import os
import shutil
from pathlib import Path

os.environ["KERAS_BACKEND"] = "tensorflow"
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"

import keras
import numpy as np


keras.utils.set_random_seed(31)

log_dir = Path("logs/tensorboard-demo")
if log_dir.exists():
    shutil.rmtree(log_dir)

x_train = np.linspace(0.0, 1.0, 80, dtype="float32").reshape(20, 4)
y_train = ((x_train[:, 0] + x_train[:, 1]) > 0.8).astype("float32")

model = keras.Sequential(
    [
        keras.Input(shape=(4,), name="features"),
        keras.layers.Dense(8, activation="relu"),
        keras.layers.Dense(1, activation="sigmoid"),
    ]
)
model.compile(
    optimizer=keras.optimizers.Adam(learning_rate=0.03),
    loss=keras.losses.BinaryCrossentropy(),
    metrics=[keras.metrics.BinaryAccuracy(name="accuracy")],
)

callback = keras.callbacks.TensorBoard(
    log_dir=log_dir,
    histogram_freq=0,
    write_graph=False,
    update_freq="epoch",
)
history = model.fit(x_train, y_train, epochs=2, batch_size=5, callbacks=[callback], verbose=0)
event_files = sorted(path for path in log_dir.rglob("events.out.tfevents.*") if path.is_file())

print(f"backend: {keras.backend.backend()}")
print(f"log directory: {log_dir}")
print(f"epochs completed: {len(history.history['loss'])}")
print(f"event files: {len(event_files)}")
print(f"first event file: {event_files[0] if event_files else 'none'}")
print(f"view command: tensorboard --logdir {log_dir}")