ジェネレータからの読み取り時の競合条件

Question

Python2.7でPythonプログラムを実行しています。私は、以下の手法を使って発電機の価値を印刷しようとしています。

y = m.predict(input_fn=lambda:input_fn(df_predict), as_iterable=True) 
#output of this is a generator  
print(type(y)) 
print(list(y)) 

次のエラーが表示されます。print ('Predictions: {}'.format(str(y)))出力を実行する上で

Traceback (most recent call last): 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 176, in <module> 
    tf.app.run() 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 43, in run 
    sys.exit(main(sys.argv[:1] + flags_passthrough)) 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 171, in main 
    train_and_eval() 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 167, in train_and_eval 
    print (list(y)) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 328, in _as_iterable 
    for pred in preds: 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 909, in _infer_model_as_iterable 
    restore_checkpoint_path=checkpoint_path): 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/graph_actions.py", line 867, in run_feeds_iter 
    yield session.run(output_dict, f) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 766, in run 
    run_metadata_ptr) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 964, in _run 
    feed_dict_string, options, run_metadata) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1014, in _do_run 
    target_list, options, run_metadata) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1034, in _do_call 
    raise type(e)(node_def, op, message) 
tensorflow.python.framework.errors_impl.InvalidArgumentError: WhereOp: Race condition between counting the number of true elements and writing them. When counting, saw 2645 elements; but when writing their indices, saw 19 elements. 
     [[Node: linear/linear/ip/ip_weights/Where = Where[_device="/job:localhost/replica:0/task:0/cpu:0"](linear/linear/ip/ip_weights/GreaterEqual/_409)]] 

Caused by op u'linear/linear/ip/ip_weights/Where', defined at: 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 176, in <module> 
    tf.app.run() 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 43, in run 
    sys.exit(main(sys.argv[:1] + flags_passthrough)) 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 171, in main 
    train_and_eval() 
    File "tensorflow/examples/wide_n_deep_model_predictions_v3.0.py", line 163, in train_and_eval 
    y = m.predict(input_fn=lambda:input_fn(df_predict), as_iterable=True) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/deprecation.py", line 245, in new_func 
    return func(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 747, in predict 
    as_iterable=as_iterable) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/deprecation.py", line 191, in new_func 
    return func(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 477, in predict 
    as_iterable=as_iterable) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 847, in _infer_model 
    infer_ops = self._get_predict_ops(features) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1113, in _get_predict_ops 
    return self._call_model_fn(features, labels, ModeKeys.INFER) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1026, in _call_model_fn 
    params=self.params) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 504, in _dnn_linear_combined_model_fn 
    scope=scope) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 535, in weighted_sum_from_feature_columns 
    weight_collections) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 332, in _create_embedding_lookup 
    name=column.name + '_weights') 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/layers/python/layers/embedding_ops.py", line 123, in safe_embedding_lookup_sparse 
    sparse_ids, sparse_weights = _prune_invalid_ids(sparse_ids, sparse_weights) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/layers/python/layers/embedding_ops.py", line 169, in _prune_invalid_ids 
    sparse_ids = sparse_ops.sparse_retain(sparse_ids, is_id_valid) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/sparse_ops.py", line 880, in sparse_retain 
    where_true = array_ops.reshape(array_ops.where(to_retain), [-1]) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 2501, in where 
    return gen_array_ops.where(input=condition, name=name) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 3821, in where 
    result = _op_def_lib.apply_op("Where", input=input, name=name) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op 
    op_def=op_def) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2259, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1130, in __init__ 
    self._traceback = _extract_stack() 
InvalidArgumentError (see above for traceback): WhereOp: Race condition between counting the number of true elements and writing them. When counting, saw 2645 elements; but when writing their indices, saw 19 elements. 
     [[Node: linear/linear/ip/ip_weights/Where = Where[_device="/job:localhost/replica:0/task:0/cpu:0"](linear/linear/ip/ip_weights/GreaterEqual/_409)]] 

はPredictions: <generator object _as_iterable at 0x7f1883235550>

ある誰かが、私は発電機を印刷することができますどのように私を導くことはできますか？

Answer 1

は、私はあなたが私はボストンのチュートリアルからそれを発見し、この

# Print out predictions 
y = regressor.predict(input_fn=lambda: input_fn(prediction_set)) 

# .predict() returns an iterator; convert to a list and print predictions 
predictions = list(itertools.islice(y, 6)) 
print("Predictions: {}".format(str(predictions))) 

ような何かをする必要があると思う：https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/input_fn/boston.py