این صفحه به‌وسیله ‏Cloud Translation API‏ ترجمه شده است.

Migrate TensorBoard: جعبه ابزار تجسم TensorFlow

مشاهده در TensorFlow.org

در Google Colab اجرا شود

مشاهده منبع در GitHub

دانلود دفترچه یادداشت

TensorBoard یک ابزار داخلی برای ارائه اندازه گیری ها و تجسم ها در TensorFlow است. معیارهای رایج آزمایش یادگیری ماشین، مانند دقت و از دست دادن، را می توان در TensorBoard ردیابی و نمایش داد. TensorBoard با کدهای TensorFlow 1 و 2 سازگار است.

در TensorFlow 1، tf.estimator.Estimator خلاصه ها را برای TensorBoard به طور پیش فرض ذخیره می کند. در مقایسه، در TensorFlow 2، خلاصه ها را می توان با استفاده از یک پاسخ تماس tf.keras.callbacks.TensorBoard ذخیره کرد.

این راهنما نحوه استفاده از TensorBoard، ابتدا در TensorFlow 1 با تخمین‌گرها و سپس نحوه انجام فرآیند معادل در TensorFlow 2 را نشان می‌دهد.

برپایی

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 با tf.estimator

در این مثال TensorFlow 1، یک tf.estimator.DNNClassifier را نمونه‌سازی می‌کنید، آن را در مجموعه داده‌های MNIST آموزش می‌دهید و ارزیابی می‌کنید، و از TensorBoard برای نمایش معیارها استفاده می‌کنید:

%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 با فراخوان Keras و Model.fit

در این مثال TensorFlow 2، شما لاگ‌ها را با tf.keras.callbacks.TensorBoard ایجاد و ذخیره می‌کنید و مدل را آموزش می‌دهید. تماس برگشتی دقت و ضرر را در هر دوره ردیابی می کند. در لیست callbacks به Model.fit می شود.

%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}

مراحل بعدی

درباره TensorBoard در راهنمای شروع کار بیشتر بیاموزید.
برای APIهای سطح پایین تر، به راهنمای انتقال tf.summary به TensorFlow 2 مراجعه کنید.