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私は、1つのTFRecordファイルに多くのcsvファイルをロードしようとしていますが、そのTFRecordを私のモデルに送ることができます。私はすべて私のコードであり、私は自分が思っていることについてそれを打破しようとしました。TFRecords QueueRunnerエラー
データを生成します。ターゲット変数は最後の列になります。
for i in range(10):
filename = './Data/random_csv' + str(i) + '.csv'
pd.DataFrame(np.random.randint(0,100,size=(100, 50))).to_csv(filename)
機能TFRecordがパンダにCSVをロードするための機能
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
def _float_feature(value):
return tf.train.Feature(float_list=tf.train.FloatList(value=[value]))
def _bytes_feature(value):
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
def make_q_list(filepathlist, filetype):
filepathlist = filepathlist
filepaths = []
labels = []
for path in filepathlist:
data_files = os.listdir(path)
for data in data_files:
if data.endswith(filetype):
data_file = os.path.join(path, data)
data_file = data_file
data_label = os.path.basename(os.path.normpath(path))
filepaths.append(data_file)
labels.append(data_label)
return filepaths, labels
def rnn_list_format(df):
input_data_list = []
output_data_list = []
y = df[df.columns[-1]]
X = df[df.columns[:-1]]
for i in range(len(df)):
output_data_list.append(y.loc[i])
input_data_list.append(X.loc[i].as_matrix())
return input_data_list, output_data_list
def data_split(df):
y = df[df.columns[-1]]
X = df[df.columns[:-1]]
X, y = X.as_matrix(), y.as_matrix()
return X, y
ファイル作ります。そして最後の列をとり、ターゲット変数yにします。パンダのデータフレームは、numpy配列に変換され、TFRecordsファイルに書き込まれます。
def tables_to_TF(queue_list, tf_filename, file_type='csv'):
#Target variable needs to be the last column of data
filepath = os.path.join(tf_filename)
print('Writing', filepath)
writer = tf.python_io.TFRecordWriter(tf_filename)
for file in tqdm(queue_list):
if file_type == 'csv':
data = pd.read_csv(file)
X, y = data_split(data)
elif file_type == 'hdf':
data = pd.read_hdf(file)
X, y = data_split(data)
else:
print(file_type, 'is not supported at this time...')
break
rec_count = X.shape[0]
for index in range(rec_count):
_X = np.asarray(X[index]).tostring()
_y = np.asarray(y[index]).tostring()
example = tf.train.Example(features=tf.train.Features(feature={
'X': _bytes_feature(_X),
'y': _bytes_feature(_y)}))
writer.write(example.SerializeToString())
TFRecordsファイルを読み出す機能。
def read_and_decode(filename_queue, datashape=160*160*3):
reader = tf.TFRecordReader()
_, serialized_example = reader.read(filename_queue)
features = tf.parse_single_example(
serialized_example,
features={
'X': tf.FixedLenFeature([], tf.string),
'y': tf.FixedLenFeature([], tf.string)
})
X = tf.decode_raw(features['X'], tf.float32)
X.set_shape([datashape])
X = tf.cast(X, tf.float32)
y = tf.decode_raw(features['y'], tf.float32)
y.set_shape([1])
y = tf.cast(y, tf.float32)
return X, y
が作成されたデータからTFRecordファイルを作成します
def inputs(train_dir, file, batch_size, num_epochs, n_classes, one_hot_labels=False, datashape=160*160*3):
if not num_epochs: num_epochs = None
filename = os.path.join(train_dir, file)
with tf.name_scope('input'):
filename_queue = tf.train.string_input_producer(
[filename], num_epochs=num_epochs)
X, y = read_and_decode(filename_queue, datashape)
if one_hot_labels:
label = tf.one_hot(label, n_classes, dtype=tf.int32)
example_batch, label_batch = tf.train.shuffle_batch(
[X, y], batch_size=batch_size, num_threads=2,
capacity=2000, enqueue_many=False,
# Ensures a minimum amount of shuffling of examples.
min_after_dequeue=1000, name=file)
return example_batch, label_batch
Tensorflowでバッチを作成しました。
filepathlist = ['./Data']
q, _ = make_q_list(filepathlist, '.csv')
tffilename = 'Demo_TFR.tfrecords'
tables_to_TF(q, tffilename, file_type='csv')
queueRunnerにTFRecordファイルをロードしよう。
X_train_batch, y_train_batch = inputs('./',
'Demo_TFR.tfrecords',
50,
1,
0,
one_hot_labels=False,
datashape=50)
sess = tf.Session()
init_op = tf.group(tf.global_variables_initializer())
sess.run(init_op)
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
sess.run([X_train_batch, y_train_batch])
ERROR
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.FailedPreconditionError'>, Attempting to use uninitialized value input/input_producer/limit_epochs/epochs
[[Node: input/input_producer/limit_epochs/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@input/input_producer/limit_epochs/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/cpu:0"](input/input_producer/limit_epochs/epochs)]]
Caused by op 'input/input_producer/limit_epochs/CountUpTo', defined at:
File "/home/mcamp/anaconda3/lib/python3.5/runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "/home/mcamp/anaconda3/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-13-a00f528d3e80>", line 7, in <module>
datashape=50)
File "<ipython-input-11-468d0a66f589>", line 94, in inputs
[filename], num_epochs=num_epochs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 230, in string_input_producer
cancel_op=cancel_op)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 156, in input_producer
input_tensor = limit_epochs(input_tensor, num_epochs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 96, in limit_epochs
counter = epochs.count_up_to(num_epochs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 652, in count_up_to
return state_ops.count_up_to(self._variable, limit=limit)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_state_ops.py", line 126, in count_up_to
result = _op_def_lib.apply_op("CountUpTo", ref=ref, limit=limit, name=name)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
op_def=op_def)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value input/input_producer/limit_epochs/epochs
[[Node: input/input_producer/limit_epochs/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@input/input_producer/limit_epochs/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/cpu:0"](input/input_producer/limit_epochs/epochs)]]
---------------------------------------------------------------------------
OutOfRangeError Traceback (most recent call last)
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1020 try:
-> 1021 return fn(*args)
1022 except errors.OpError as e:
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1002 feed_dict, fetch_list, target_list,
-> 1003 status, run_metadata)
1004
/home/mcamp/anaconda3/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
468 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 469 pywrap_tensorflow.TF_GetCode(status))
470 finally:
OutOfRangeError: RandomShuffleQueue '_7_input_1/Demo_TFR.tfrecords/random_shuffle_queue' is closed and has insufficient elements (requested 50, current size 0)
[[Node: input_1/Demo_TFR.tfrecords = QueueDequeueMany[_class=["loc:@input_1/Demo_TFR.tfrecords/random_shuffle_queue"], component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](input_1/Demo_TFR.tfrecords/random_shuffle_queue, input_1/Demo_TFR.tfrecords/n)]]
During handling of the above exception, another exception occurred:
OutOfRangeError Traceback (most recent call last)
<ipython-input-17-a00f528d3e80> in <module>()
12 coord = tf.train.Coordinator()
13 threads = tf.train.start_queue_runners(sess=sess, coord=coord)
---> 14 sess.run([X_train_batch, y_train_batch])
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
764 try:
765 result = self._run(None, fetches, feed_dict, options_ptr,
--> 766 run_metadata_ptr)
767 if run_metadata:
768 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
962 if final_fetches or final_targets:
963 results = self._do_run(handle, final_targets, final_fetches,
--> 964 feed_dict_string, options, run_metadata)
965 else:
966 results = []
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1012 if handle is None:
1013 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1014 target_list, options, run_metadata)
1015 else:
1016 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1032 except KeyError:
1033 pass
-> 1034 raise type(e)(node_def, op, message)
1035
1036 def _extend_graph(self):
OutOfRangeError: RandomShuffleQueue '_7_input_1/Demo_TFR.tfrecords/random_shuffle_queue' is closed and has insufficient elements (requested 50, current size 0)
[[Node: input_1/Demo_TFR.tfrecords = QueueDequeueMany[_class=["loc:@input_1/Demo_TFR.tfrecords/random_shuffle_queue"], component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](input_1/Demo_TFR.tfrecords/random_shuffle_queue, input_1/Demo_TFR.tfrecords/n)]]
Caused by op 'input_1/Demo_TFR.tfrecords', defined at:
File "/home/mcamp/anaconda3/lib/python3.5/runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "/home/mcamp/anaconda3/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-17-a00f528d3e80>", line 7, in <module>
datashape=50)
File "<ipython-input-15-468d0a66f589>", line 105, in inputs
min_after_dequeue=1000, name=file)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 917, in shuffle_batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1099, in _queue_dequeue_many
timeout_ms=timeout_ms, name=name)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
op_def=op_def)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/mcamp/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): RandomShuffleQueue '_7_input_1/Demo_TFR.tfrecords/random_shuffle_queue' is closed and has insufficient elements (requested 50, current size 0)
[[Node: input_1/Demo_TFR.tfrecords = QueueDequeueMany[_class=["loc:@input_1/Demo_TFR.tfrecords/random_shuffle_queue"], component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](input_1/Demo_TFR.tfrecords/random_shuffle_queue, input_1/Demo_TFR.tfrecords/n)]]
EDIT： 以下のコードは、問題の根本的な原因であると思われるものです。私はTFRecordファイルを正しく解析していないと思う（duh *）。おそらく私は正しいデータ型としてそれを読んでいないと思います。ほぼ完全に同じコードは、TFRecordに画像を読み込んで返します。違いは、float32の値をすべて送信しようとしていることです。
def read_and_decode(filename_queue, datashape=160*160*3):
reader = tf.TFRecordReader()
_, serialized_example = reader.read(filename_queue)
features = tf.parse_single_example(
serialized_example,
features={
'X': tf.FixedLenFeature([], tf.string),
'y': tf.FixedLenFeature([], tf.string)
})
X = tf.decode_raw(features['X'], tf.float32)
X.set_shape([datashape])
X = tf.cast(X, tf.float32)
y = tf.decode_raw(features['y'], tf.float32)
y.set_shape([1])
y = tf.cast(y, tf.float32)
return X, y
これでもう少し遊んでいると、問題は私のread_and_decode関数にあるようです...実行しようとすると、プログラムはただ座って何もしません。助言がありますか？ –
問題を小さな自己完結型のサンプルにまで引き上げることはできますか？問題を簡単に解決するためにコードが多すぎます。 –
上記のコードはすべて自己完結型です。実行され、上記のエラーが発生します。 以下のコード行が主な問題だと思われますが、何が間違っているのか分かりません。私の推測では、間違ったデータ型としてTFRecordファイルを読み込んでいますが、わかりません。 'X、y = read_and_decode（filename_queue、datashape）' –