Question

我正在通过发布的教程开始使用TensorFlow。

我在Fedora 23上运行Linux CPU python2.7版本0.10.0（二十三）。

我正在按照以下代码尝试tf.contrib.learn快速入门教程。

https://www.tensorflow.org/versions/r0.10/tutorials/tflearn/index.html#tf-contrib-learn-quickstart

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf
import numpy as np

# Data sets
IRIS_TRAINING = "IRIS_data/iris_training.csv"
IRIS_TEST = "IRIS_data/iris_test.csv"

# Load datasets.
training_set = tf.contrib.learn.datasets.base.load_csv(filename=IRIS_TRAINING,
                                                   target_dtype=np.int)
test_set = tf.contrib.learn.datasets.base.load_csv(filename=IRIS_TEST,
                                               target_dtype=np.int)

# Specify that all features have real-value data
feature_columns = [tf.contrib.layers.real_valued_column("", dimension=4)]

# Build 3 layer DNN with 10, 20, 10 units respectively.
classifier = tf.contrib.learn.DNNClassifier(feature_columns=feature_columns,
                                        hidden_units=[10, 20, 10],
                                        n_classes=3,
                                        model_dir="/tmp/iris_model")

# Fit model.
classifier.fit(x=training_set.data, 
           y=training_set.target, 
           steps=2000)

# Evaluate accuracy.
accuracy_score = classifier.evaluate(x=test_set.data,
                                 y=test_set.target)["accuracy"]
print('Accuracy: {0:f}'.format(accuracy_score))

# Classify two new flower samples.
new_samples = np.array(
[[6.4, 3.2, 4.5, 1.5], [5.8, 3.1, 5.0, 1.7]], dtype=float)
y = classifier.predict(new_samples)
print('Predictions: {}'.format(str(y)))

代码执行，但给出了float64警告。如此：

$ python confErr.py
WARNING:tensorflow:load_csv (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed after 2016-09-15.
Instructions for updating:
Please use load_csv_{with|without}_header instead.
WARNING:tensorflow:load_csv (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed after 2016-09-15.
Instructions for updating:
Please use load_csv_{with|without}_header instead.
WARNING:tensorflow:Using default config.
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:Setting feature info to TensorSignature(dtype=tf.float64, shape=TensorShape([Dimension(None), Dimension(4)]), is_sparse=False)
WARNING:tensorflow:Setting targets info to TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(None)]), is_sparse=False)
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:Given features: Tensor("input:0", shape=(?, 4), dtype=float64), required signatures: TensorSignature(dtype=tf.float64, shape=TensorShape([Dimension(None), Dimension(4)]), is_sparse=False).
WARNING:tensorflow:Given targets: Tensor("output:0", shape=(?,), dtype=int64), required signatures: TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(None)]), is_sparse=False).
Accuracy: 0.966667
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
Predictions: [1 1]

注意：将'load_csv（）'替换为'load_csv_with_header（）'会产生正确的预测。但仍然存在float64警告。

我已经尝试为training_set，test_set和new_samples明确列出dtype（np.int32; np.float32; tf.int32; tf.float32）。

我也试过'cast'feature_columns：

feature_columns = tf.cast(feature_columns, tf.float32)

float64的问题是已知的开发问题，但我想知道是否有一些解决方法？

Answer 1

我通过Git-hub从开发团队收到了这个答案。

您好@qweelar，float64警告是由于在commit b6813bd中修复了load_csv_with_header函数的错误。此修复程序不在TensorFlow版本0.10中，但应该在下一版本中。

与此同时，出于tf.contrib.learn快速入门的目的，您可以安全地忽略float64警告。

（附注：就其他弃用警告而言，我将更新教程代码以使用load_csv_with_header，并在此问题到位时更新此问题。）

tf.contrib.learn快速入门：修复float64警告

1 个答案: