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Di TensorFlow 1, untuk menyesuaikan perilaku pelatihan, Anda menggunakan tf.estimator.SessionRunHook
dengan tf.estimator.Estimator
. Panduan ini menunjukkan cara bermigrasi dari SessionRunHook
ke callback khusus TensorFlow 2 dengan tf.keras.callbacks.Callback
API, yang berfungsi dengan Keras Model.fit
untuk pelatihan (serta Model.evaluate
dan Model.predict
). Anda akan mempelajari cara melakukannya dengan menerapkan SessionRunHook
dan tugas Callback
yang mengukur contoh per detik selama pelatihan.
Contoh callback adalah penyimpanan checkpoint ( tf.keras.callbacks.ModelCheckpoint
) dan penulisan ringkasan TensorBoard . Callback Keras adalah objek yang dipanggil pada titik yang berbeda selama pelatihan/evaluasi/prediksi dalam Keras Model.fit
/ Model.evaluate
/ Model.predict
API bawaan. Anda dapat mempelajari lebih lanjut tentang panggilan balik di dokumen tf.keras.callbacks.Callback
API, serta panduan Menulis panggilan balik Anda sendiri dan Pelatihan dan evaluasi dengan metode bawaan (bagian Menggunakan panggilan balik ).
Mempersiapkan
Mulailah dengan impor dan kumpulan data sederhana untuk tujuan demonstrasi:
import tensorflow as tf
import tensorflow.compat.v1 as tf1
import time
from datetime import datetime
from absl import flags
features = [[1., 1.5], [2., 2.5], [3., 3.5]]
labels = [[0.3], [0.5], [0.7]]
eval_features = [[4., 4.5], [5., 5.5], [6., 6.5]]
eval_labels = [[0.8], [0.9], [1.]]
TensorFlow 1: Buat SessionRunHook kustom dengan tf.estimator API
Contoh TensorFlow 1 berikut menunjukkan cara menyiapkan SessionRunHook
kustom yang mengukur contoh per detik selama pelatihan. Setelah membuat hook ( LoggerHook
), berikan ke parameter hooks
dari tf.estimator.Estimator.train
.
def _input_fn():
return tf1.data.Dataset.from_tensor_slices(
(features, labels)).batch(1).repeat(100)
def _model_fn(features, labels, mode):
logits = tf1.layers.Dense(1)(features)
loss = tf1.losses.mean_squared_error(labels=labels, predictions=logits)
optimizer = tf1.train.AdagradOptimizer(0.05)
train_op = optimizer.minimize(loss, global_step=tf1.train.get_global_step())
return tf1.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)
class LoggerHook(tf1.train.SessionRunHook):
"""Logs loss and runtime."""
def begin(self):
self._step = -1
self._start_time = time.time()
self.log_frequency = 10
def before_run(self, run_context):
self._step += 1
def after_run(self, run_context, run_values):
if self._step % self.log_frequency == 0:
current_time = time.time()
duration = current_time - self._start_time
self._start_time = current_time
examples_per_sec = self.log_frequency / duration
print('Time:', datetime.now(), ', Step #:', self._step,
', Examples per second:', examples_per_sec)
estimator = tf1.estimator.Estimator(model_fn=_model_fn)
