齒輪Conv1D的負尺寸

Question

我正在使用Keras的模型api將1D卷積應用於大小為20的輸入1d向量。我想要每個大小為3的五個內核。 輸入將具有(None, 1,20)形狀(None, 1,20)大小為20的可變數量的1D向量）。

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)

該模型的摘要是-

_________________________________________________________________
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的形狀為(None, 1, 20) train_labels (None, 1, 20) ， train_labels的形狀為(None, 1) 。

錯誤來自卷積層-

    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)]]

當我在卷積層中添加padding="same" ，一切似乎都工作正常。 這種行為的原因是什么？

Answer 1

您的輸入形狀為（1，20），它被解釋為1寬度，20通道的數組。 您可能想要相反的選擇，即寬度20和1通道。 由於數組只有一個元素，因此在不使用SAME填充的情況下執行卷積將導致負數維，從而產生錯誤。

請注意，卷積始終在空間維度上執行，對於Conv1D，該維度是形狀數組中倒數第二個維度。 最后一個維度代表渠道。

Answer 2

在官方文檔中，它寫道：“當將此層用作模型的第一層時，請提供input_shape參數（整數元組或None，不包括批處理軸）”。 我很困惑，為什么它在輸入層中聲明了conv1D的輸入形狀之后