notebook v1

Dockerfile

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+# Imagen base con soporte de CUDA
+FROM tensorflow/tensorflow:2.12.0-gpu
+
+# Crear directorio de trabajo
+WORKDIR /app
+
+# Copiar archivos de dependencias
+COPY requirements.txt .
+
+# Instalar dependencias
+RUN pip install --upgrade pip && \
+    pip install -r requirements.txt
+
+# Copiar el notebook o app
+COPY . .
+
+# Comando por defecto (puede cambiarse según necesidad)
+CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--allow-root", "--NotebookApp.token=''", "--NotebookApp.password=''", "--no-browser"]

lstm_gpu_demo.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(\"GPU disponible:\", tf.config.list_physical_devices('GPU'))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "N = 10000  # muestras\n",
+    "T = 30     # pasos de tiempo\n",
+    "F = 10     # features\n",
+    "\n",
+    "X = np.random.rand(N, T, F)\n",
+    "y = np.random.rand(N, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import LSTM, Dense\n",
+    "\n",
+    "model = Sequential([\n",
+    "    LSTM(64, input_shape=(T, F)),\n",
+    "    Dense(1)\n",
+    "])\n",
+    "\n",
+    "model.compile(optimizer='adam', loss='mse')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "history = model.fit(X, y, epochs=5, batch_size=64)\n",
+    "\n",
+    "# 6. Graficar pérdida\n",
+    "plt.plot(history.history['loss'])\n",
+    "plt.title('Pérdida de entrenamiento')\n",
+    "plt.xlabel('Época')\n",
+    "plt.ylabel('Loss')\n",
+    "plt.grid(True)\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

requirements.tct

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+tensorflow>=2.12
+numpy
+pandas
+matplotlib
+jupyter