Trainer.py 12.8 KB
Newer Older
1 2 3 4 5 6
#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
# @date: Tue 09 Aug 2016 15:25:22 CEST

import tensorflow as tf
7 8 9
import threading
import os
import bob.io.base
10
import bob.core
11
from ..analyzers import SoftmaxAnalizer
12
from tensorflow.core.framework import summary_pb2
13
import time
14
from bob.learn.tensorflow.datashuffler import OnlineSampling, TFRecord
15
from bob.learn.tensorflow.utils.session import Session
16
from .learning_rate import constant
17
import time
18

19 20 21 22 23
#logger = bob.core.log.setup("bob.learn.tensorflow")

import logging
logger = logging.getLogger("bob.learn")

24

25 26 27
class Trainer(object):
    """
    One graph trainer.
28

29 30 31
    Use this trainer when your CNN is composed by one graph

    **Parameters**
32

Tiago Pereira's avatar
Tiago Pereira committed
33 34
    train_data_shuffler:
      The data shuffler used for batching data for training
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
35

Tiago Pereira's avatar
Tiago Pereira committed
36
    iterations:
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
37
      Maximum number of iterations
38

Tiago Pereira's avatar
Tiago Pereira committed
39
    snapshot:
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
40
      Will take a snapshot of the network at every `n` iterations
41

Tiago Pereira's avatar
Tiago Pereira committed
42 43
    validation_snapshot:
      Test with validation each `n` iterations
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
44 45 46 47

    analizer:
      Neural network analizer :py:mod:`bob.learn.tensorflow.analyzers`

Tiago Pereira's avatar
Tiago Pereira committed
48 49 50
    temp_dir: str
      The output directory

Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
51
    verbosity_level:
52 53

    """
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
54

55
    def __init__(self,
Tiago Pereira's avatar
Tiago Pereira committed
56
                 train_data_shuffler,
57

58 59
                 ###### training options ##########
                 iterations=5000,
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
60 61
                 snapshot=500,
                 validation_snapshot=100,
62 63

                 ## Analizer
64
                 analizer=SoftmaxAnalizer(),
65

Tiago Pereira's avatar
Tiago Pereira committed
66 67
                 # Temporatu dir
                 temp_dir="cnn",
68

69
                 verbosity_level=2):
70

Tiago Pereira's avatar
Tiago Pereira committed
71
        self.train_data_shuffler = train_data_shuffler
72 73
        self.temp_dir = temp_dir

74 75
        self.iterations = iterations
        self.snapshot = snapshot
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
76
        self.validation_snapshot = validation_snapshot
77

78 79 80
        # Training variables used in the fit
        self.summaries_train = None
        self.train_summary_writter = None
81
        self.thread_pool = None
82 83 84

        # Validation data
        self.validation_summary_writter = None
85
        self.summaries_validation = None
86

87 88
        # Analizer
        self.analizer = analizer
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
89
        self.global_step = None
90

91
        self.session = None
92

Tiago Pereira's avatar
Tiago Pereira committed
93 94 95 96 97 98 99 100 101 102 103
        self.graph = None
        self.loss = None
        self.predictor = None
        self.optimizer_class = None
        self.learning_rate = None
        # Training variables used in the fit
        self.optimizer = None
        self.data_ph = None
        self.label_ph = None
        self.saver = None

104 105
        bob.core.log.set_verbosity_level(logger, verbosity_level)

Tiago Pereira's avatar
Tiago Pereira committed
106 107 108
        # Creating the session
        self.session = Session.instance(new=True).session
        self.from_scratch = True
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
109

Tiago Pereira's avatar
Tiago Pereira committed
110 111 112 113
    def create_network_from_scratch(self,
                                    graph,
                                    optimizer=tf.train.AdamOptimizer(),
                                    loss=None,
114

Tiago Pereira's avatar
Tiago Pereira committed
115 116 117 118
                                    # Learning rate
                                    learning_rate=None,
                                    ):

Tiago Pereira's avatar
Tiago Pereira committed
119 120
        """
        Prepare all the tensorflow variables before training.
121

Tiago Pereira's avatar
Tiago Pereira committed
122
        **Parameters**
123

Tiago Pereira's avatar
Tiago Pereira committed
124
            graph: Input graph for training
125

