GraphDef cannot be larger than 2GB.

[pranavi77]

TensorFlow Version: 1.3.0
INFO:tensorflow:Restoring parameters from b'C:/Users/uidk4301/Desktop/fcn8s_tensorflow-master/VGG-16_mod2FCN_ImageNet-Classification/variables\variables'

---

ValueError Traceback (most recent call last)
in ()
3 vgg16_dir='C:/Users/uidk4301/Desktop/fcn8s_tensorflow-master/VGG-16_mod2FCN_ImageNet-Classification/',
4 num_classes=num_classes,
----> 5 variables_load_dir=None)

C:\Users\uidk4301\Desktop\fcn8s_tensorflow-master\fcn8s_tensorflow.py in init(self, model_load_dir, tags, vgg16_dir, num_classes, variables_load_dir)
104
105 # Load the pretrained convolutionalized VGG-16 model as our encoder.
--> 106 self.image_input, self.keep_prob, self.pool3_out, self.pool4_out, self.fc7_out = self._load_vgg16()
107 # Build the decoder on top of the VGG-16 encoder.
108 self.fcn8s_output, self.l2_regularization_rate = self._build_decoder()

C:\Users\uidk4301\Desktop\fcn8s_tensorflow-master\fcn8s_tensorflow.py in _load_vgg16(self)
132 # 1: Load the model
133
--> 134 tf.saved_model.loader.load(sess=self.sess, tags=[self.vgg16_tag], export_dir=self.vgg16_dir)
135
136 # 2: Return the tensors of interest

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\saved_model\loader_impl.py in load(sess, tags, export_dir, **saver_kwargs)
224
225 # Restore the variables using the built saver in the provided session.
--> 226 saver.restore(sess, variables_path)
227 else:
228 tf_logging.info("The specified SavedModel has no variables; no "

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py in restore(self, sess, save_path)
1558 logging.info("Restoring parameters from %s", save_path)
1559 sess.run(self.saver_def.restore_op_name,
-> 1560 {self.saver_def.filename_tensor_name: save_path})
1561
1562 @staticmethod

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
893 try:
894 result = self._run(None, fetches, feed_dict, options_ptr,
--> 895 run_metadata_ptr)
896 if run_metadata:
897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1122 if final_fetches or final_targets or (handle and feed_dict_tensor):
1123 results = self._do_run(handle, final_targets, final_fetches,
-> 1124 feed_dict_tensor, options, run_metadata)
1125 else:
1126 results = []

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1319 if handle is None:
1320 return self._do_call(_run_fn, self._session, feeds, fetches, targets,
-> 1321 options, run_metadata)
1322 else:
1323 return self._do_call(_prun_fn, self._session, handle, feeds, fetches)

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1325 def _do_call(self, fn, *args):
1326 try:
-> 1327 return fn(*args)
1328 except errors.OpError as e:
1329 message = compat.as_text(e.message)

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1295 run_metadata):
1296 # Ensure any changes to the graph are reflected in the runtime.
-> 1297 self._extend_graph()
1298 with errors.raise_exception_on_not_ok_status() as status:
1299 if self._created_with_new_api:

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in _extend_graph(self)
1351 graph_def, self._current_version = self._graph._as_graph_def(
1352 from_version=self._current_version,
-> 1353 add_shapes=self._add_shapes)
1354 # pylint: enable=protected-access
1355

C:\Users\uidk4301\AppData\Local\Continuum\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in _as_graph_def(self, from_version, add_shapes)
2444 bytesize += op.node_def.ByteSize()
2445 if bytesize >= (1 << 31) or bytesize < 0:
-> 2446 raise ValueError("GraphDef cannot be larger than 2GB.")
2447 if self._functions:
2448 for f in self._functions.values():

ValueError: GraphDef cannot be larger than 2GB.

I am getting this while loading model