Hi,

I was trying to rewrite vgg16.py from scratch but instead building vgg19 instead. I actually wanted to build a different model from scratch to see if it really affects accuracy. I went through the code for vgg19 and vgg16 from the keras repo. I saw that the difference lies in the extra convolution blocks in vgg19.

And also, the pre-trained weights for both of them differ. I’m pasting the part where my code for vgg16 and vgg19 differ here.

```
self.ConvBlock(2, 64)
self.ConvBlock(2, 128)
self.ConvBlock(4, 256)
self.ConvBlock(4, 512)
self.ConvBlock(4, 512)
```

And, I’m loading the pre-trained weights this way:

```
TH_WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_th_dim_ordering_th_kernels.h5'
TH_WEIGHTS_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_th_dim_ordering_th_kernels_notop.h5'
.....
def create(self,size,include_top):
.....
if not include_top:
fname = 'vgg19_weights_th_dim_ordering_th_kernels_notop.h5'
model.load_weights(get_file(fname, TH_WEIGHTS_PATH_NO_TOP, cache_subdir='models'))
return
model.add(Flatten())
self.FCBlock()
self.FCBlock()
model.add(Dense(1000, activation='softmax'))
fname = 'vgg19_weights_th_dim_ordering_th_kernels.h5'
model.load_weights(get_file(fname, TH_WEIGHTS_PATH, cache_subdir='models'))
```

I’m getting the following error when i try to instantiate vgg19 in my redux.ipynb file.

```
ValueError: You are trying to load a weight file containing 18 layers into a model with 21 layers.
```

The exact line of error pointed out is.

```
89 self.FCBlock()
90 model.add(Dense(1000, activation='softmax'))
---> 91
92 fname = 'vgg19_weights_th_dim_ordering_th_kernels.h5'
93 model.load_weights(get_file(fname, TH_WEIGHTS_PATH, cache_subdir='models'))
```

I double-checked the path for my weights and they seem correct. Please do let me know what I’m doing wrong here.

Thanks!

Karthik