Question

我正在使用 Talos 和Google colab TPU 对 Keras 模型进行超参数调整。请注意，我使用的是 Tensorflow 1.15.0和 Keras 2.2.4-tf。

import os
import tensorflow as tf
import talos as ta
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import Adam

def iris_model(x_train, y_train, x_val, y_val, params):
    # Specify a distributed strategy to use TPU
    resolver = tf.contrib.cluster_resolver.TPUClusterResolver(tpu='grpc://' + os.environ['COLAB_TPU_ADDR'])
    tf.contrib.distribute.initialize_tpu_system(resolver)
    strategy = tf.contrib.distribute.TPUStrategy(resolver)

    # Use the strategy to create and compile a Keras model
    with strategy.scope():
      model = Sequential()
      model.add(Dense(32, input_shape=(4,), activation=tf.nn.relu, name = "relu"))
      model.add(Dense(3, activation=tf.nn.softmax, name = "softmax"))
      model.compile(optimizer=Adam(learning_rate=0.1), loss=params['losses'])

    # Fit the Keras model on the dataset
    out = model.fit(x_train, y_train,
                    batch_size=params['batch_size'], 
                    epochs=params['epochs'],
                    validation_data=[x_val, y_val],
                    verbose=0,
                    steps_per_epoch=2)

    return out, model


x, y = ta.templates.datasets.iris()

# Create a hyperparameter distributions 
p = {'losses': ['logcosh'],
     'batch_size': (20, 50, 5),
     'epochs': [10, 20]}

# Use Talos to scan the best hyperparameters of the Keras model
scan_object = ta.Scan(x, y, model=iris_model, params=p, fraction_limit=0.1, experiment_name='first_test')

使用 out = model.fit 拟合模型时，出现以下错误：

InvalidArgumentError                      Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py in _do_call(self, fn, *args)
   1382                     '\nsession_config.graph_options.rewrite_options.'
   1383                     'disable_meta_optimizer = True')
-> 1384       raise type(e)(node_def, op, message)
   1385 
   1386   def _extend_graph(self):

InvalidArgumentError: Unsupported data type for TPU: double, caused by output cond_8/Merge:0

Answer 1

最近在TPU中增加了对double的支持。您现在可以参考https://github.com/tensorflow/tensorflow/blob/d0a48afee650b12dde805fadca868d6b113c3c5d/tensorflow/core/tpu/tpu_defs.h#L52了解所有受支持的类型。

Google Colab：TPU不支持的数据类型：double，由输出cond_8 / Merge：0引起

1 个答案: