See documentation for input_from_feature_columns. The following types of
FeatureColumn are permitted in feature_columns: _OneHotColumn,
_EmbeddingColumn, _ScatteredEmbeddingColumn, _RealValuedColumn,
_DataFrameColumn. In addition, columns in feature_columns may not be
constructed using any of the following: ScatteredEmbeddingColumn,
BucketizedColumn, CrossedColumn.
Args
columns_to_tensors
A mapping from feature column to tensors. 'string' key
means a base feature (not-transformed). It can have FeatureColumn as a
key too. That means that FeatureColumn is already transformed by input
pipeline.
feature_columns
A set containing all the feature columns. All items in the
set should be instances of classes derived by FeatureColumn.
weight_collections
List of graph collections to which weights are added.
trainable
If True also add variables to the graph collection
GraphKeys.TRAINABLE_VARIABLES (see tf.Variable).
scope
Optional scope for variable_scope.
Returns
A Tensor which can be consumed by hidden layers in the neural network.
Raises
ValueError
if FeatureColumn cannot be consumed by a neural network.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.layers.sequence_input_from_feature_columns\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/layers/python/layers/feature_column_ops.py#L224-L267) |\n\nBuilds inputs for sequence models from `FeatureColumn`s. (experimental) \n\n tf.contrib.layers.sequence_input_from_feature_columns(\n columns_to_tensors, feature_columns, weight_collections=None, trainable=True,\n scope=None\n )\n\n| **Warning:** THIS FUNCTION IS EXPERIMENTAL. It may change or be removed at any time, and without warning.\n\nSee documentation for `input_from_feature_columns`. The following types of\n`FeatureColumn` are permitted in `feature_columns`: `_OneHotColumn`,\n`_EmbeddingColumn`, `_ScatteredEmbeddingColumn`, `_RealValuedColumn`,\n`_DataFrameColumn`. In addition, columns in `feature_columns` may not be\nconstructed using any of the following: `ScatteredEmbeddingColumn`,\n`BucketizedColumn`, `CrossedColumn`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `columns_to_tensors` | A mapping from feature column to tensors. 'string' key means a base feature (not-transformed). It can have FeatureColumn as a key too. That means that FeatureColumn is already transformed by input pipeline. |\n| `feature_columns` | A set containing all the feature columns. All items in the set should be instances of classes derived by FeatureColumn. |\n| `weight_collections` | List of graph collections to which weights are added. |\n| `trainable` | If `True` also add variables to the graph collection `GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable). |\n| `scope` | Optional scope for variable_scope. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A Tensor which can be consumed by hidden layers in the neural network. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|----------------------------------------------------------|\n| `ValueError` | if FeatureColumn cannot be consumed by a neural network. |\n\n\u003cbr /\u003e"]]
View source on GitHub