有点晚了，但也许将来对某些访客有帮助。对于您的示例，我成功测试了以下代码段：
g = tf.Graph()run_meta = tf.Runmetadata()with g.as_default(): A = tf.Variable(tf.random_normal( [25,16] )) B = tf.Variable(tf.random_normal( [16,9] )) C = tf.matmul(A,B) # shape=[25,9] opts = tf.profiler.ProfileOptionBuilder.float_operation() flops = tf.profiler.profile(g, run_meta=run_meta, cmd='op', options=opts) if flops is not None: print('Flops should be ~',2*25*16*9) print('25 x 25 x 9 would be',2*25*25*9) # ignores internal dim, repeats first print('TF stats gives',flops.total_float_ops)也可以将分析器与
Keras以下代码段结合使用：
import tensorflow as tfimport keras.backend as Kfrom keras.applications.mobilenet import MobileNetrun_meta = tf.Runmetadata()with tf.Session(graph=tf.Graph()) as sess: K.set_session(sess) net = MobileNet(alpha=.75, input_tensor=tf.placeholder('float32', shape=(1,32,32,3))) opts = tf.profiler.ProfileOptionBuilder.float_operation() flops = tf.profiler.profile(sess.graph, run_meta=run_meta, cmd='op', options=opts) opts = tf.profiler.ProfileOptionBuilder.trainable_variables_parameter() params = tf.profiler.profile(sess.graph, run_meta=run_meta, cmd='op', options=opts) print("{:,} --- {:,}".format(flops.total_float_ops, params.total_parameters))希望我能帮上忙！
