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TensorBoard adalah alat bawaan untuk menyediakan pengukuran dan visualisasi di TensorFlow. Metrik eksperimen machine learning yang umum, seperti akurasi dan kehilangan, dapat dilacak dan ditampilkan di TensorBoard. TensorBoard kompatibel dengan kode TensorFlow 1 dan 2.
Di TensorFlow 1, tf.estimator.Estimator
menyimpan ringkasan untuk TensorBoard secara default. Sebagai perbandingan, di TensorFlow 2, ringkasan dapat disimpan menggunakan panggilan balik tf.keras.callbacks.TensorBoard
.
Panduan ini menunjukkan cara menggunakan TensorBoard, pertama, di TensorFlow 1 dengan Estimator, lalu, cara melakukan proses yang setara di TensorFlow 2.
Mempersiapkan
import tensorflow.compat.v1 as tf1
import tensorflow as tf
import tempfile
import numpy as np
import datetime
%load_ext tensorboard
mnist = tf.keras.datasets.mnist # The MNIST dataset.
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz 11493376/11490434 [==============================] - 0s 0us/step 11501568/11490434 [==============================] - 0s 0us/step
TensorFlow 1: TensorBoard dengan tf.estimator
Dalam contoh TensorFlow 1 ini, Anda membuat tf.estimator.DNNClassifier
, melatih dan mengevaluasinya pada set data MNIST, dan menggunakan TensorBoard untuk menampilkan metrik:
%reload_ext tensorboard
feature_columns = [tf1.feature_column.numeric_column("x", shape=[28, 28])]
config = tf1.estimator.RunConfig(save_summary_steps=1,
save_checkpoints_steps=1)
path = tempfile.mkdtemp()
classifier = tf1.estimator.DNNClassifier(
feature_columns=feature_columns,
hidden_units=[256, 32],
optimizer=tf1.train.AdamOptimizer(0.001),
n_classes=10,
dropout=0.1,
model_dir=path,
config = config
)
train_input_fn = tf1.estimator.inputs.numpy_input_fn(
x={"x": x_train},
y=y_train.astype(np.int32),
num_epochs=10,
batch_size=50,
shuffle=True,
)
test_input_fn = tf1.estimator.inputs.numpy_input_fn(
x={"x": x_test},
y=y_test.astype(np.int32),
num_epochs=10,
shuffle=False
)
train_spec = tf1.estimator.TrainSpec(input_fn=train_input_fn, max_steps=10)
eval_spec = tf1.estimator.EvalSpec(input_fn=test_input_fn,
steps=10,
throttle_secs=0)
tf1.estimator.train_and_evaluate(estimator=classifier,
train_spec=train_spec,
eval_spec=eval_spec)
INFO:tensorflow:Using config: {'_model_dir': '/tmp/tmp9w0s5sgg', '_tf_random_seed': None, '_save_summary_steps': 1, '_save_checkpoints_steps': 1, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1} WARNING:tensorflow:From /tmp/ipykernel_13367/2752664473.py:20: The name tf.estimator.inputs is deprecated. Please use tf.compat.v1.estimator.inputs instead. WARNING:tensorflow:From /tmp/ipykernel_13367/2752664473.py:20: The name tf.estimator.inputs.numpy_input_fn is deprecated. Please use tf.compat.v1.estimator.inputs.numpy_input_fn instead. INFO:tensorflow:Not using Distribute Coordinator. INFO:tensorflow:Running training and evaluation locally (non-distributed). INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps 1 or save_checkpoints_secs None. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version. Instructions for updating: Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py:65: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the `tf.data` module. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_functions.py:491: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the `tf.data` module. INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Create CheckpointSaverHook. INFO:tensorflow:Graph was finalized. INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow/python/training/monitored_session.py:907: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the `tf.data` module. INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0... INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0... INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 1... INFO:tensorflow:Saving checkpoints for 1 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 1... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:45 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-1 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.25105s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:45 INFO:tensorflow:Saving dict for global step 1: accuracy = 0.16328125, average_loss = 2.2459474, global_step = 1, loss = 287.48126 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 1: /tmp/tmp9w0s5sgg/model.ckpt-1 INFO:tensorflow:loss = 115.65201, step = 0 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 2... INFO:tensorflow:Saving checkpoints for 2 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 2... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:46 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-2 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24542s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:46 INFO:tensorflow:Saving dict for global step 2: accuracy = 0.25625, average_loss = 2.1821105, global_step = 2, loss = 279.31015 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2: /tmp/tmp9w0s5sgg/model.ckpt-2 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 3... INFO:tensorflow:Saving checkpoints for 3 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 3... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:46 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-3 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24425s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:46 INFO:tensorflow:Saving dict for global step 3: accuracy = 0.3, average_loss = 2.1269565, global_step = 3, loss = 272.25043 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 3: /tmp/tmp9w0s5sgg/model.ckpt-3 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 4... INFO:tensorflow:Saving checkpoints for 4 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 4... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:47 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-4 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.25865s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:47 INFO:tensorflow:Saving dict for global step 4: accuracy = 0.3484375, average_loss = 2.0719538, global_step = 4, loss = 265.21008 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 4: /tmp/tmp9w0s5sgg/model.ckpt-4 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 5... INFO:tensorflow:Saving checkpoints for 5 into /tmp/tmp9w0s5sgg/model.ckpt. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow/python/training/saver.py:971: remove_checkpoint (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version. Instructions for updating: Use standard file APIs to delete files with this prefix. