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Codepython

#Install if required
# pip install tensorflow-datasets

# =========================================================
# 1. IMPORT LIBRARIES
# =========================================================
# Core Python + ML libraries
import os
import json

# TensorFlow + datasets
import tensorflow as tf
import tensorflow_datasets as tfds

# Visualization
import matplotlib.pyplot as plt

# Keras modules
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.applications import VGG16
from tensorflow.keras.applications.vgg16 import preprocess_input

# ========================================================= # 2. GPU MEMORY SAFETY (VERY IMPORTANT 🔥) # ========================================================= # Prevent TensorFlow from grabbing all GPU memory at once # This avoids OOM (Out Of Memory) issues gpus = tf.config.list_physical_devices('GPU') if gpus: for gpu in gpus: tf.config.experimental.set_memory_growth(gpu, True) # ========================================================= # 3. CONFIGURATION # ========================================================= # Image size for models IMG_SIZE = (160, 160) # smaller than 224 → saves memory # Batch size (reduce if OOM occurs) BATCH_SIZE = 16 # Performance optimization AUTOTUNE = tf.data.AUTOTUNE # Directory structure DATA_DIR = "./datasets" MODEL_DIR = "./saved_models" PLOT_DIR = "./plots" # Create directories if they don't exist os.makedirs(DATA_DIR, exist_ok=True) os.makedirs(MODEL_DIR, exist_ok=True) os.makedirs(PLOT_DIR, exist_ok=True) # ========================================================= # 4. LOAD DATASET (TFDS handles download automatically) # ========================================================= (train_ds, val_ds), info = tfds.load( 'cats_vs_dogs', split=['train[:75%]', 'train[75%:]'], # 75/25 split as_supervised=True, # returns (image, label) with_info=True, data_dir=DATA_DIR )

2026-03-23 20:35:47.437291: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.460449: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.462735: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.540567: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.542813: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.544982: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.627758: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.628681: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.629442: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 2026-03-23 20:35:47.630208: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 10105 MB memory: -> device: 0, name: NVIDIA GeForce RTX 3060, pci bus id: 0000:01:00.0, compute capability: 8.6

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