我正在使用sklearn中的一包角色特征模型和一个自定义估算器：
我正在使用Mac，而Tensorflow几乎不使用我的2个CPU内核，而Keras使用了所有这些内核 .
配置参数：
config_proto = tf.ConfigProto(allow_soft_placement=True, inter_op_parallelism_threads=8, intra_op_parallelism_threads=32, device_count = {'CPU':4})
config_estimator = tf.estimator.RunConfig(session_config=config_proto)
分类：
classifier = tf.estimator.Estimator(model_fn=my_model_fn,\
params={'feature_columns':make_feat_cols(), 'hidden_units':[20,20,20], 'n_classes':2}, model_dir='checkpoints', config=config_estimator)
只是一个简单的密集神经网络 .
def inputs_fn(X,y):
#converts pandas dataframe/series into a dict-like function
dataset = tf.estimator.inputs.pandas_input_fn(X,y, shuffle=True, batch_size=500, num_epochs=10, queue_capacity=200000)
return dataset
在线搜索，似乎pandas_input_fn可能是减速的原因，但我不确定 . 测试集是6000个特征x 30000个条目 .
为了它的 Value ，这是我在运行训练后从python profiler得到的：
ncalls tottime percall cumtime percall filename:lineno(function)
2723/1 0.230 0.000 3752.153 3752.153 {built-in method builtins.exec}
1 0.005 0.005 3752.153 3752.153 Estimator_testing.py:1(<module>)
618 0.002 0.000 3473.290 5.620 /usr/local/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py:550(run)
618 0.002 0.000 3473.288 5.620 /usr/local/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py:1035(run)
618 0.007 0.000 3473.286 5.620 /usr/local/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py:1117(run)
618 0.038 0.000 3473.279 5.620 /usr/local/lib/python3.6/site-packages/tensorflow/python/training/monitored_session.py:1170(run)
1 0.000 0.000 3395.453 3395.453 /usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py:295(train)
1 0.000 0.000 3395.453 3395.453 /usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py:839(_train_model)
1 0.001 0.001 3395.453 3395.453 /usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py:845(_train_model_default)
651 0.020 0.000 3358.462 5.159 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:790(run)
651 0.070 0.000 3358.173 5.158 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1046(_run)
651 0.007 0.000 3357.739 5.158 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1271(_do_run)
651 0.002 0.000 3357.682 5.158 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1320(_do_call)
651 0.003 0.000 3357.680 5.158 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1303(_run_fn)
651 0.003 0.000 3354.512 5.153 /usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1404(_call_tf_sessionrun)
什么是最好的事情 - 摆脱pandas_input_fn？
偏离主题：这个自定义估算器以某种方式在测试数据上达到95％的准确率，而在keras上达到92％ . 但是，在预测时，它只能预测一个类 . 这怎么可能？
提前致谢！