tf.estimator.inputs.pandas_input_fn
Returns input function that would feed Pandas DataFrame into the model.
tf.estimator.inputs.pandas_input_fn(
x, y=None, batch_size=128, num_epochs=1, shuffle=None, queue_capacity=1000,
num_threads=1, target_column='target'
)
Note: y's index must match x's index.
| Args |
|---|
x | pandas DataFrame object. |
y | pandas Series object or DataFrame. None if absent. |
batch_size | int, size of batches to return. |
num_epochs | int, number of epochs to iterate over data. If not None, read attempts that would exceed this value will raise OutOfRangeError. |
shuffle | bool, whether to read the records in random order. |
queue_capacity | int, size of the read queue. If None, it will be set roughly to the size of x. |
num_threads | Integer, number of threads used for reading and enqueueing. In order to have predicted and repeatable order of reading and enqueueing, such as in prediction and evaluation mode, num_threads should be 1. |
target_column | str, name to give the target column y. This parameter is not used when y is a DataFrame. |
| Returns |
|---|
Function, that has signature of ()->(dict of features, target) |
| Raises |
|---|
ValueError | if x already contains a column with the same name as y, or if the indexes of x and y don't match. |
ValueError | if 'shuffle' is not provided or a bool. |