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 5... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:47 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-5 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.23830s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:47 INFO:tensorflow:Saving dict for global step 5: accuracy = 0.40078124, average_loss = 2.013233, global_step = 5, loss = 257.69382 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 5: /tmp/tmp9w0s5sgg/model.ckpt-5 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 6... INFO:tensorflow:Saving checkpoints for 6 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 6... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:48 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-6 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24491s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:48 INFO:tensorflow:Saving dict for global step 6: accuracy = 0.45546874, average_loss = 1.9495137, global_step = 6, loss = 249.53775 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 6: /tmp/tmp9w0s5sgg/model.ckpt-6 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 7... INFO:tensorflow:Saving checkpoints for 7 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 7... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:48 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-7 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24294s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:49 INFO:tensorflow:Saving dict for global step 7: accuracy = 0.4984375, average_loss = 1.8863195, global_step = 7, loss = 241.4489 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 7: /tmp/tmp9w0s5sgg/model.ckpt-7 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 8... INFO:tensorflow:Saving checkpoints for 8 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 8... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:49 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-8 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24205s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:49 INFO:tensorflow:Saving dict for global step 8: accuracy = 0.50390625, average_loss = 1.8260235, global_step = 8, loss = 233.731 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 8: /tmp/tmp9w0s5sgg/model.ckpt-8 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 9... INFO:tensorflow:Saving checkpoints for 9 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 9... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:49 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-9 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24289s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:50 INFO:tensorflow:Saving dict for global step 9: accuracy = 0.5046875, average_loss = 1.770147, global_step = 9, loss = 226.57881 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 9: /tmp/tmp9w0s5sgg/model.ckpt-9 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 10... INFO:tensorflow:Saving checkpoints for 10 into /tmp/tmp9w0s5sgg/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 10... INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-09-22T20:09:50 INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmp9w0s5sgg/model.ckpt-10 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Evaluation [1/10] INFO:tensorflow:Evaluation [2/10] INFO:tensorflow:Evaluation [3/10] INFO:tensorflow:Evaluation [4/10] INFO:tensorflow:Evaluation [5/10] INFO:tensorflow:Evaluation [6/10] INFO:tensorflow:Evaluation [7/10] INFO:tensorflow:Evaluation [8/10] INFO:tensorflow:Evaluation [9/10] INFO:tensorflow:Evaluation [10/10] INFO:tensorflow:Inference Time : 0.24503s INFO:tensorflow:Finished evaluation at 2021-09-22-20:09:50 INFO:tensorflow:Saving dict for global step 10: accuracy = 0.50859374, average_loss = 1.7165858, global_step = 10, loss = 219.72298 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 10: /tmp/tmp9w0s5sgg/model.ckpt-10 INFO:tensorflow:Loss for final step: 82.50392. ({'accuracy': 0.50859374, 'average_loss': 1.7165858, 'loss': 219.72298, 'global_step': 10}, [])
%tensorboard --logdir {classifier.model_dir}
TensorFlow 2: TensorBoard dengan callback Keras dan Model.fit
Dalam contoh TensorFlow 2 ini, Anda membuat dan menyimpan log dengan callback tf.keras.callbacks.TensorBoard
, dan melatih modelnya. Callback melacak akurasi dan kerugian per zaman. Itu diteruskan ke Model.fit
dalam daftar callbacks
.
%reload_ext tensorboard
def create_model():
return tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(512, activation='relu'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation='softmax')
])
model = create_model()
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'],
steps_per_execution=10)
log_dir = tempfile.mkdtemp()
tensorboard_callback = tf.keras.callbacks.TensorBoard(
log_dir=log_dir,
histogram_freq=1) # Enable histogram computation with each epoch.
model.fit(x=x_train,
y=y_train,
epochs=10,
validation_data=(x_test, y_test),
callbacks=[tensorboard_callback])
Epoch 1/10 1875/1875 [==============================] - 4s 2ms/step - loss: 0.2205 - accuracy: 0.9351 - val_loss: 0.1078 - val_accuracy: 0.9675 Epoch 2/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0958 - accuracy: 0.9711 - val_loss: 0.0852 - val_accuracy: 0.9716 Epoch 3/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0685 - accuracy: 0.9786 - val_loss: 0.0728 - val_accuracy: 0.9772 Epoch 4/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0525 - accuracy: 0.9834 - val_loss: 0.0694 - val_accuracy: 0.9786 Epoch 5/10 1875/1875 [==============================] - 3s 1ms/step - loss: 0.0429 - accuracy: 0.9860 - val_loss: 0.0705 - val_accuracy: 0.9784 Epoch 6/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0369 - accuracy: 0.9876 - val_loss: 0.0616 - val_accuracy: 0.9822 Epoch 7/10 1875/1875 [==============================] - 3s 1ms/step - loss: 0.0316 - accuracy: 0.9897 - val_loss: 0.0777 - val_accuracy: 0.9787 Epoch 8/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0267 - accuracy: 0.9910 - val_loss: 0.0709 - val_accuracy: 0.9806 Epoch 9/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0239 - accuracy: 0.9918 - val_loss: 0.0651 - val_accuracy: 0.9835 Epoch 10/10 1875/1875 [==============================] - 3s 2ms/step - loss: 0.0225 - accuracy: 0.9920 - val_loss: 0.0713 - val_accuracy: 0.9819 <keras.callbacks.History at 0x7f3b2c590310>
%tensorboard --logdir {tensorboard_callback.log_dir}
Langkah selanjutnya
- Pelajari lebih lanjut tentang TensorBoard di panduan Memulai .
- Untuk API tingkat yang lebih rendah, lihat panduan migrasi tf.summary ke TensorFlow 2 .