Tiago Pereira's avatar
Tiago Pereira committed
126
            optimizer: Solver
127

Tiago Pereira's avatar
Tiago Pereira committed
128
            loss: Loss function
129

Tiago Pereira's avatar
Tiago Pereira committed
130 131 132
            learning_rate: Learning rate
        """

133 134
        self.data_ph = self.train_data_shuffler("data", from_queue=True)
        self.label_ph = self.train_data_shuffler("label", from_queue=True)
Tiago Pereira's avatar
Tiago Pereira committed
135 136
        self.graph = graph
        self.loss = loss
137
        self.predictor = self.loss(self.graph, self.label_ph)
138

Tiago Pereira's avatar
Tiago Pereira committed
139 140
        self.optimizer_class = optimizer
        self.learning_rate = learning_rate
141

142
        self.global_step = tf.contrib.framework.get_or_create_global_step()
Tiago Pereira's avatar
Tiago Pereira committed
143 144 145 146

        # Saving all the variables
        self.saver = tf.train.Saver(var_list=tf.global_variables())

Tiago Pereira's avatar
Tiago Pereira committed
147
        tf.add_to_collection("global_step", self.global_step)
148

Tiago Pereira's avatar
Tiago Pereira committed
149 150
        tf.add_to_collection("graph", self.graph)
        tf.add_to_collection("predictor", self.predictor)
151

Tiago Pereira's avatar
Tiago Pereira committed
152 153
        tf.add_to_collection("data_ph", self.data_ph)
        tf.add_to_collection("label_ph", self.label_ph)
154

Tiago Pereira's avatar
Tiago Pereira committed
155 156 157 158 159
        # Preparing the optimizer
        self.optimizer_class._learning_rate = self.learning_rate
        self.optimizer = self.optimizer_class.minimize(self.predictor, global_step=self.global_step)
        tf.add_to_collection("optimizer", self.optimizer)
        tf.add_to_collection("learning_rate", self.learning_rate)
160

Tiago Pereira's avatar
Tiago Pereira committed
161 162
        self.summaries_train = self.create_general_summary()
        tf.add_to_collection("summaries_train", self.summaries_train)
163

164 165
        self.summaries_validation = self.create_general_summary()
        self.summaries_validation = tf.add_to_collection("summaries_validation", self.summaries_validation)
Tiago Pereira's avatar
Tiago Pereira committed
166

Tiago Pereira's avatar
Tiago Pereira committed
167
        # Creating the variables
168
        self.session.run(tf.local_variables_initializer())
Tiago Pereira's avatar
Tiago Pereira committed
169 170
        tf.global_variables_initializer().run(session=self.session)

171
    def create_network_from_file(self, file_name, clear_devices=True):
Tiago Pereira's avatar
Tiago Pereira committed
172
        """
Tiago Pereira's avatar
Tiago Pereira committed
173
        Bootstrap a graph from a checkpoint
Tiago Pereira's avatar
Tiago Pereira committed
174 175 176

         ** Parameters **

Tiago Pereira's avatar
Tiago Pereira committed
177
           file_name: Name of of the checkpoing
Tiago Pereira's avatar
Tiago Pereira committed
178
        """
179
        self.saver = tf.train.import_meta_graph(file_name + ".meta", clear_devices=clear_devices)
Tiago Pereira's avatar
Tiago Pereira committed
180
        self.saver.restore(self.session, file_name)
Tiago Pereira's avatar
Tiago Pereira committed
181 182

        # Loading training graph
Tiago Pereira's avatar
Tiago Pereira committed
183 184
        self.data_ph = tf.get_collection("data_ph")[0]
        self.label_ph = tf.get_collection("label_ph")[0]
Tiago Pereira's avatar
Tiago Pereira committed
185 186 187 188 189 190 191 192

        self.graph = tf.get_collection("graph")[0]
        self.predictor = tf.get_collection("predictor")[0]

