Python TensorFlow:卷积网络中的维数不相容误差

我假设权重变量

weights['wc1']

的形状不正确，但我不确定正确的形状是什么。

问题是，您的输入图像（在

\u X

中）有3个通道（可能是红色、绿色和蓝色），而层

conv1

的卷积滤波器（在

\u weights['wc1']

中）需要1个输入通道

对于如何解决此问题，至少有两种可能性：

重新定义权重['wc1']以接受3个输入通道：

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
Traceback (most recent call last):
  File "/home/anilil/projects/pycharm-community-5.0.4/helpers/pydev/pydevd.py", line 2411, in <module>
    globals = debugger.run(setup['file'], None, None, is_module)
  File "/home/anilil/projects/pycharm-community-5.0.4/helpers/pydev/pydevd.py", line 1802, in run
    launch(file, globals, locals)  # execute the script
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 104, in <module>
    pred = vgg_single_frame(x, weights, biases, keep_prob)
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 50, in vgg_single_frame
    conv1 = conv2d('conv1', _X, _weights['wc1'], _biases['bc1'],s=2)
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 38, in conv2d
    return tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(l_input, w, strides=[1, s, s, 1], padding='SAME'),b), name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 211, in conv2d
    use_cudnn_on_gpu=use_cudnn_on_gpu, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 655, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2042, in create_op
    set_shapes_for_outputs(ret)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1528, in set_shapes_for_outputs
    shapes = shape_func(op)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/common_shapes.py", line 187, in conv2d_shape
    input_shape[3].assert_is_compatible_with(filter_shape[2])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 94, in assert_is_compatible_with
    % (self, other))
ValueError: Dimensions Dimension(3) and Dimension(1) are not compatible

使用

tf.image.rgb\u to_grayscale（）

op:

weights = {
    'wc1': tf.Variable(tf.random_normal([7, 7, 3, 96])), # ...
    # ...
}

---

问题是您的输入图像（在

\ux

中）有3个通道（可能是红色、绿色和蓝色），而层

conv1

的卷积滤波器（在

\u权重['wc1']

中）需要1个输入通道

对于如何解决此问题，至少有两种可能性：

重新定义权重['wc1']以接受3个输入通道：

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
Traceback (most recent call last):
  File "/home/anilil/projects/pycharm-community-5.0.4/helpers/pydev/pydevd.py", line 2411, in <module>
    globals = debugger.run(setup['file'], None, None, is_module)
  File "/home/anilil/projects/pycharm-community-5.0.4/helpers/pydev/pydevd.py", line 1802, in run
    launch(file, globals, locals)  # execute the script
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 104, in <module>
    pred = vgg_single_frame(x, weights, biases, keep_prob)
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 50, in vgg_single_frame
    conv1 = conv2d('conv1', _X, _weights['wc1'], _biases['bc1'],s=2)
  File "/media/anilil/Data/charm/Cnn/build_vgg_model.py", line 38, in conv2d
    return tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(l_input, w, strides=[1, s, s, 1], padding='SAME'),b), name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 211, in conv2d
    use_cudnn_on_gpu=use_cudnn_on_gpu, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 655, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2042, in create_op
    set_shapes_for_outputs(ret)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1528, in set_shapes_for_outputs
    shapes = shape_func(op)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/common_shapes.py", line 187, in conv2d_shape
    input_shape[3].assert_is_compatible_with(filter_shape[2])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 94, in assert_is_compatible_with
    % (self, other))
ValueError: Dimensions Dimension(3) and Dimension(1) are not compatible

使用

tf.image.rgb\u to_grayscale（）

op:

weights = {
    'wc1': tf.Variable(tf.random_normal([7, 7, 3, 96])), # ...
    # ...
}