LittleHann
commented
7 years ago tha whole error is
root@ubuntu:~/eXposeDeepNeuralNetwork/src# python model_server.py ../data/models/urls/
Using TensorFlow backend.
Loading models
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your InputLayer call to the Keras 2 API: InputLayer(dtype="int32", batch_input_shape=[None, 100..., name="main_input")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: The dropout argument is no longer support in Embedding. You can apply a keras.layers.SpatialDropout1D layer right after the Embedding layer to get the same behavior.
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Embedding call to the Keras 2 API: Embedding(embeddings_initializer="uniform", trainable=True, name="embedding_1", output_dim=32, activity_regularizer=None, embeddings_regularizer=None, input_dtype="int32", embeddings_constraint=None, mask_zero=False, input_dim=100, batch_input_shape=[None, 100..., input_length=100)
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Conv1D call to the Keras 2 API: Conv1D(trainable=True, filters=256, use_bias=True, bias_regularizer=None, input_dtype="float32", activation="relu", kernel_initializer="uniform", kernel_constraint=None, activity_regularizer=None, input_shape=(None, Non..., padding="same", strides=1, batch_input_shape=[None, 100..., name="convolution1d_1", bias_constraint=None, kernel_regularizer=None, kernel_size=2)
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_1")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Conv1D call to the Keras 2 API: Conv1D(trainable=True, filters=256, use_bias=True, bias_regularizer=None, input_dtype="float32", activation="relu", kernel_initializer="uniform", kernel_constraint=None, activity_regularizer=None, input_shape=(None, Non..., padding="same", strides=1, batch_input_shape=[None, 100..., name="convolution1d_2", bias_constraint=None, kernel_regularizer=None, kernel_size=3)
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_2")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Conv1D call to the Keras 2 API: Conv1D(trainable=True, filters=256, use_bias=True, bias_regularizer=None, input_dtype="float32", activation="relu", kernel_initializer="uniform", kernel_constraint=None, activity_regularizer=None, input_shape=(None, Non..., padding="same", strides=1, batch_input_shape=[None, 100..., name="convolution1d_3", bias_constraint=None, kernel_regularizer=None, kernel_size=4)
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_3")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Conv1D call to the Keras 2 API: Conv1D(trainable=True, filters=256, use_bias=True, bias_regularizer=None, input_dtype="float32", activation="relu", kernel_initializer="uniform", kernel_constraint=None, activity_regularizer=None, input_shape=(None, Non..., padding="same", strides=1, batch_input_shape=[None, 100..., name="convolution1d_4", bias_constraint=None, kernel_regularizer=None, kernel_size=5)
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_4")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: The Merge layer is deprecated and will be removed after 08/2017. Use instead layers from keras.layers.merge, e.g. add, concatenate, etc.
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dense call to the Keras 2 API: Dense(name="dense_1", bias_regularizer=None, bias_constraint=None, activity_regularizer=None, trainable=True, kernel_constraint=None, kernel_regularizer=None, input_dim=None, units=1024, kernel_initializer="glorot_uniform", use_bias=True, activation="relu")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_5")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dense call to the Keras 2 API: Dense(name="dense_2", bias_regularizer=None, bias_constraint=None, activity_regularizer=None, trainable=True, kernel_constraint=None, kernel_regularizer=None, input_dim=None, units=1024, kernel_initializer="glorot_uniform", use_bias=True, activation="relu")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dropout call to the Keras 2 API: Dropout(rate=0.5, trainable=True, name="dropout_6")
return cls(config)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py:1231: UserWarning: Update your Dense call to the Keras 2 API: Dense(name="dense_3", bias_regularizer=None, bias_constraint=None, activity_regularizer=None, trainable=True, kernel_constraint=None, kernel_regularizer=None, input_dim=None, units=1, kernel_initializer="glorot_uniform", use_bias=True, activation="sigmoid")
return cls(**config)
Traceback (most recent call last):
File "model_server.py", line 28, in
zsavvas
I run the code from github python model_server.py ../data/models/urls/ and get:
Traceback (most recent call last): File "model_server.py", line 28, in
'model_weights.h5',
File "/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py", line 2538, in load_weights
load_weights_from_hdf5_group(f, self.layers)
File "/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py", line 2970, in load_weights_from_hdf5_group
K.batch_set_value(weight_value_tuples)
File "/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.py", line 2148, in batch_set_value
assign_op = x.assign(assign_placeholder)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 551, in assign
return state_ops.assign(self._variable, value, use_locking=use_locking)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_state_ops.py", line 47, in assign
use_locking=use_locking, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2397, in create_op
set_shapes_for_outputs(ret)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1757, in set_shapes_for_outputs
shapes = shape_func(op)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1707, in call_with_requiring
return call_cpp_shape_fn(op, require_shape_fn=True)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/common_shapes.py", line 610, in call_cpp_shape_fn
debug_python_shape_fn, require_shape_fn)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/common_shapes.py", line 675, in _call_cpp_shape_fn_impl
raise ValueError(err.message)
ValueError: Shapes must be equal rank, but are 3 and 4 for 'Assign_1' (op: 'Assign') with input shapes: [2,32,256], [256,32,2,1].
anybody known what happend?