        # Loding other elements
        self.optimizer = tf.get_collection("optimizer")[0]
        self.learning_rate = tf.get_collection("learning_rate")[0]
        self.summaries_train = tf.get_collection("summaries_train")[0]
193
        self.summaries_validation = tf.get_collection("summaries_validation")[0]
Tiago Pereira's avatar
Tiago Pereira committed
194 195 196 197 198
        self.global_step = tf.get_collection("global_step")[0]
        self.from_scratch = False

    def __del__(self):
        tf.reset_default_graph()
199 200 201

    def get_feed_dict(self, data_shuffler):
        """
202
        Given a data shuffler prepared the dictionary to be injected in the graph
203 204

        ** Parameters **
205 206

            data_shuffler: Data shuffler :py:class:`bob.learn.tensorflow.datashuffler.Base`
207

208
        """
209
        [data, labels] = data_shuffler.get_batch()
210

Tiago Pereira's avatar
Tiago Pereira committed
211 212
        feed_dict = {self.data_ph: data,
                     self.label_ph: labels}
213 214
        return feed_dict

215
    def fit(self, step):
216 217 218 219 220 221 222 223 224
        """
        Run one iteration (`forward` and `backward`)

        ** Parameters **
            session: Tensorflow session
            step: Iteration number

        """

225
        if self.train_data_shuffler.prefetch or isinstance(self.train_data_shuffler, TFRecord):
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
226
            _, l, lr, summary = self.session.run([self.optimizer, self.predictor,
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
227
                                                  self.learning_rate, self.summaries_train])
228 229
        else:
            feed_dict = self.get_feed_dict(self.train_data_shuffler)
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
230
            _, l, lr, summary = self.session.run([self.optimizer, self.predictor,
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
231
                                                  self.learning_rate, self.summaries_train], feed_dict=feed_dict)
232

233 234
        logger.info("Loss training set step={0} = {1}".format(step, l))
        self.train_summary_writter.add_summary(summary, step)
235

Tiago Pereira's avatar
Tiago Pereira committed
236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256
    def compute_validation(self, data_shuffler, step):
        """
        Computes the loss in the validation set

        ** Parameters **
            session: Tensorflow session
            data_shuffler: The data shuffler to be used
            step: Iteration number

        """
        pass
        # Opening a new session for validation
        #feed_dict = self.get_feed_dict(data_shuffler)
        #l, summary = self.session.run(self.predictor, self.summaries_train, feed_dict=feed_dict)
        #train_summary_writter.add_summary(summary, step)


        #summaries = [summary_pb2.Summary.Value(tag="loss", simple_value=float(l))]
        #self.validation_summary_writter.add_summary(summary_pb2.Summary(value=summaries), step)
        #logger.info("Loss VALIDATION set step={0} = {1}".format(step, l))

257
    def create_general_summary(self):
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
258
        """
259
        Creates a simple tensorboard summary with the value of the loss and learning rate
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
260
        """
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
261

262
        # Train summary
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
263
        tf.summary.scalar('loss', self.predictor)
264 265
        tf.summary.scalar('lr', self.learning_rate)
        return tf.summary.merge_all()
266

267
    def start_thread(self):
Tiago Pereira's avatar
Tiago Pereira committed
268
        """
269 270 271 272
        Start pool of threads for pre-fetching

        **Parameters**
          session: Tensorflow session
Tiago Pereira's avatar
Tiago Pereira committed
273
        """
274

275
        threads = []
276
        for n in range(self.train_data_shuffler.prefetch_threads):
277
            t = threading.Thread(target=self.load_and_enqueue, args=())
278 279 280 281
            t.daemon = True  # thread will close when parent quits
            t.start()
            threads.append(t)
        return threads
282

283
    def load_and_enqueue(self):
Tiago Pereira's avatar
Tiago Pereira committed
284
        """
285
        Injecting data in the place holder queue
286 287 288

        **Parameters**
          session: Tensorflow session
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
289

Tiago Pereira's avatar
Tiago Pereira committed
290
        """
291
        while not self.thread_pool.should_stop():
292
            [train_data, train_labels] = self.train_data_shuffler.get_batch()
293

294 295
            data_ph = self.train_data_shuffler("data", from_queue=False)
            label_ph = self.train_data_shuffler("label", from_queue=False)
296

