Cast string to float is not supported - python-3.x

Question

I am working on a tensorflow course and am trying to apply what I am learning to my own data. I am getting a "Cast string to float is not supported". Using the pandas dataframe INFO(), I confirm that all columns that are OBJECTS I have turned to a feature column using categorical_column_with_hash_bucket, all INT64 or FLOAT64 I have used numeric_column. Why is this error popping up?
Here is my code and error:
import tensorflow as tf
import pandas as pd
from sklearn.model_selection import train_test_split
tree_data_file = r'\\David\f\first_test_feature_cols_v2.csv'
tree_data = pd.read_csv(tree_data_file)
### Create feature columns for continuous data
b3_sum = tf.feature_column.numeric_column('b3_sum')
im3b3_s = tf.feature_column.numeric_column('im3b3_s')
imred = tf.feature_column.numeric_column('imred')
# Create feature columns for categorical data
sp1 = tf.feature_column.categorical_column_with_hash_bucket('sp1',hash_bucket_size=10)
sp2 = tf.feature_column.categorical_column_with_hash_bucket('sp2',hash_bucket_size=10)
feat_cols = [b3_sum,im3b3_s,im_red,sp1,sp2]
#TRAIN TEST SPLIT
x_data = tree_data.drop('sp_call', axis=1)
labels = tree_data['sp_call']
X_train, X_test, Y_train, Y_test = train_test_split(x_data, labels, test_size = 0.3)
input_func = tf.estimator.inputs.pandas_input_fn(x = X_train, y=Y_train, batch_size=10, num_epochs=1000, shuffle=True)
model = tf.estimator.LinearClassifier(feature_columns=feat_cols, n_classes=2)
model.train(input_fn=input_func, steps=1000)
Caused by op 'linear/head/ToFloat', defined at:
File "<string>", line 1, in <module>
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\idlelib\run.py", line 144, in main
ret = method(*args, **kwargs)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\idlelib\run.py", line 474, in runcode
exec(code, self.locals)
File "C:\Users\david\Documents\Neural_Network\test_neural_network_v1.py", line 59, in <module>
model.train(input_fn=input_func, steps=1000)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py", line 354, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1207, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1237, in _train_model_default
features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py", line 1195, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\canned\linear.py", line 384, in _model_fn
sparse_combiner=sparse_combiner)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\canned\linear.py", line 215, in _linear_model_fn
logits=logits)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\canned\head.py", line 239, in create_estimator_spec
regularization_losses))
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\canned\head.py", line 1209, in _create_tpu_estimator_spec
features=features, mode=mode, logits=logits, labels=labels))
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\canned\head.py", line 1115, in create_loss
labels = math_ops.to_float(labels)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\math_ops.py", line 732, in to_float
return cast(x, dtypes.float32, name=name)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\math_ops.py", line 677, in cast
x = gen_math_ops.cast(x, base_type, name=name)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1754, in cast
"Cast", x=x, DstT=DstT, Truncate=Truncate, name=name)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 3274, in create_op
op_def=op_def)
File "C:\Users\david\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
UnimplementedError (see above for traceback): Cast string to float is not supported
[[node linear/head/ToFloat (defined at C:\Users\david\Documents\Neural_Network\test_neural_network_v1.py:59) = Cast[DstT=DT_FLOAT, SrcT=DT_STRING, Truncate=false, _class=["loc:#linea...t/Switch_1"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/head/labels/_781)]]