我目前正在尝试为交互式神经网络实验创建一个简单的Web应用程序。我对Tensorflow和机器学习一般都很陌生，所以我想从S＆amp; P500的简单时间序列回归开始。
我遇到的问题是出现以下错误：
InvalidArgumentError (see above for traceback): Incompatible shapes: [32,1] vs. [1248,1]
如果批处理大小为32且实际数据大小为1248.它在会话运行时由以下代码行生成：
tMSE = tf.reduce_mean(tf.square(y_hat - train_y))
这是源代码
def retrieve_data():
"""Retrieves the data - to be expanded for custom database access + S3 retrieval + URL"""
result = pd.read_csv('snp_data.csv', parse_dates=['Date'], index_col=['Date'])
return result
def get_features(data, columns):
features = data.ix[:, columns]
return features
def preprocess(data):
"""Data preprocessing"""
result = (data - data.mean()) / data.std(ddof=0)
result = result.fillna(0)
return result
def init_weights(shape):
""" Weights initialization """
weights = tf.random_normal(shape=shape, stddev=0.1)
return tf.Variable(weights)
def forwardprop(X, w_1, w_2):
"""Forward propagation"""
h = tf.nn.relu(tf.matmul(X, w_1))
y_hat = tf.matmul(h, w_2)
return y_hat
@app.route('/train')
def train():
data = retrieve_data()
train_x = get_features(data, columns=['Open', 'Close'])
train_x = preprocess(data=train_x).as_matrix().astype(np.float32)
train_x = train_x[:(len(train_x) - (len(train_x) % 32))]
train_y = get_features(data, columns=['Adj Close']).as_matrix().astype(np.float32)
train_y = train_y[:(len(train_y) - (len(train_y) % 32))]
# Number of input nodes
n_features = train_x.shape[1]
# Number of output nodes
output_nodes = train_y.shape[1]
# Number of hidden nodes
hidden_nodes = 20
# TF Placeholders for the inputs and outputs
tx = tf.placeholder(tf.float32, shape=(None, n_features))
ty = tf.placeholder(tf.float32, shape=(None, output_nodes))
# Weight initializations
tW1 = init_weights(shape=(n_features, hidden_nodes))
tW2 = init_weights(shape=(hidden_nodes, output_nodes))
# Forward propagation
y_hat = forwardprop(tx, tW1, tW2)
# Backward Propagation
tMSE = tf.reduce_mean(tf.square(y_hat - train_y))
learning_rate = 0.025
tOptimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
tOptimize = tOptimizer.minimize(tMSE)
batch_size = 32
n_epochs = 8
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
for i_e in range(n_epochs):
for i in range(0, train_x.shape[0], batch_size):
batch_X = train_x[i:i + batch_size, ...]
batch_y = train_y[i:i + batch_size]
_, loss = sess.run([tOptimize, tMSE], feed_dict={tx: batch_X, ty: batch_y})
print(i, loss)
return 'Flask Dockerized'
这是记录的错误：
Traceback (most recent call last):
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1997, in __call__
return self.wsgi_app(environ, start_response)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1985, in wsgi_app
response = self.handle_exception(e)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1540, in handle_exception
reraise(exc_type, exc_value, tb)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1982, in wsgi_app
response = self.full_dispatch_request()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1614, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1517, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1612, in full_dispatch_request
rv = self.dispatch_request()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1598, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "/{PROJECT_PATH}/web/app.py", line 85, in train
_, loss = sess.run([tOptimize, tMSE], feed_dict={tx: batch_X, ty: batch_y})
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
options, run_metadata)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
InvalidArgumentError: Incompatible shapes: [32,1] vs. [1248,1]
[[Node: sub = Sub[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](MatMul_1, sub/y)]]
Caused by op u'sub', defined at:
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/threading.py", line 783, in __bootstrap
self.__bootstrap_inner()
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/threading.py", line 810, in __bootstrap_inner
self.run()
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/threading.py", line 763, in run
self.__target(*self.__args, **self.__kwargs)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 702, in inner
srv.serve_forever()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 539, in serve_forever
HTTPServer.serve_forever(self)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/SocketServer.py", line 238, in serve_forever
self._handle_request_noblock()
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/SocketServer.py", line 295, in _handle_request_noblock
self.process_request(request, client_address)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/SocketServer.py", line 321, in process_request
self.finish_request(request, client_address)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/SocketServer.py", line 334, in finish_request
self.RequestHandlerClass(request, client_address, self)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/SocketServer.py", line 655, in __init__
self.handle()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 232, in handle
rv = BaseHTTPRequestHandler.handle(self)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/BaseHTTPServer.py", line 340, in handle
self.handle_one_request()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 267, in handle_one_request
return self.run_wsgi()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 209, in run_wsgi
execute(self.server.app)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/serving.py", line 199, in execute
for data in application_iter:
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/werkzeug/debug/__init__.py", line 284, in debug_application
app_iter = self.app(environ, start_response)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1997, in __call__
return self.wsgi_app(environ, start_response)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1982, in wsgi_app
response = self.full_dispatch_request()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1612, in full_dispatch_request
rv = self.dispatch_request()
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/flask/app.py", line 1598, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "/{PROJECT_PATH}/web/app.py", line 68, in train
tMSE = tf.reduce_mean(tf.square(y_hat - train_y))
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 865, in binary_op_wrapper
return func(x, y, name=name)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 2629, in _sub
result = _op_def_lib.apply_op("Sub", x=x, y=y, name=name)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/{PROJECT_PATH}/venv/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1204, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): Incompatible shapes: [32,1] vs. [1248,1]
[[Node: sub = Sub[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](MatMul_1, sub/y)]]
答案 0 :(得分：2)
您应该更改您的tMSE代码：
# original wrong code: tMSE = tf.reduce_mean(tf.square(y_hat - train_y))
tMSE = tf.reduce_mean(tf.square(y_hat - ty))