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TensorBoard 是一个内置工具，用于在 TensorFlow 中提供测量和呈现。可以在 TensorBoard 中跟踪和显示准确率和损失等常见的机器学习实验指标。TensorBoard 与 TensorFlow 1 和 2 代码兼容。
在 TensorFlow 1 中，tf.estimator.Estimator 默认为 TensorBoard 保存摘要。相比之下，在 TensorFlow 2 中，可以使用 tf.keras.callbacks.TensorBoard 回调保存摘要。
本指南首先演示了如何在 TensorFlow 1 中将 TensorBoard 与 Estimator 一起使用，然后演示了如何在 TensorFlow 2 中执行等效的过程。
安装
import tensorflow.compat.v1 as tf1
import tensorflow as tf
import tempfile
import numpy as np
import datetime
%load_ext tensorboard
2022-12-14 20:28:46.264152: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory 2022-12-14 20:28:46.264255: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory 2022-12-14 20:28:46.264266: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
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
TensorFlow 1：TensorBoard 与 tf.estimator 一起使用
在此 TensorFlow 1 示例中，您将实例化 tf.estimator.DNNClassifier，在 MNIST 数据集上对其进行训练和评估，并使用 TensorBoard 显示指标：
%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': '/tmpfs/tmp/tmp6t925gz_', '_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 /tmpfs/tmp/ipykernel_31731/2752664473.py:20: The name tf.estimator.inputs is deprecated. Please use tf.compat.v1.estimator.inputs instead.
WARNING:tensorflow:From /tmpfs/tmp/ipykernel_31731/2752664473.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/python3.9/site-packages/tensorflow/python/training/training_util.py:396: 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/python3.9/site-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py:60: 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/python3.9/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/python3.9/site-packages/tensorflow/python/training/monitored_session.py:910: 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.
2022-12-14 20:28:52.170464: W tensorflow/core/common_runtime/type_inference.cc:339] Type inference failed. This indicates an invalid graph that escaped type checking. Error message: INVALID_ARGUMENT: expected compatible input types, but input 1:
type_id: TFT_OPTIONAL
args {
type_id: TFT_PRODUCT
args {
type_id: TFT_TENSOR
args {
type_id: TFT_INT64
}
}
}
is neither a subtype nor a supertype of the combined inputs preceding it:
type_id: TFT_OPTIONAL
args {
type_id: TFT_PRODUCT
args {
type_id: TFT_TENSOR
args {
type_id: TFT_INT32
}
}
}
while inferring type of node 'dnn/zero_fraction/cond/output/_18'
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...
INFO:tensorflow:Saving checkpoints for 0 into /tmpfs/tmp/tmp6t925gz_/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 /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:53
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [5/10]
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INFO:tensorflow:Evaluation [7/10]
INFO:tensorflow:Evaluation [8/10]
INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.29496s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:53
INFO:tensorflow:Saving dict for global step 1: accuracy = 0.159375, average_loss = 2.2843251, global_step = 1, loss = 292.39362
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 1: /tmpfs/tmp/tmp6t925gz_/model.ckpt-1
INFO:tensorflow:loss = 118.0285, step = 0
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 2...
INFO:tensorflow:Saving checkpoints for 2 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:53
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.29514s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:54
INFO:tensorflow:Saving dict for global step 2: accuracy = 0.2359375, average_loss = 2.2260919, global_step = 2, loss = 284.93976
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2: /tmpfs/tmp/tmp6t925gz_/model.ckpt-2
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 3...
INFO:tensorflow:Saving checkpoints for 3 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:54
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.28853s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:54
INFO:tensorflow:Saving dict for global step 3: accuracy = 0.31796876, average_loss = 2.1714652, global_step = 3, loss = 277.94754
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 3: /tmpfs/tmp/tmp6t925gz_/model.ckpt-3
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 4...
INFO:tensorflow:Saving checkpoints for 4 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:55
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.28964s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:55
INFO:tensorflow:Saving dict for global step 4: accuracy = 0.371875, average_loss = 2.122491, global_step = 4, loss = 271.67883
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 4: /tmpfs/tmp/tmp6t925gz_/model.ckpt-4
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 5...
INFO:tensorflow:Saving checkpoints for 5 into /tmpfs/tmp/tmp6t925gz_/model.ckpt.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/tensorflow/python/training/saver.py:1064: remove_checkpoint (from tensorflow.python.checkpoint.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 2022-12-14T20:28:55
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.28730s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:55
INFO:tensorflow:Saving dict for global step 5: accuracy = 0.4359375, average_loss = 2.0693138, global_step = 5, loss = 264.87216
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 5: /tmpfs/tmp/tmp6t925gz_/model.ckpt-5
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 6...
INFO:tensorflow:Saving checkpoints for 6 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:56
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [7/10]
INFO:tensorflow:Evaluation [8/10]
INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.28980s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:56
INFO:tensorflow:Saving dict for global step 6: accuracy = 0.46484375, average_loss = 2.015913, global_step = 6, loss = 258.03687
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 6: /tmpfs/tmp/tmp6t925gz_/model.ckpt-6
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 7...
INFO:tensorflow:Saving checkpoints for 7 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:56
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.29669s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:57
INFO:tensorflow:Saving dict for global step 7: accuracy = 0.49765626, average_loss = 1.9582294, global_step = 7, loss = 250.65337
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 7: /tmpfs/tmp/tmp6t925gz_/model.ckpt-7
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 8...
INFO:tensorflow:Saving checkpoints for 8 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:57
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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]
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INFO:tensorflow:Evaluation [7/10]
INFO:tensorflow:Evaluation [8/10]
INFO:tensorflow:Evaluation [9/10]
INFO:tensorflow:Evaluation [10/10]
INFO:tensorflow:Inference Time : 0.28751s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:57
INFO:tensorflow:Saving dict for global step 8: accuracy = 0.53046876, average_loss = 1.8992742, global_step = 8, loss = 243.1071
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 8: /tmpfs/tmp/tmp6t925gz_/model.ckpt-8
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 9...
INFO:tensorflow:Saving checkpoints for 9 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:58
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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 : 0.29179s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:58
INFO:tensorflow:Saving dict for global step 9: accuracy = 0.56953126, average_loss = 1.8388231, global_step = 9, loss = 235.36935
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 9: /tmpfs/tmp/tmp6t925gz_/model.ckpt-9
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 10...
INFO:tensorflow:Saving checkpoints for 10 into /tmpfs/tmp/tmp6t925gz_/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 2022-12-14T20:28:58
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /tmpfs/tmp/tmp6t925gz_/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 : 0.29187s
INFO:tensorflow:Finished evaluation at 2022-12-14-20:28:58
INFO:tensorflow:Saving dict for global step 10: accuracy = 0.5859375, average_loss = 1.7800614, global_step = 10, loss = 227.84785
INFO:tensorflow:Saving 'checkpoint_path' summary for global step 10: /tmpfs/tmp/tmp6t925gz_/model.ckpt-10
INFO:tensorflow:Loss for final step: 92.82808.
({'accuracy': 0.5859375,
'average_loss': 1.7800614,
'loss': 227.84785,
'global_step': 10},
[])
%tensorboard --logdir {classifier.model_dir}
TensorFlow 2: TensorBoard 与 Keras 回调和 Model.fit 一起使用
在此 TensorFlow 2 示例中，您将使用 tf.keras.callbacks.TensorBoard 回调创建和存储日志并训练模型。回调跟踪每个周期的准确率和损失。它会被传递给 callbacks 列表中的 Model.fit。
%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: 0.2193 - accuracy: 0.9355 - val_loss: 0.1076 - val_accuracy: 0.9645 Epoch 2/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0978 - accuracy: 0.9702 - val_loss: 0.0777 - val_accuracy: 0.9752 Epoch 3/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0670 - accuracy: 0.9789 - val_loss: 0.0740 - val_accuracy: 0.9776 Epoch 4/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0531 - accuracy: 0.9830 - val_loss: 0.0686 - val_accuracy: 0.9787 Epoch 5/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0434 - accuracy: 0.9855 - val_loss: 0.0655 - val_accuracy: 0.9810 Epoch 6/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0360 - accuracy: 0.9884 - val_loss: 0.0607 - val_accuracy: 0.9818 Epoch 7/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0316 - accuracy: 0.9893 - val_loss: 0.0712 - val_accuracy: 0.9802 Epoch 8/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0263 - accuracy: 0.9912 - val_loss: 0.0714 - val_accuracy: 0.9804 Epoch 9/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0233 - accuracy: 0.9919 - val_loss: 0.0853 - val_accuracy: 0.9801 Epoch 10/10 1875/1875 [==============================] - 2s 1ms/step - loss: 0.0229 - accuracy: 0.9919 - val_loss: 0.0729 - val_accuracy: 0.9802 <keras.callbacks.History at 0x7f6d5054e790>
%tensorboard --logdir {tensorboard_callback.log_dir}
后续步骤
- 在使用入门指南中详细了解 TensorBoard。
- 对于较低级别的 API，请参阅 tf.summary 迁移到 TensorFlow 2 指南。