mirror of
https://github.com/sbrl/research-rainfallradar
synced 2024-11-16 22:53:00 +00:00
143 lines
6.2 KiB
Text
143 lines
6.2 KiB
Text
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "1f6fdebf-69c5-46ab-a5a8-f9c91f000ff3",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2022-10-24 17:18:42.868504: 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",
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"2022-10-24 17:18:42.868519: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
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]
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}
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],
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"source": [
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"import sys\n",
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"\n",
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"import tensorflow as tf\n",
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"\n",
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"from lib.dataset.dataset_segmenter import dataset_predict"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "4a6a94dd-5c4e-4481-bfae-eb5ccf6214db",
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"metadata": {},
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"outputs": [],
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"source": [
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"dirpath=\"/home/bryan-smithl/Documents/repos/PhD-Rainfall-Radar/aimodel/output/rainfallwater_records_embed_2022-10-06_contrast_embed_umap_d512e19_tfrecord\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "d1aa931a-ecf2-4134-8e70-87db4ae60736",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"DEBUG:dataset ITEM rainfall:shape (512,) water:shape (94, 94, 1)\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2022-10-24 17:18:44.582661: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
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"2022-10-24 17:18:44.583031: 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",
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"2022-10-24 17:18:44.583152: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583257: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583353: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcufft.so.10'; dlerror: libcufft.so.10: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583438: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcurand.so.10'; dlerror: libcurand.so.10: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583519: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusolver.so.11'; dlerror: libcusolver.so.11: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583598: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583675: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory\n",
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"2022-10-24 17:18:44.583688: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1850] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\n",
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"Skipping registering GPU devices...\n",
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"2022-10-24 17:18:44.584534: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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}
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],
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"source": [
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"dataset = dataset_predict(\n",
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"\tdirpath_input=dirpath,\n",
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"\twater_threshold=0.1,\n",
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"\tshape_water_desired=[94, 94],\n",
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"\tparallel_reads_multiplier=1.5 # Mangles the ordering. For counting things this doesn't matter\n",
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").batch(64)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "456f7c8f-3f7d-4a2c-b361-900588c49612",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Processed 23100 batches\r"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Complete. Counts:\n",
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"0: 10238285719\n",
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"1: 2854828393\n"
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]
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}
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],
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"source": [
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"i = 0\n",
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"counts = tf.constant([0, 0], dtype=tf.int64)\n",
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"for (items, label) in dataset:\n",
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"\tstep_counts = tf.math.bincount(tf.reshape(label, [-1]))\n",
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"\tcounts += tf.cast(step_counts, dtype=tf.int64)\n",
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"\t# print(\"STEP counts\", counts, \"step_counts\", step_counts)\n",
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"\ti += 1\n",
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"\tif i % 100 == 0:\n",
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"\t\tsys.stderr.write(f\"Processed {i} batches\\r\")\n",
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"print(\"\\nComplete. Counts:\\n\"+\"\\n\".join([ str(i)+\": \"+str(count) for i,count in enumerate(counts.numpy().tolist()) ]))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.10.6 64-bit",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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},
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"vscode": {
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"interpreter": {
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"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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