我在这上面已经深陷其中，无法让这个（看似）简单的线性回归工作。我知道答案可能就在眼前，但我觉得我已经盯着它太久了，看不到了 :).
回溯信息：
Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 510, in _apply_op_helper preferred_dtype=default_dtype) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1022, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 233, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 212, in constant value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 401, in make_tensor_proto raise ValueError("None values not supported.")ValueError: None values not supported.During handling of the above exception, another exception occurred:Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 524, in _apply_op_helper values, as_ref=input_arg.is_ref).dtype.name File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1022, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 233, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 212, in constant value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 401, in make_tensor_proto raise ValueError("None values not supported.")ValueError: None values not supported.During handling of the above exception, another exception occurred:Traceback (most recent call last): File "flights.py", line 143, in <module> regressor.train(input_fn=training_input_fn, steps=10000) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 314, in train loss = self._train_model(input_fn, hooks, saving_listeners) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 740, in _train_model input_fn, model_fn_lib.ModeKeys.TRAIN)) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 603, in _get_features_and_labels_from_input_fn result = self._call_input_fn(input_fn, mode) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 694, in _call_input_fn return input_fn(**kwargs) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/pandas_io.py", line 110, in input_fn features = queue.dequeue_many(batch_size) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 475, in dequeue_many self._queue_ref, n=n, component_types=self._dtypes, name=name) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2445, in _queue_dequeue_many_v2 component_types=component_types, timeout_ms=timeout_ms, name=name) File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 528, in _apply_op_helper (input_name, err))ValueError: Tried to convert 'n' to a tensor and failed. Error: None values not supported.代码： https://pastebin.com/M9arSCQa
数据文件： https://storage.googleapis.com/stackquestion2/201701.csv
更新在应用了一些建议后，错误已经改变了，然而，这个错误是我在发帖前就遇到过的，这意味着我在原地打转 🙂
这是完整的错误信息：
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_0_enqueue_input/fifo_queue' is closed and has insufficient elements (requested 128, current size 0) [[Node: fifo_queue_DequeueUpTo = QueueDequeueUpToV2[component_types=[DT_INT64, DT_STRING, DT_STRING, DT_DOUBLE, DT_STRING, ..., DT_STRING, DT_STRING, DT_STRING, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](enqueue_input/fifo_queue, fifo_queue_DequeueUpTo/n)]]最新代码： https://pastebin.com/TvCw0rVw
回答：
我认为你的问题出在这里，
training_input_fn = tf.estimator.inputs.pandas_input_fn(x=training_data, y=training_label, batch_size=None, shuffle=True, num_epochs=None)你将batch_size设置为None，这覆盖了默认参数（128），当它到达deque时，它会检查该参数。只要删除batch_size或将其设置为训练数据集大小的因数即可