# Begin training.
estimator.train(_input_fn, hooks=[LoggerHook()])
INFO:tensorflow:Using default config. WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpe4lxk_r8 INFO:tensorflow:Using config: {'_model_dir': '/tmp/tmpe4lxk_r8', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_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/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. INFO:tensorflow:Calling model_fn. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow/python/training/adagrad.py:77: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version. Instructions for updating: Call initializer instance with the dtype argument instead of passing it to the constructor 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. INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0... INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmpe4lxk_r8/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0... Time: 2021-10-26 01:34:53.978329 , Step #: 0 , Examples per second: 6.5659573368942015 INFO:tensorflow:loss = 0.272405, step = 0 Time: 2021-10-26 01:34:54.010834 , Step #: 10 , Examples per second: 307.6243353258279 Time: 2021-10-26 01:34:54.020112 , Step #: 20 , Examples per second: 1077.700865900974 Time: 2021-10-26 01:34:54.029483 , Step #: 30 , Examples per second: 1067.1171606665819 Time: 2021-10-26 01:34:54.039412 , Step #: 40 , Examples per second: 1007.1566814743667 Time: 2021-10-26 01:34:54.048087 , Step #: 50 , Examples per second: 1152.756355641061 Time: 2021-10-26 01:34:54.056877 , Step #: 60 , Examples per second: 1137.6234777184084 Time: 2021-10-26 01:34:54.066122 , Step #: 70 , Examples per second: 1081.6752630493088 Time: 2021-10-26 01:34:54.074645 , Step #: 80 , Examples per second: 1173.2647067050827 Time: 2021-10-26 01:34:54.083555 , Step #: 90 , Examples per second: 1122.3118912554853 INFO:tensorflow:global_step/sec: 866.456 Time: 2021-10-26 01:34:54.094488 , Step #: 100 , Examples per second: 914.6685275645499 INFO:tensorflow:loss = 0.00072448375, step = 100 (0.116 sec) Time: 2021-10-26 01:34:54.104045 , Step #: 110 , Examples per second: 1046.3525009355121 Time: 2021-10-26 01:34:54.112493 , Step #: 120 , Examples per second: 1183.7949817956028 Time: 2021-10-26 01:34:54.120903 , Step #: 130 , Examples per second: 1189.0301913536498 Time: 2021-10-26 01:34:54.129681 , Step #: 140 , Examples per second: 1139.106488145352 Time: 2021-10-26 01:34:54.138138 , Step #: 150 , Examples per second: 1182.5933966786026 Time: 2021-10-26 01:34:54.146595 , Step #: 160 , Examples per second: 1182.4933746828306 Time: 2021-10-26 01:34:54.155248 , Step #: 170 , Examples per second: 1155.551147477753 Time: 2021-10-26 01:34:54.163869 , Step #: 180 , Examples per second: 1159.993362464738 Time: 2021-10-26 01:34:54.172881 , Step #: 190 , Examples per second: 1109.5455266917095 INFO:tensorflow:global_step/sec: 1129.39 Time: 2021-10-26 01:34:54.183226 , Step #: 200 , Examples per second: 966.6745027541543 INFO:tensorflow:loss = 0.004354417, step = 200 (0.088 sec) Time: 2021-10-26 01:34:54.192698 , Step #: 210 , Examples per second: 1055.8082867643357 Time: 2021-10-26 01:34:54.201008 , Step #: 220 , Examples per second: 1203.288865937975 Time: 2021-10-26 01:34:54.209423 , Step #: 230 , Examples per second: 1188.3900946336487 Time: 2021-10-26 01:34:54.218621 , Step #: 240 , Examples per second: 1087.1987350631173 Time: 2021-10-26 01:34:54.227779 , Step #: 250 , Examples per second: 1091.9538673817397 Time: 2021-10-26 01:34:54.236563 , Step #: 260 , Examples per second: 1138.4571955919873 Time: 2021-10-26 01:34:54.244876 , Step #: 270 , Examples per second: 1202.9437577078613 Time: 2021-10-26 01:34:54.253524 , Step #: 280 , Examples per second: 1156.2838396647737 Time: 2021-10-26 01:34:54.262094 , Step #: 290 , Examples per second: 1166.8671581582973 INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 300... INFO:tensorflow:Saving checkpoints for 300 into /tmp/tmpe4lxk_r8/model.ckpt. INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 300... INFO:tensorflow:Loss for final step: 0.0026133624. <tensorflow_estimator.python.estimator.estimator.Estimator at 0x7f9750e2efd0>
TensorFlow 2: Buat panggilan balik Keras khusus untuk Model.fit
Di TensorFlow 2, saat Anda menggunakan Keras Model.fit
(atau Model.evaluate
) bawaan untuk pelatihan/evaluasi, Anda dapat mengonfigurasi tf.keras.callbacks.Callback
khusus, yang kemudian Anda teruskan ke parameter callbacks
Model.fit
(atau Model.evaluate
). (Pelajari lebih lanjut di panduan Menulis panggilan balik Anda sendiri .)
Pada contoh di bawah ini, Anda akan menulis tf.keras.callbacks.Callback
khusus yang mencatat berbagai metrik—ini akan mengukur contoh per detik, yang harus sebanding dengan metrik dalam contoh SessionRunHook
sebelumnya.
