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": [ - "
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Available hardware:\n",
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"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": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.plot(train_report.loss, 'o', mfc='None', label=\"Train\")\n", "plt.plot(test_report.loss, 'o', mfc='None', label=\"Train\")\n", @@ -384,23 +299,10 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "8c3ab30b-9c4d-4b1a-95e0-ea75214a630f", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.plot(train_report.covariance_entropy, 'o', mfc='None', label=\"Entropy\")\n", "plt.xlabel(\"Epoch\")\n", @@ -411,23 +313,10 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "d8772e69", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.plot(train_report.magnitude_variance, 'o', mfc='None', label=\"Magnitude Variance\")\n", "plt.xlabel(\"Epoch\")\n", @@ -438,23 +327,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "6d43257c-defc-4f1e-816a-ebe1ae79e7ca", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.plot(train_report.trace, 'o', mfc='None', label=\"Trace\")\n", "plt.xlabel(\"Epoch\")\n", @@ -465,23 +341,10 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "0bd153b8-caa4-4095-8f9c-bcc6142d93d5", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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