Skip to content

[WIP] fix print outputs in notebooks for 21.12 #9866

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
taureandyernv wants to merge 1 commit into from
Closed

[WIP] fix print outputs in notebooks for 21.12 #9866

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
169 changes: 115 additions & 54 deletions docs/cudf/source/user_guide/10min-cudf-cupy.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,9 +45,23 @@
"name": "stdout",
"output_type": "stream",
"text": [
"44.1 µs ± 689 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"209 µs ± 2.77 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
"208 µs ± 3.14 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
"158 µs ± 306 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"419 µs ± 149 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/envs/rapids/lib/python3.7/site-packages/cudf/core/dataframe.py:3044: FutureWarning: The as_gpu_matrix method will be removed in a future cuDF release. Consider using `to_cupy` instead.\n",
" FutureWarning,\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"339 µs ± 282 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
]
}
],
Expand Down Expand Up @@ -117,9 +131,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"22.1 µs ± 518 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"58.3 µs ± 647 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"80.2 µs ± 647 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
"45.4 µs ± 63.9 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"127 µs ± 351 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"135 µs ± 5.24 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
]
}
],
Expand Down Expand Up @@ -256,7 +270,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"13.1 ms ± 193 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
"15.5 ms ± 7.55 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
Expand Down Expand Up @@ -510,7 +524,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"4.9 ms ± 26.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
"7.26 ms ± 3.32 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
Expand All @@ -530,7 +544,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"5.1 ms ± 23.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
"4.87 ms ± 2.08 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
Expand Down Expand Up @@ -1139,135 +1153,135 @@
" <th>0</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.704433</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.00000</td>\n",
" <td>0.0</td>\n",
" <td>16.822959</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>-1.162275</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.00000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>11.460403</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>6.618972</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>2.25678</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.407392</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.00000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>2.715802</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>8.299425</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.296568</td>\n",
" <td>0.00000</td>\n",
" <td>2.096401</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.865495</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" a0 a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 \\\n",
"0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.00000 \n",
"1 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.00000 \n",
"2 0.0 0.0 6.618972 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 2.25678 \n",
"3 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.00000 \n",
"4 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.296568 0.00000 \n",
" a0 a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 \\\n",
"0 0.0 0.0 0.0 0.0 0.0 4.704433 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"1 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"2 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"3 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"4 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 8.299425 0.0 0.0 0.0 2.096401 \n",
"\n",
" a12 a13 a14 a15 a16 a17 a18 a19 \n",
"0 0.0 16.822959 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"1 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"2 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.000000 \n",
"3 0.0 0.000000 0.0 2.715802 0.0 0.0 0.0 0.000000 \n",
"4 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 4.865495 "
" a12 a13 a14 a15 a16 a17 a18 a19 \n",
"0 0.0 0.0 0.000000 0.0 -1.162275 0.000000 0.0 0.0 \n",
"1 0.0 0.0 11.460403 0.0 0.000000 0.000000 0.0 0.0 \n",
"2 0.0 0.0 0.000000 0.0 0.000000 0.407392 0.0 0.0 \n",
"3 0.0 0.0 0.000000 0.0 0.000000 0.000000 0.0 0.0 \n",
"4 0.0 0.0 0.000000 0.0 0.000000 0.000000 0.0 0.0 "
]
},
"execution_count": 20,
Expand All @@ -1285,19 +1299,66 @@
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<cupyx.scipy.sparse.csc.csc_matrix at 0x7f25e49466a0>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
"name": "stdout",
"output_type": "stream",
"text": [
" (41, 0)\t8.237732918475851\n",
" (49, 0)\t-4.161219849238402\n",
" (70, 0)\t-1.646588718395583\n",
" (80, 0)\t11.607048248828713\n",
" (81, 0)\t11.387095517746493\n",
" (105, 0)\t4.059008225609349\n",
" (107, 0)\t9.299030876304984\n",
" (108, 0)\t10.652087054434446\n",
" (127, 0)\t2.442578989241219\n",
" (133, 0)\t-0.7674141633646347\n",
" (135, 0)\t-6.091151515788713\n",
" (145, 0)\t2.968949150266586\n",
" (148, 0)\t5.649147779687932\n",
" (158, 0)\t7.7809955768930745\n",
" (166, 0)\t5.801884262747882\n",
" (175, 0)\t7.3205065025042\n",
" (181, 0)\t13.704683370645277\n",
" (204, 0)\t15.915619596241733\n",
" (207, 0)\t-0.2205888963107494\n",
" (209, 0)\t3.565578265020142\n",
" (215, 0)\t4.1493767841754154\n",
" (231, 0)\t3.4286524053271803\n",
" (233, 0)\t6.021200022977307\n",
" (241, 0)\t4.247163658236771\n",
" (249, 0)\t1.8502158424149273\n",
" :\t:\n",
" (9729, 19)\t7.226429647432215\n",
" (9762, 19)\t-0.6042314722021014\n",
" (9764, 19)\t-1.4827372788735615\n",
" (9769, 19)\t4.140245505599609\n",
" (9776, 19)\t-0.3441145182655059\n",
" (9781, 19)\t-0.235562982602191\n",
" (9782, 19)\t2.1458765970993223\n",
" (9791, 19)\t7.219427633840467\n",
" (9803, 19)\t6.6874487362355115\n",
" (9807, 19)\t5.1769501512294465\n",
" (9823, 19)\t-1.1040045399744103\n",
" (9828, 19)\t3.074156937033751\n",
" (9849, 19)\t0.4663962936122451\n",
" (9851, 19)\t10.302861735090476\n",
" (9862, 19)\t1.9377857550195872\n",
" (9893, 19)\t8.991541850619656\n",
" (9896, 19)\t-0.9003118390325282\n",
" (9919, 19)\t2.4984693551284587\n",
" (9934, 19)\t1.6161057487404191\n",
" (9944, 19)\t6.063387997554039\n",
" (9945, 19)\t11.038782286791717\n",
" (9954, 19)\t13.750186699958661\n",
" (9979, 19)\t0.9225731640357893\n",
" (9995, 19)\t-1.775155437069923\n",
" (9998, 19)\t12.265785237649636\n"
]
}
],
"source": [
"sparse_data = cudf_to_cupy_sparse_matrix(df)\n",
"sparse_data"
"print(sparse_data)"
]
},
{
Expand Down Expand Up @@ -1326,7 +1387,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.6"
"version": "3.7.12"
Copy link
Member

@jakirkham jakirkham Dec 8, 2021

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Should we keep running under Python 3.8? Or is there a reason to use 3.7?

Copy link
Contributor Author

@taureandyernv taureandyernv Dec 8, 2021

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

i ran it with the nightlies docker container running 3.7 python. Do you want me to revert it with 3.8?

}
},
"nbformat": 4,
Expand Down