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我有旨在帮助TensorFlow程序我非正式基准我用的,更重要的是,了解分析工具来与TensorFlow一个GPU。代码没有什么,但设置了两个占位符的矩阵,和MATMUL运算,然后调用会话来填充占位符和执行图形十倍。Tensorflow时间轴元回来的NaN
下面是代码:当我看tensorboard图
n = 10240
iter = 10
tf.reset_default_graph()
graph = tf.Graph()
with graph.as_default():
with tf.device("/gpu:0"):
matrix1 = tf.placeholder(tf.float32, [n, n], name="Matrix_One")
matrix2 = tf.placeholder(tf.float32, [n, n], name="Matrix_Two")
product = tf.matmul(matrix1, matrix2, name = "Matrix_Multiply")
date = datetime.now()
cwd = os.getcwd()
LogBase = cwd + "/benchmarks2/"
LogPath = LogBase + date.strftime("%Y%m%d-%H%M%S") + "/"
print(LogPath)
with tf.Session(graph=graph) as session:
tf.global_variables_initializer().run()
run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
run_metadata = tf.RunMetadata()
writer = tf.summary.FileWriter(LogPath, session.graph)
for i in range(iter):
m1 = np.random.rand(n, n)
m2 = np.random.rand(n, n)
feed_dict = { matrix1 : m1,matrix2 : m2}
p = session.run([product], feed_dict=feed_dict, options=run_options, run_metadata=run_metadata)
writer.add_run_metadata(run_metadata, 'step%2d' % i)
tf.summary.FileWriter(LogPath, graph).close()
两个特点出现:
- 注意,我跑十次迭代,但tensorboard只显示八个步骤,这似乎奇
- 最重要的是,我从来没有看到任何东西,但对于NaN的计算时间或内存,如下图所示。注意选择了矩阵倍数操作。