[英]Variable sized input doesn't work with dilated convolutional layer
我有一个非常简单的模型，它在文本输入（嵌入）上运行一些卷积层，这些文本输入（嵌入）具有由批处理填充的可变大小。 我想添加一些扩张层，但我遇到了问题。
运行以下代码时，我可以在第一次运行时输入任何维度，但将相同的卷积层应用于另一个输入时会出错。
bs = 5
text_len_1 = 772
text_len_2 = 741
embed_size = 300
in_channels = 1
test_in_1 = tf.random.normal((bs, text_len_1, embed_size, in_channels))
test_in_2 = tf.random.normal((bs, text_len_2, embed_size, in_channels))
dilated_convs = [tf.keras.layers.Conv2D(filters=10, kernel_size=(2, embed_size),
dilation_rate=(dilation, 1),
padding='valid')
for dilation in range(2, 23)]
for conv in dilated_convs:
res = conv(test_in_1)
for conv in dilated_convs:
# Fails here, regardless of test_in_1 or 2 is called first
res = conv(test_in_2)
起初我以为我只需要正确填充输入，但我似乎无法找到应该如何完成的任何模式，所以为了正确填充输入可能需要一个简单的计算，但它看起来像还有其他事情发生，因为只要是第一个输入，我就可以使用任何输入进行调用。
编辑：添加错误和堆栈跟踪
2019-06-25 13:50:33.329503: W tensorflow/core/framework/op_kernel.cc:1546] OP_REQUIRES failed at spacetobatch_op.cc:219 : Invalid argument: padded_shape[0]=741 is not divisible by block_shape[0]=2
Traceback (most recent call last):
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3296, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-59b677f0b758>", line 1, in <module>
runfile('/home/name/.PyCharm2019.1/config/scratches/dilated_conv_test.py', wdir='/home/name/.PyCharm2019.1/config/scratches')
File "/snap/pycharm-professional/136/helpers/pydev/_pydev_bundle/pydev_umd.py", line 197, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "/snap/pycharm-professional/136/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/name/.PyCharm2019.1/config/scratches/dilated_conv_test.py", line 22, in <module>
res = conv(test_in_2)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 712, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/keras/layers/convolutional.py", line 196, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 1078, in __call__
return self.conv_op(inp, filter)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 634, in __call__
return self.call(inp, filter)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 617, in _with_space_to_batch_call
input=inp, block_shape=dilation_rate, paddings=paddings)
File "/home/name/anaconda3/envs/3.6/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 9246, in space_to_batch_nd
_six.raise_from(_core._status_to_exception(e.code, message), None)
File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: padded_shape[0]=741 is not divisible by block_shape[0]=2 [Op:SpaceToBatchND]
我运行了您的代码，错误在 tensorflow 1.x 版中仍然存在，但在升级到 tensorflow 2.x 版时消失。 能否请您升级到 2.x 版本并尝试。
以下是运行详情。
运行 1 - Tensorflow 版本 1.x
%tensorflow_version 1.x
import tensorflow as tf
bs = 5
text_len_1 = 772
text_len_2 = 741
embed_size = 300
in_channels = 1
test_in_1 = tf.random.normal((bs, text_len_1, embed_size, in_channels))
test_in_2 = tf.random.normal((bs, text_len_2, embed_size, in_channels))
dilated_convs = [tf.keras.layers.Conv2D(filters=10, kernel_size=(2, embed_size),
dilation_rate=(dilation, 1),
padding='same')
for dilation in range(2, 23)]
print(dilated_convs)
for conv in dilated_convs:
res = conv(test_in_1)
for conv in dilated_convs:
# Fails here, regardless of test_in_1 or 2 is called first
res = conv(test_in_2)
print("I ran Succesfully")
输出 -
TensorFlow 1.x selected.
[<tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe3db797160>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa30e48>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa542b0>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa546d8>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa54b00>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa54f28>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa58390>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa587b8>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa58be0>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa5f048>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa5f470>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa5f898>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa5fcc0>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa62128>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa62550>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa62978>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39fa62da0>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39f9e8208>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39f9e8630>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39f9e8a58>, <tensorflow.python.keras.layers.convolutional.Conv2D object at 0x7fe39f9e8e80>]
WARNING:tensorflow:From /tensorflow-1.15.2/python3.6/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1606 try:
-> 1607 c_op = c_api.TF_FinishOperation(op_desc)
1608 except errors.InvalidArgumentError as e:
InvalidArgumentError: Dimension size must be evenly divisible by 2 but is 743 for 'conv2d_21/SpaceToBatchND' (op: 'SpaceToBatchND') with input shapes: [5,741,300,1], [2], [2,2] and with computed input tensors: input[1] = <2 1>, input[2] = <[1 1][149 150]>.
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
12 frames
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1608 except errors.InvalidArgumentError as e:
1609 # Convert to ValueError for backwards compatibility.
-> 1610 raise ValueError(str(e))
1611
1612 return c_op
ValueError: Dimension size must be evenly divisible by 2 but is 743 for 'conv2d_21/SpaceToBatchND' (op: 'SpaceToBatchND') with input shapes: [5,741,300,1], [2], [2,2] and with computed input tensors: input[1] = <2 1>, input[2] = <[1 1][149 150]>.
运行 2 - Tensorflow 版本 2.x
%tensorflow_version 2.x
import tensorflow as tf
bs = 5
text_len_1 = 772
text_len_2 = 741
embed_size = 300
in_channels = 1
test_in_1 = tf.random.normal((bs, text_len_1, embed_size, in_channels))
test_in_2 = tf.random.normal((bs, text_len_2, embed_size, in_channels))
dilated_convs = [tf.keras.layers.Conv2D(filters=10, kernel_size=(2, embed_size),
dilation_rate=(dilation, 1),
padding='same')
for dilation in range(2, 23)]
for conv in dilated_convs:
res = conv(test_in_1)
for conv in dilated_convs:
# Fails here, regardless of test_in_1 or 2 is called first
res = conv(test_in_2)
print("I ran Succesfully")
输出 -
I ran Succesfully
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