Question

我使用以下代码将准确度记录为验证度量（TensorFlow 0.10）：

  validation_metrics = {"accuracy": tf.contrib.metrics.streaming_accuracy}
  validation_monitor = tf.contrib.learn.monitors.ValidationMonitor(
                       input_fn=input_fn_eval,
                       every_n_steps=FLAGS.eval_every,
                       # metrics=validation_metrics,
                       early_stopping_rounds=500,
                       early_stopping_metric="loss",
                       early_stopping_metric_minimize=True)

运行后，在＆＃39; every_n_steps＆＃39;中，我在输出中看到以下几行：

INFO:tensorflow:Validation (step 1000): loss = 1.04875, global_step = 900

问题是当＆＃39; metrics = validation_metrics＆＃39;参数取消注释在上面的代码中，我在验证阶段得到以下错误：

INFO:tensorflow:Error reported to Coordinator: <type 'exceptions.TypeError'>, Input 'y' of 'Equal' Op has type int64 that does not match type float32 of argument 'x'.
E tensorflow/core/client/tensor_c_api.cc:485] Enqueue operation was cancelled
     [[Node: read_batch_features_train/file_name_queue/file_name_queue_EnqueueMany = QueueEnqueueMany[Tcomponents=[DT_STRING], _class=["loc:@read_batch_features_train/file_name_queue"], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](read_batch_features_train/file_name_queue, read_batch_features_train/file_name_queue/RandomShuffle)]]
E tensorflow/core/client/tensor_c_api.cc:485] Enqueue operation was cancelled
     [[Node: read_batch_features_train/random_shuffle_queue_EnqueueMany = QueueEnqueueMany[Tcomponents=[DT_STRING, DT_STRING], _class=["loc:@read_batch_features_train/random_shuffle_queue"], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](read_batch_features_train/random_shuffle_queue, read_batch_features_train/read/ReaderReadUpTo, read_batch_features_train/read/ReaderReadUpTo:1)]]
Traceback (most recent call last):
  File "udc_train.py", line 74, in <module>
    tf.app.run()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 30, in run
    sys.exit(main(sys.argv))
  File "udc_train.py", line 70, in main
    estimator.fit(input_fn=input_fn_train, steps=None, monitors=[validation_monitor])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 240, in fit
    max_steps=max_steps)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 578, in _train_model
    max_steps=max_steps)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/graph_actions.py", line 280, in _supervised_train
    None)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/supervised_session.py", line 270, in run
    run_metadata=run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/recoverable_session.py", line 54, in run
    run_metadata=run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/coordinated_session.py", line 70, in run
    self._coord.join(self._coordinated_threads_to_join)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/coordinator.py", line 357, in join
    six.reraise(*self._exc_info_to_raise)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/coordinated_session.py", line 66, in run
    return self._sess.run(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/monitored_session.py", line 107, in run
    induce_stop = monitor.step_end(monitors_step, monitor_outputs)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 396, in step_end
    return self.every_n_step_end(step, output)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 687, in every_n_step_end
    steps=self.eval_steps, metrics=self.metrics, name=self.name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 356, in evaluate
    name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 630, in _evaluate_model
    eval_dict = self._get_eval_ops(features, targets, metrics)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 877, in _get_eval_ops
    result[name] = metric(predictions, targets)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/metrics/python/ops/metric_ops.py", line 432, in streaming_accuracy
    is_correct = math_ops.to_float(math_ops.equal(predictions, labels))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 708, in equal
    result = _op_def_lib.apply_op("Equal", x=x, y=y, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 468, in apply_op
    inferred_from[input_arg.type_attr]))
TypeError: Input 'y' of 'Equal' Op has type int64 that does not match type float32 of argument 'x'.

Answer 1

这看起来像是input_fn和估算器的问题，它们会为标签返回不同的类型。

“验证监控”中的错误＆＃39;通过＆＃39;指标＆＃39;参数

1 个答案: