Getting AttributeError while training DNN classifer - string

Question

Here is the code:
continous=['age', 'education_num', 'capital_gain', 'capital_loss', 'hours_per_week']
creating feat_cols
I have automated the process using for loop
feat_cols = []
for col in census.columns:
## Continous - Unchanged
if col in continous:
feat_cols.append(tf.feature_column.numeric_column(col))
## Categorical - Trick, no need to count
elif col!='income_bracket':
print('Embedded {}'.format(col))
feat_cols.append(tf.feature_column.embedding_column(categorical_column=col,dimension=X_train[col].nunique()))
Creating model
Importing Tensorflow I've created this model.
dnnmodel = tf.estimator.DNNClassifier(hidden_units=[7,7,7], feature_columns=feat_cols, n_classes=2)
ip_dnn = tf.estimator.inputs.pandas_input_fn(X_train, y_train, num_epochs=None,shuffle=True)
dnnmodel.train(input_fn=ip_dnn, steps=5000)
Error:
Earlier with LinearClassifier everything worked fine.
INFO:tensorflow:Calling model_fn.
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-67-751f0a94d0d2> in <module>()
1 # ip_func created earliar
2
----> 3 dnnmodel.train(input_fn=ip_dnn, steps=5000)
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py in train(self, input_fn, hooks, steps, max_steps, saving_listeners)
356
357 saving_listeners = _check_listeners_type(saving_listeners)
--> 358 loss = self._train_model(input_fn, hooks, saving_listeners)
359 logging.info('Loss for final step: %s.', loss)
360 return self
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py in _train_model(self, input_fn, hooks, saving_listeners)
1122 return self._train_model_distributed(input_fn, hooks, saving_listeners)
1123 else:
-> 1124 return self._train_model_default(input_fn, hooks, saving_listeners)
1125
1126 def _train_model_default(self, input_fn, hooks, saving_listeners):
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py in _train_model_default(self, input_fn, hooks, saving_listeners)
1152 worker_hooks.extend(input_hooks)
1153 estimator_spec = self._call_model_fn(
-> 1154 features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
1155 global_step_tensor = training_util.get_global_step(g)
1156 return self._train_with_estimator_spec(estimator_spec, worker_hooks,
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py in _call_model_fn(self, features, labels, mode, config)
1110
1111 logging.info('Calling model_fn.')
-> 1112 model_fn_results = self._model_fn(features=features, **kwargs)
1113 logging.info('Done calling model_fn.')
1114
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py in _model_fn(features, labels, mode, config)
520 input_layer_partitioner=input_layer_partitioner,
521 config=config,
--> 522 batch_norm=batch_norm)
523
524 super(DNNClassifier, self).__init__(
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py in _dnn_model_fn(features, labels, mode, head, hidden_units, feature_columns, optimizer, activation_fn, dropout, input_layer_partitioner, config, use_tpu, batch_norm)
285 input_layer_partitioner=input_layer_partitioner,
286 batch_norm=batch_norm)
--> 287 logits = logit_fn(features=features, mode=mode)
288
289 if use_tpu:
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py in dnn_logit_fn(features, mode)
101 batch_norm,
102 name='dnn')
--> 103 return dnn_model(features, mode)
104
105 return dnn_logit_fn
~\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in __call__(self, inputs, *args, **kwargs)
552 # In graph mode, failure to build the layer's graph
553 # implies a user-side bug. We don't catch exceptions.
--> 554 outputs = self.call(inputs, *args, **kwargs)
555 else:
556 try:
~\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py in call(self, features, mode)
193 'input_from_feature_columns',
194 partitioner=self._input_layer_partitioner):
--> 195 net = self._input_layer(features)
196 for i in range(len(self._hidden_layers)):
197 net = self._hidden_layers[i](net)
~\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py in __call__(self, features)
335 trainable=self._trainable,
336 cols_to_vars=None,
--> 337 from_template=True)
338
339 #property
~\Anaconda3\lib\site-packages\tensorflow\python\ops\template.py in __call__(self, *args, **kwargs)
366 custom_getter=self._custom_getter) as vs:
367 self._variable_scope = vs
--> 368 return self._call_func(args, kwargs)
369
370 #property
~\Anaconda3\lib\site-packages\tensorflow\python\ops\template.py in _call_func(self, args, kwargs)
309 # Checkpointable).
310 with checkpointable_util.capture_dependencies(template=self):
--> 311 result = self._func(*args, **kwargs)
312
313 if self._variables_created:
~\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py in _internal_input_layer(features, feature_columns, weight_collections, trainable, cols_to_vars, scope, cols_to_output_tensors, from_template)
179 """See input_layer. `scope` is a name or variable scope to use."""
180
--> 181 feature_columns = _normalize_feature_columns(feature_columns)
182 for column in feature_columns:
183 if not isinstance(column, _DenseColumn):
~\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py in _normalize_feature_columns(feature_columns)
2266 name_to_column = dict()
2267 for column in feature_columns:
-> 2268 if column.name in name_to_column:
2269 raise ValueError('Duplicate feature column name found for columns: {} '
2270 'and {}. This usually means that these columns refer to '
~\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column_v2.py in name(self)
2960 def name(self):
2961 """See `FeatureColumn` base class."""
-> 2962 return '{}_embedding'.format(self.categorical_column.name)
2963
2964 #property
**AttributeError: 'str' object has no attribute 'name'**
originally defined at:
File "C:\Users\Subham\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py", line 102, in dnn_logit_fn
name='dnn')
File "C:\Users\Subham\Anaconda3\lib\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py", line 134, in __init__
create_scope_now=False)
File "C:\Users\Subham\Anaconda3\lib\site-packages\tensorflow\python\feature_column\feature_column.py", line 327, in __init__
self._name, _internal_input_layer, create_scope_now_=create_scope_now)
File "C:\Users\Subham\Anaconda3\lib\site-packages\tensorflow\python\ops\template.py", line 154, in make_template
**kwargs)