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Thanks for your share, you know the tensorflow update all the time,
some functions in tf maybe cause warnings.
when I run train_tfrecord.py
WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:128: string_input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.data.Dataset.from_tensor_slices(string_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs). If shuffle=False, omit the .shuffle(...). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:276: input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.data.Dataset.from_tensor_slices(input_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs). If shuffle=False, omit the .shuffle(...). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:188: limit_epochs (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.data.Dataset.from_tensors(tensor).repeat(num_epochs). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:197: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the tf.datamodule. WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:197: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use thetf.datamodule. WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:130: TFRecordReader.__init__ (from tensorflow.python.ops.io_ops) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced bytf.data. Use tf.data.TFRecordDataset. Tensor("ReaderNumRecordsProducedV2:0", shape=(), dtype=int64) Tensor("ReaderNumWorkUnitsCompletedV2:0", shape=(), dtype=int64) WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:154: shuffle_batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.data.Dataset.shuffle(min_after_dequeue).batch(batch_size)`.
Tensor("ReaderNumRecordsProducedV2_1:0", shape=(), dtype=int64)
Tensor("ReaderNumWorkUnitsCompletedV2_1:0", shape=(), dtype=int64)
training data prepared, data processing duration: 0:00:00.557883
last shape: [None, 50, 13, 256]
WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:192: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the tf.data module.
Done reading
Traceback (most recent call last):
File "D:\python\kws\KeywordSpotting-master\train_tfrecord.py", line 264, in
train_accuracies, validation_accuracies, x_range, loss_epoch, loss_epoch_val, save_path = train()
File "D:\python\kws\KeywordSpotting-master\train_tfrecord.py", line 258, in train
coord.join(threads)
File "D:\python\lib\site-packages\tensorflow\python\training\coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "D:\python\lib\site-packages\six.py", line 693, in reraise
raise value
File "D:\python\lib\site-packages\tensorflow\python\training\queue_runner_impl.py", line 257, in _run
enqueue_callable()
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1257, in _single_operation_run
self._call_tf_sessionrun(None, {}, [], target_list, None)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Key: source. Can't parse serialized Example.
[[{{node ParseSingleExample/ParseSingleExample}} = ParseSingleExample[Tdense=[DT_FLOAT, DT_FLOAT], dense_keys=["source", "target"], dense_shapes=[[650], [2]], num_sparse=0, sparse_keys=[], sparse_types=[], _device="/job:localhost/replica:0/task:0/device:CPU:0"](ReaderReadV2:1, ParseSingleExample/Const, ParseSingleExample/Const)]]`
The text was updated successfully, but these errors were encountered:
Dear,
Thanks for your share, you know the tensorflow update all the time,
some functions in tf maybe cause warnings.
when I run train_tfrecord.py
WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:128: string_input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by
tf.data. Use
tf.data.Dataset.from_tensor_slices(string_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs). If
shuffle=False, omit the
.shuffle(...). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:276: input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by
tf.data. Use
tf.data.Dataset.from_tensor_slices(input_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs). If
shuffle=False, omit the
.shuffle(...). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:188: limit_epochs (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by
tf.data. Use
tf.data.Dataset.from_tensors(tensor).repeat(num_epochs). WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:197: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the
tf.datamodule. WARNING:tensorflow:From D:\python\lib\site-packages\tensorflow\python\training\input.py:197: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version. Instructions for updating: To construct input pipelines, use the
tf.datamodule. WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:130: TFRecordReader.__init__ (from tensorflow.python.ops.io_ops) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by
tf.data. Use
tf.data.TFRecordDataset. Tensor("ReaderNumRecordsProducedV2:0", shape=(), dtype=int64) Tensor("ReaderNumWorkUnitsCompletedV2:0", shape=(), dtype=int64) WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:154: shuffle_batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by
tf.data. Use
tf.data.Dataset.shuffle(min_after_dequeue).batch(batch_size)`.Tensor("ReaderNumRecordsProducedV2_1:0", shape=(), dtype=int64)
Tensor("ReaderNumWorkUnitsCompletedV2_1:0", shape=(), dtype=int64)
training data prepared, data processing duration: 0:00:00.557883
last shape: [None, 50, 13, 256]
WARNING:tensorflow:From D:\python\kws\KeywordSpotting-master\train_tfrecord.py:192: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the
tf.data
module.Done reading
Traceback (most recent call last):
File "D:\python\kws\KeywordSpotting-master\train_tfrecord.py", line 264, in
train_accuracies, validation_accuracies, x_range, loss_epoch, loss_epoch_val, save_path = train()
File "D:\python\kws\KeywordSpotting-master\train_tfrecord.py", line 258, in train
coord.join(threads)
File "D:\python\lib\site-packages\tensorflow\python\training\coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "D:\python\lib\site-packages\six.py", line 693, in reraise
raise value
File "D:\python\lib\site-packages\tensorflow\python\training\queue_runner_impl.py", line 257, in _run
enqueue_callable()
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1257, in _single_operation_run
self._call_tf_sessionrun(None, {}, [], target_list, None)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Key: source. Can't parse serialized Example.
[[{{node ParseSingleExample/ParseSingleExample}} = ParseSingleExample[Tdense=[DT_FLOAT, DT_FLOAT], dense_keys=["source", "target"], dense_shapes=[[650], [2]], num_sparse=0, sparse_keys=[], sparse_types=[], _device="/job:localhost/replica:0/task:0/device:CPU:0"](ReaderReadV2:1, ParseSingleExample/Const, ParseSingleExample/Const)]]`
The text was updated successfully, but these errors were encountered: