From a2201892d3a3bd92fa179985e9df4e954cac2dc1 Mon Sep 17 00:00:00 2001
From: knikolaou <>
Date: Mon, 11 Sep 2023 13:37:07 +0200
Subject: [PATCH] clear outputs of example notebook on CVs
---
examples/Computing-Collective-Variables.ipynb | 181 +++---------------
1 file changed, 22 insertions(+), 159 deletions(-)
diff --git a/examples/Computing-Collective-Variables.ipynb b/examples/Computing-Collective-Variables.ipynb
index 776ce3f..36a0781 100644
--- a/examples/Computing-Collective-Variables.ipynb
+++ b/examples/Computing-Collective-Variables.ipynb
@@ -22,76 +22,12 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "02668461",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "2023-09-11 13:29:15.849208: W external/org_tensorflow/tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
- "2023-09-11 13:29:15.891460: W external/org_tensorflow/tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
- "2023-09-11 13:29:15.894211: W external/org_tensorflow/tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
- "2023-09-11 13:29:17.794277: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
- "/tikhome/knikolaou/miniconda3/envs/jax/lib/python3.10/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
- " from .autonotebook import tqdm as notebook_tqdm\n",
- "2023-09-11 13:29:25.297262: E external/org_tensorflow/tensorflow/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",
- "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
- ]
- },
- {
- "data": {
- "text/html": [
- "
Using backend: cpu\n",
- "
\n"
- ],
- "text/plain": [
- "Using backend: cpu\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/html": [
- "Available hardware:\n",
- "
\n"
- ],
- "text/plain": [
- "Available hardware:\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/html": [
- "TFRT_CPU_0\n",
- "
\n"
- ],
- "text/plain": [
- "TFRT_CPU_0\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'cpu'"
- ]
- },
- "execution_count": 1,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"import os\n",
"os.environ['CUDA_VISIBLE_DEVICES'] = '-1'\n",
@@ -120,7 +56,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "0d70094e",
"metadata": {},
"outputs": [],
@@ -166,7 +102,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "088201ee",
"metadata": {},
"outputs": [],
@@ -190,7 +126,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": null,
"id": "62250ce8",
"metadata": {},
"outputs": [],
@@ -204,7 +140,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": null,
"id": "dd7b67ca",
"metadata": {},
"outputs": [],
@@ -241,7 +177,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": null,
"id": "e7acdbd1-055b-4624-accd-3f6575fc9525",
"metadata": {},
"outputs": [],
@@ -285,7 +221,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"id": "0f306c72-d3e4-4a1e-a82a-d99621c7a636",
"metadata": {},
"outputs": [],
@@ -311,18 +247,10 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": null,
"id": "3daf2090-8265-44db-8343-caf8dfcd193d",
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Epoch: 50: 100%|█████████████████████████████████| 50/50 [00:14<00:00, 3.52batch/s, test_loss=1.47]\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"batched_training_metrics = training_strategy.train_model(\n",
" train_ds=data_generator.train_ds, \n",
@@ -343,7 +271,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": null,
"id": "a72513b0-3b57-46de-b504-65d66b4ca035",
"metadata": {},
"outputs": [],
@@ -354,23 +282,10 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": null,
"id": "2e3db688-241e-4cc5-8f91-685e7d0c4e4a",
"metadata": {},
- "outputs": [
- {
- "data": {
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",
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