ -1610,7 +1297,7 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 36,
"metadata": {},
"outputs": [
{
@@ -1701,36 +1388,34 @@
{
"data": {
"text/html": [
- "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span><span class=\"w\"> </span><span class=\"kt\">void</span><span class=\"w\"> </span><span class=\"n\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"k\">const</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"p\">,</span><span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
+ "<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span><span class=\"w\"> </span><span class=\"nf\">__launch_bounds__</span><span class=\"p\">(</span><span class=\"mi\">256</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"kt\">void</span><span class=\"w\"> </span><span class=\"n\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"k\">const</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"p\">,</span><span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">81</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"k\">if</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">202</span><span class=\"w\"> </span><span class=\"o\">&&</span><span class=\"w\"> </span><span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">600</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
"<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_01</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_0m1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I_21</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">1160</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"k\">for</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\"><</span><span class=\"w\"> </span><span class=\"mi\">289</span><span class=\"p\">;</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"p\">{</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"p\">];</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
- "<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"k\">const</span><span class=\"w\"> </span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"k\">const</span><span class=\"w\"> </span><span class=\"kt\">int64_t</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_dst_10</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_dst</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">ctr_1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_11_21</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">5</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_1m1_21</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">3</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"kt\">double</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"n\">RESTRICT</span><span class=\"w\"> </span><span class=\"n\">_data_I_10_21</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">_data_I</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"n\">_data_dst_10</span><span class=\"p\">[</span><span class=\"mi\">601</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mf\">-1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">1.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">-</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">]</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">2404</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">2404</span><span class=\"p\">];</span><span class=\"w\"></span>\n",
+ "<span class=\"w\"> </span><span class=\"p\">}</span><span class=\"w\"> </span>\n",
"<span class=\"p\">}</span><span class=\"w\"></span>\n",
"</pre></div>\n"
],
"text/plain": [
- "FUNC_PREFIX void kernel(double * RESTRICT const _data_I, double * RESTRICT _data_dst)\n",
+ "FUNC_PREFIX __launch_bounds__(256) void kernel(double * RESTRICT const _data_I, double * RESTRICT _data_dst)\n",
"{\n",
- " double * RESTRICT _data_I_21 = _data_I + 1;\n",
- " for (int64_t ctr_0 = 1; ctr_0 < 81; ctr_0 += 1)\n",
+ " if (blockDim.x*blockIdx.x + threadIdx.x + 1 < 202 && blockDim.y*blockIdx.y + threadIdx.y + 1 < 600)\n",
" {\n",
- " double * RESTRICT _data_dst_00 = _data_dst + 290*ctr_0;\n",
- " double * RESTRICT _data_I_21_01 = _data_I_21 + 1160*ctr_0 + 1160;\n",
- " double * RESTRICT _data_I_21_0m1 = _data_I_21 + 1160*ctr_0 - 1160;\n",
- " for (int64_t ctr_1 = 1; ctr_1 < 289; ctr_1 += 1)\n",
- " {\n",
- " _data_dst_00[ctr_1] = -1.0*_data_I_21_01[4*ctr_1 + 4] - 1.0*_data_I_21_0m1[4*ctr_1 + 4] - 1.0*_data_I_21_0m1[4*ctr_1 - 4] - 2.0*_data_I_21_0m1[4*ctr_1] + 2.0*_data_I_21_01[4*ctr_1] + _data_I_21_01[4*ctr_1 - 4];\n",
- " }\n",
- " }\n",
+ " const int64_t ctr_0 = blockDim.x*blockIdx.x + threadIdx.x + 1;\n",
+ " const int64_t ctr_1 = blockDim.y*blockIdx.y + threadIdx.y + 1;\n",
+ " double * RESTRICT _data_dst_10 = _data_dst + ctr_1;\n",
+ " double * RESTRICT _data_I_11_21 = _data_I + 4*ctr_1 + 5;\n",
+ " double * RESTRICT _data_I_1m1_21 = _data_I + 4*ctr_1 - 3;\n",
+ " double * RESTRICT _data_I_10_21 = _data_I + 4*ctr_1 + 1;\n",
+ " _data_dst_10[601*ctr_0] = -1.0*_data_I_11_21[2404*ctr_0 + 2404] - 1.0*_data_I_11_21[2404*ctr_0 - 2404] - 1.0*_data_I_1m1_21[2404*ctr_0 - 2404] - 2.0*_data_I_10_21[2404*ctr_0 - 2404] + 2.0*_data_I_10_21[2404*ctr_0 + 2404] + _data_I_1m1_21[2404*ctr_0 + 2404];\n",
+ " } \n",
"}"
]
},
@@ -1747,7 +1432,7 @@
" gpu_indexing=BlockIndexing,\n",
" gpu_indexing_params={'blockSize': (64, 1, 1)})\n",
"\n",
- " ps.show_code(ast)\n",
+ " ps.show_code(gpu_ast)\n",
"except ImportError:\n",
" print(\"Please install pycuda for GPU support\")"
]
@@ -1770,7 +1455,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.2"
+ "version": "3.10.6"
}
},
"nbformat": 4,
diff --git a/setup.py b/setup.py
index 79f1f108b..2de55acd3 100644
--- a/setup.py
+++ b/setup.py
@@ -90,7 +90,7 @@ setuptools.setup(name='pystencils',
author_email='cs10-codegen@fau.de',
url='https://i10git.cs.fau.de/pycodegen/pystencils/',
packages=['pystencils'] + ['pystencils.' + s for s in setuptools.find_packages('pystencils')],
- install_requires=['sympy>=1.6,<=1.10', 'numpy>=1.8.0', 'appdirs', 'joblib'],
+ install_requires=['sympy>=1.6,<=1.11.1', 'numpy>=1.8.0', 'appdirs', 'joblib'],
package_data={'pystencils': ['include/*.h',
'backends/cuda_known_functions.txt',
'backends/opencl1.1_known_functions.txt',
--
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