TensorFlow can not add training data through placeholder - python-3.x

Question

Good day to all. Studying TF. Made an example with adding data through placeholder and it does not work. As I understand it, fetch_batch creates batchy just as a string and cannot feed them through feed_dict. But why and how to fix do not understand. I would be very grateful for the help.
import tensorflow as tf
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.preprocessing import StandardScaler
housing = fetch_california_housing()
m, n = housing.data.shape
learning_rate = 0.1
n_epochs = 1000
scaler = StandardScaler()
scaled_housing_data = scaler.fit_transform(housing.data)
scaled_housing_data_plus_bias = np.c_[np.ones((m, 1)), scaled_housing_data]
#X = tf.constant(scaled_housing_data_plus_bias, dtype=tf.float32, name="X")
#y = tf.constant(housing.target.reshape(-1, 1), dtype=tf.float32, name="y")
X = tf.placeholder(tf.float32, shape=(None, n+1), name="X")
y = tf.placeholder(tf.float32, shape=(None, 1), name="y")
def fetch_batch (batch_index, batch_size, epoch):
np.random.seed (epoch * batch_size + batch_size)
indices = np.random.randint (m, size=batch_size)
X_batch = scaled_housing_data_plus_bias [indices]
y_batch = housing.target.reshape(-1, 1) [indices]
return X_batch, y_batch
batch_size = 100
theta = tf.Variable(tf.random_uniform([n + 1, 1], -1.0, 1.0, seed=42), name="theta")
y_pred = tf.matmul(X, theta, name="prediction")
erorr = y_pred - y
mse = tf.reduce_mean(tf.square(erorr), name="mse")
#gradients = 2/m * tf.matmul(tf.transpose(X), erorr, name="gradients")
#training_op = tf.assign(theta, theta - learning_rate * gradients)
optimizer = tf.train.GradientDescentOptimizer (learning_rate=learning_rate)
training_op = optimizer.minimize(mse)
n_batches = int(np.ceil(m / batch_size))
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
for epoch in range(n_epochs):
for batch_index in range(n_batches):
X_batch, y_batch = fetch_batch (batch_index, batch_size, epoch)
sess.run(training_op, feed_dict={X:X_batch, y:y_batch})
if epoch % 100 == 0 :
print("Epoch:", epoch, "MSE:", mse.eval())
but in the end I get an error
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1333 try:
-> 1334 return fn(*args)
1335 except errors.OpError as e:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1318 return self._call_tf_sessionrun(
-> 1319 options, feed_dict, fetch_list, target_list, run_metadata)
1320
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1406 self._session, options, feed_dict, fetch_list, target_list,
-> 1407 run_metadata)
1408
InvalidArgumentError: You must feed a value for placeholder tensor 'X_11' with dtype float and shape [?,9]
[[{{node X_11}} = Placeholder[dtype=DT_FLOAT, shape=[?,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[{{node mse_12/_7}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_15_mse_12", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-19-46a547b04ceb> in <module>()
56 sess.run(training_op, feed_dict={X:X_batch, y:y_batch})
57 if epoch % 100 == 0 :
---> 58 print("Epoch:", epoch, "MSE:", mse.eval())
59
60
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in eval(self, feed_dict, session)
711
712 """
--> 713 return _eval_using_default_session(self, feed_dict, self.graph, session)
714
715
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _eval_using_default_session(tensors, feed_dict, graph, session)
5155 "the tensor's graph is different from the session's "
5156 "graph.")
-> 5157 return session.run(tensors, feed_dict)
5158
5159
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
927 try:
928 result = self._run(None, fetches, feed_dict, options_ptr,
--> 929 run_metadata_ptr)
930 if run_metadata:
931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1150 if final_fetches or final_targets or (handle and feed_dict_tensor):
1151 results = self._do_run(handle, final_targets, final_fetches,
-> 1152 feed_dict_tensor, options, run_metadata)
1153 else:
1154 results = []
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1326 if handle is None:
1327 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328 run_metadata)
1329 else:
1330 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1346 pass
1347 message = error_interpolation.interpolate(message, self._graph)
-> 1348 raise type(e)(node_def, op, message)
1349
1350 def _extend_graph(self):
InvalidArgumentError: You must feed a value for placeholder tensor 'X_11' with dtype float and shape [?,9]
[[node X_11 (defined at <ipython-input-19-46a547b04ceb>:23) = Placeholder[dtype=DT_FLOAT, shape=[?,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[{{node mse_12/_7}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_15_mse_12", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'X_11', defined at:
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.6/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python3.6/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-19-46a547b04ceb>", line 23, in <module>
X = tf.placeholder(tf.float32, shape=(None, n+1), name="X")
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/array_ops.py", line 1747, in placeholder
return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 5206, in placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'X_11' with dtype float and shape [?,9]
[[node X_11 (defined at <ipython-input-19-46a547b04ceb>:23) = Placeholder[dtype=DT_FLOAT, shape=[?,9], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[{{node mse_12/_7}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_15_mse_12", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Answer 1

print("MSE=%s" % sess.run(mse, feed_dict={X:X_train, y:y_train}))
or
_, mse_value = sess.run([training_op, mse], feed_dict={X:X_train, y:y_train})
print("MSE=%s" % mse_value)