Tensorflow custom estimator: 'Series' objects are mutable, thus they cannot be hashed

Trying to create a custom classifier in Tensorflow like so

def my_model_fn(
features, # This is batch_features from input_fn
labels, # This is batch_labels from input_fn
mode, # An instance of tf.estimator.ModeKeys
params # Additional configuration
):

input_layer = tf.feature_column.input_layer(features,
feature_columns=params['feature_columns'])

(...)


where params['feature_columns'] is defined as below, and is of type _NumericColumn

params['feature_columns']

_NumericColumn

feature_columns = [
tf.feature_column.numeric_column(training_examples['x'])
]

params={'feature_columns': feature_columns, 'n_outputs': 1}


When I try and construct the model, however,

#construct model
model = tf.estimator.Estimator(
model_fn=my_model_fn,
model_dir='tensor_custom',
params=params
)


I receive the following error

TypeError: 'Series' objects are mutable, thus they cannot be hashed


Which I don't understand; the docs suggest that I should be able to pass a _NumericColumn to the feature_columns argument?

_NumericColumn

feature_columns

I suppose I'm missing something conceptually, but not sure what it is. Any help would be appreciated!

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