class CustomCallback(tf.keras.callbacks.Callback):
def on_train_begin(self, logs = None):
self._step = -1
self._start_time = time.time()
self.log_frequency = 10
def on_train_batch_begin(self, batch, logs = None):
self._step += 1
def on_train_batch_end(self, batch, logs = None):
if self._step % self.log_frequency == 0:
current_time = time.time()
duration = current_time - self._start_time
self._start_time = current_time
examples_per_sec = self.log_frequency / duration
print('Time:', datetime.now(), ', Step #:', self._step,
', Examples per second:', examples_per_sec)
callback = CustomCallback()
dataset = tf.data.Dataset.from_tensor_slices(
(features, labels)).batch(1).repeat(100)
model = tf.keras.models.Sequential([tf.keras.layers.Dense(1)])
optimizer = tf.keras.optimizers.Adagrad(learning_rate=0.05)
model.compile(optimizer, "mse")
# Begin training.
result = model.fit(dataset, callbacks=[callback], verbose = 0)
# Provide the results of training metrics.
result.history
Time: 2021-10-26 01:34:54.545193 , Step #: 0 , Examples per second: 47.66297875435231 Time: 2021-10-26 01:34:54.558176 , Step #: 10 , Examples per second: 770.1198979123442 Time: 2021-10-26 01:34:54.570778 , Step #: 20 , Examples per second: 793.5191176192368 Time: 2021-10-26 01:34:54.583033 , Step #: 30 , Examples per second: 815.9807011400335 Time: 2021-10-26 01:34:54.595632 , Step #: 40 , Examples per second: 793.6993093007853 Time: 2021-10-26 01:34:54.607942 , Step #: 50 , Examples per second: 812.3458320421444 Time: 2021-10-26 01:34:54.619847 , Step #: 60 , Examples per second: 840.0368515922291 Time: 2021-10-26 01:34:54.632529 , Step #: 70 , Examples per second: 788.4919351806594 Time: 2021-10-26 01:34:54.646415 , Step #: 80 , Examples per second: 720.1881900444719 Time: 2021-10-26 01:34:54.659728 , Step #: 90 , Examples per second: 751.1154886194731 Time: 2021-10-26 01:34:54.672811 , Step #: 100 , Examples per second: 764.3517877318949 Time: 2021-10-26 01:34:54.685740 , Step #: 110 , Examples per second: 773.5000461041955 Time: 2021-10-26 01:34:54.698443 , Step #: 120 , Examples per second: 787.2192192192192 Time: 2021-10-26 01:34:54.711277 , Step #: 130 , Examples per second: 779.161449722279 Time: 2021-10-26 01:34:54.725101 , Step #: 140 , Examples per second: 723.355408388521 Time: 2021-10-26 01:34:54.738438 , Step #: 150 , Examples per second: 749.7861994994637 Time: 2021-10-26 01:34:54.752388 , Step #: 160 , Examples per second: 716.8280010937927 Time: 2021-10-26 01:34:54.765563 , Step #: 170 , Examples per second: 759.0538755270826 Time: 2021-10-26 01:34:54.779201 , Step #: 180 , Examples per second: 733.295569775167 Time: 2021-10-26 01:34:54.792040 , Step #: 190 , Examples per second: 778.8865366759517 Time: 2021-10-26 01:34:54.804998 , Step #: 200 , Examples per second: 771.664274938367 Time: 2021-10-26 01:34:54.818003 , Step #: 210 , Examples per second: 768.9762393663831 Time: 2021-10-26 01:34:54.831546 , Step #: 220 , Examples per second: 738.3428098649814 Time: 2021-10-26 01:34:54.845028 , Step #: 230 , Examples per second: 741.7245525924878 Time: 2021-10-26 01:34:54.858053 , Step #: 240 , Examples per second: 767.7375896910236 Time: 2021-10-26 01:34:54.871158 , Step #: 250 , Examples per second: 763.0585624101734 Time: 2021-10-26 01:34:54.883612 , Step #: 260 , Examples per second: 802.922010796738 Time: 2021-10-26 01:34:54.896472 , Step #: 270 , Examples per second: 777.6301981941895 Time: 2021-10-26 01:34:54.909765 , Step #: 280 , Examples per second: 752.2740561384629 Time: 2021-10-26 01:34:54.922856 , Step #: 290 , Examples per second: 763.8645759347284 {'loss': [0.33093082904815674]}
Langkah selanjutnya
Pelajari lebih lanjut tentang panggilan balik di:
- Dokumen API:
tf.keras.callbacks.Callback
- Panduan: Menulis panggilan balik Anda sendiri
- Panduan: Pelatihan dan evaluasi dengan metode bawaan (bagian Menggunakan panggilan balik )
Anda mungkin juga menemukan sumber daya terkait migrasi berikut ini berguna:
- Panduan migrasi penghentian awal :
tf.keras.callbacks.EarlyStopping
adalah panggilan balik penghentian awal bawaan - Panduan migrasi TensorBoard : TensorBoard memungkinkan pelacakan dan menampilkan metrik
- Panduan migrasi panggilan balik LoggingTensorHook dan StopAtStepHook ke Keras