297 298 299 300
            feed_dict = {data_ph: train_data,
                         label_ph: train_labels}

            self.session.run(self.train_data_shuffler.enqueue_op, feed_dict=feed_dict)
301

Tiago Pereira's avatar
Tiago Pereira committed
302
    def train(self, validation_data_shuffler=None):
303
        """
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
304 305 306 307
        Train the network:

         ** Parameters **
           validation_data_shuffler: Data shuffler for validation
308 309 310 311
        """

        # Creating directory
        bob.io.base.create_directories_safe(self.temp_dir)
312

313
        logger.info("Initializing !!")
314 315

        # Loading a pretrained model
Tiago Pereira's avatar
Tiago Pereira committed
316
        if self.from_scratch:
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
317
            start_step = 0
Tiago Pereira's avatar
Tiago Pereira committed
318 319
        else:
            start_step = self.global_step.eval(session=self.session)
320

Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
321 322
        #if isinstance(train_data_shuffler, OnlineSampling):
        #    train_data_shuffler.set_feature_extractor(self.architecture, session=self.session)
323 324

        # Start a thread to enqueue data asynchronously, and hide I/O latency.
Tiago Pereira's avatar
Tiago Pereira committed
325 326 327 328
        if self.train_data_shuffler.prefetch:
            self.thread_pool = tf.train.Coordinator()
            tf.train.start_queue_runners(coord=self.thread_pool, sess=self.session)
            threads = self.start_thread()
329 330 331 332
            #time.sleep(20) # As suggested in https://stackoverflow.com/questions/39840323/benchmark-of-howto-reading-data/39842628#39842628
            
            
        # TODO: JUST FOR TESTING THE INTEGRATION
333
        #import ipdb; ipdb.set_trace();
334 335 336 337 338
        if isinstance(self.train_data_shuffler, TFRecord):
            self.thread_pool = tf.train.Coordinator()
            threads = tf.train.start_queue_runners(coord=self.thread_pool, sess=self.session)
 
        
339 340

        # TENSOR BOARD SUMMARY
341
        self.train_summary_writter = tf.summary.FileWriter(os.path.join(self.temp_dir, 'train'), self.session.graph)
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
342 343 344
        if validation_data_shuffler is not None:
            self.validation_summary_writter = tf.summary.FileWriter(os.path.join(self.temp_dir, 'validation'),
                                                                    self.session.graph)
Tiago Pereira's avatar
Tiago Pereira committed
345
        # Loop for
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
346
        for step in range(start_step, self.iterations):
Tiago Pereira's avatar
Tiago Pereira committed
347
            # Run fit in the graph
348
            start = time.time()
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
349
            self.fit(step)
350
            end = time.time()
351

352 353 354 355
            summary = summary_pb2.Summary.Value(tag="elapsed_time", simple_value=float(end-start))
            self.train_summary_writter.add_summary(summary_pb2.Summary(value=[summary]), step)

            # Running validation
Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
356 357
            if validation_data_shuffler is not None and step % self.validation_snapshot == 0:
                self.compute_validation(validation_data_shuffler, step)
358

Tiago de Freitas Pereira's avatar
Tiago de Freitas Pereira committed
359 360 361
                #if self.analizer is not None:
                #    self.validation_summary_writter.add_summary(self.analizer(
                #         validation_data_shuffler, self.architecture, self.session), step)
362 363 364 365 366

            # Taking snapshot
            if step % self.snapshot == 0:
                logger.info("Taking snapshot")
                path = os.path.join(self.temp_dir, 'model_snapshot{0}.ckp'.format(step))
Tiago Pereira's avatar
Tiago Pereira committed
367
                self.saver.save(self.session, path, global_step=step)
368 369 370 371 372 373 374 375 376

        logger.info("Training finally finished")

        self.train_summary_writter.close()
        if validation_data_shuffler is not None:
            self.validation_summary_writter.close()

        # Saving the final network
        path = os.path.join(self.temp_dir, 'model.ckp')
Tiago Pereira's avatar
Tiago Pereira committed
377
        self.saver.save(self.session, path)
378

379
        if self.train_data_shuffler.prefetch or isinstance(self.train_data_shuffler, TFRecord):
380 381
            # now they should definetely stop
            self.thread_pool.request_stop()
382
            self.thread_pool.join(threads)