运行tensorflow AI时出现GPU错误

Question

我正在学习初学者的TensorFlow教程并尝试分类。有很多GPU错误。我安装了cuda工具以及最新的GPU驱动程序。以下是输出：

这是我的代码：

from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf

import pandas as pd
CSV_COLUMN_NAMES = ['SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth', 'Species']
SPECIES = ['Setosa', 'Versicolor', 'Virginica']
train_path = tf.keras.utils.get_file(
    "iris_training.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_training.csv")
test_path = tf.keras.utils.get_file(
    "iris_test.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_test.csv")

train = pd.read_csv(train_path, names=CSV_COLUMN_NAMES, header=0)
test = pd.read_csv(test_path, names=CSV_COLUMN_NAMES, header=0)
# Here we use keras (a module inside of TensorFlow) to grab our datasets and read them into a pandas dataframe
train_y = train.pop('Species')
test_y = test.pop('Species')
train.head() # the species column is now gone


def input_fn(features, labels, training=True, batch_size=256):
    # Convert the inputs to a Dataset.
    dataset = tf.data.Dataset.from_tensor_slices((dict(features), labels))

    # Shuffle and repeat if you are in training mode.
    if training:
        dataset = dataset.shuffle(1000).repeat()

    return dataset.batch(batch_size)
# Feature columns describe how to use the input.
my_feature_columns = []
for key in train.keys():
    my_feature_columns.append(tf.feature_column.numeric_column(key=key))

# Build a DNN with 2 hidden layers with 30 and 10 hidden nodes each.
classifier = tf.estimator.DNNClassifier(
    feature_columns=my_feature_columns,
    # Two hidden layers of 30 and 10 nodes respectively.
    hidden_units=[30, 10],
    # The model must choose between 3 classes.
    n_classes=3)

print("starting training")

classifier.train(
    input_fn=lambda: input_fn(train, train_y, training=True),
    steps=5000)

Answer 1

根据评论

如果您想使用GPU，请确保上面提到的缺失库已正确安装。遵循GPU支持指南，了解如何下载和设置平台所需的库。