tf.feature_column.sequence_numeric_column
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Returns a feature column that represents sequences of numeric data. (deprecated)
tf . feature_column . sequence_numeric_column (
key ,
shape = ( 1 ,),
default_value = 0.0 ,
dtype = tf . dtypes . float32
,
normalizer_fn = None
)
Deprecated: THIS FUNCTION IS DEPRECATED. It will be removed in a future version.
Instructions for updating:
Use Keras preprocessing layers instead, either directly or via the tf.keras.utils.FeatureSpace
utility. Each of tf.feature_column.*
has a functional equivalent in tf.keras.layers
for feature preprocessing when training a Keras model.
Example:
temperature = sequence_numeric_column ( 'temperature ')
columns = [ temperature ]
features = tf . io . parse_example ( ... , features = make_parse_example_spec ( columns ))
sequence_feature_layer = SequenceFeatures ( columns )
sequence_input , sequence_length = sequence_feature_layer ( features )
sequence_length_mask = tf . sequence_mask ( sequence_length )
rnn_cell = tf . keras . layers . SimpleRNNCell ( hidden_size )
rnn_layer = tf . keras . layers . RNN ( rnn_cell )
outputs , state = rnn_layer ( sequence_input , mask = sequence_length_mask )
Args
key
A unique string identifying the input features.
shape
The shape of the input data per sequence id. E.g. if shape=(2,)
,
each example must contain 2 * sequence_length
values.
default_value
A single value compatible with dtype
that is used for
padding the sparse data into a dense Tensor
.
dtype
The type of values.
normalizer_fn
If not None
, a function that can be used to normalize the
value of the tensor after default_value
is applied for parsing.
Normalizer function takes the input Tensor
as its argument, and returns
the output Tensor
. (e.g. lambda x: (x - 3.0) / 4.2). Please note that
even though the most common use case of this function is normalization, it
can be used for any kind of Tensorflow transformations.
Returns
A SequenceNumericColumn
.
Raises
TypeError
if any dimension in shape is not an int.
ValueError
if any dimension in shape is not a positive integer.
ValueError
if dtype
is not convertible to tf.float32
.
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Last updated 2023-10-06 UTC.
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