Я использую модель API Keras, чтобы применить 1D-свертку к входному 1d-вектору размера 20. Мне нужно пять ядер размером 3 каждое. Вход будет иметь форму (None, 1,20) (переменное число 1D векторов размером 20).
input = Input(shape=(1, 20))
conv = Conv1D(filters=5, kernel_size=3, activation=keras.activations.relu, input_shape=(None,20, 1))(input)
dense =dense(1)(conv)
model = Model(inputs=input, outputs=dense)
model.compile(loss=nn.customLoss, optimizer='adam')
history = model.fit(train_X, train_labels, batch_size=50,
epochs=15, validation_split=0.2)
Сводка модели -
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) (None, None, 20) 0
_________________________________________________________________
conv1d_1 (Conv1D) (None, None, 5) 305
_________________________________________________________________
dense_1 (Dense) (None, None, 1) 6
=================================================================
Total params: 311
Trainable params: 311
Non-trainable params: 0
train_x имеет форму (None, 1, 20), train_labels имеет форму (None, 1).
Ошибка происходит из слоя свертки -
Caused by op 'conv1d_1/convolution/Conv2D', defined at:
File "/home/user/Desktop/hack/imlhack2018/conv_nn.py", line 72, in <module>
main()
File "/home/user/Desktop/hack/imlhack2018/conv_nn.py", line 42, in main
conv = Conv1D(filters=5, kernel_size=3, activation=keras.activations.relu, input_shape=(None,20, 1))(input)
File "/home/user/anaconda3/lib/python3.6/site-packages/keras/engine/topology.py", line 596, in __call__
output = self.call(inputs, **kwargs)
File "/home/user/anaconda3/lib/python3.6/site-packages/keras/layers/convolutional.py", line 156, in call
dilation_rate=self.dilation_rate[0])
File "/home/user/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 3116, in conv1d
data_format=tf_data_format)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 670, in convolution
op=op)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 338, in with_space_to_batch
return op(input, num_spatial_dims, padding)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 662, in op
name=name)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 116, in _non_atrous_convolution
name=scope)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 2010, in conv1d
data_format=data_format)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 399, in conv2d
data_format=data_format, name=name)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/user/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1269, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): computed output size would be negative
[[Node: conv1d_1/convolution/Conv2D = Conv2D[T=DT_FLOAT, data_format="NHWC", padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/cpu:0"](conv1d_1/convolution/ExpandDims, conv1d_1/convolution/ExpandDims_1)]]
Когда я добавляю padding="same" к сверточному слою, кажется, что все работает нормально. В чем причина такого поведения?