TorchModuleWrapper in documentation

[emi-dm]

Where is TorchModuleWrapper in documentation?

it would be nice to add a few examples of use.

[sachinprasadhs]

Hi,

You can find the example usage of TorchModuleWrapper in the below section.

keras/keras/utils/torch_utils.py

Lines 28 to 77 in d7268f3

	Here's an example of how the `TorchModuleWrapper` can be used with vanilla
	PyTorch modules.
	```python
	import torch.nn as nn
	import torch.nn.functional as F
	import keras
	from keras.layers import TorchModuleWrapper
	class Classifier(keras.Model):
	def __init__(self, **kwargs):
	super().__init__(**kwargs)
	# Wrap `torch.nn.Module`s with `TorchModuleWrapper`
	# if they contain parameters
	self.conv1 = TorchModuleWrapper(
	nn.Conv2d(in_channels=1, out_channels=32, kernel_size=(3, 3))
	)
	self.conv2 = TorchModuleWrapper(
	nn.Conv2d(in_channels=32, out_channels=64, kernel_size=(3, 3))
	)
	self.pool = nn.MaxPool2d(kernel_size=(2, 2))
	self.flatten = nn.Flatten()
	self.dropout = nn.Dropout(p=0.5)
	self.fc = TorchModuleWrapper(nn.Linear(1600, 10))
	def call(self, inputs):
	x = F.relu(self.conv1(inputs))
	x = self.pool(x)
	x = F.relu(self.conv2(x))
	x = self.pool(x)
	x = self.flatten(x)
	x = self.dropout(x)
	x = self.fc(x)
	return F.softmax(x, dim=1)
	model = Classifier()
	model.build((1, 28, 28))
	print("Output shape:", model(torch.ones(1, 1, 28, 28).to("cuda")).shape)
	model.compile(
	loss="sparse_categorical_crossentropy",
	optimizer="adam",
	metrics=["accuracy"]
	)
	model.fit(train_loader, epochs=5)
	```
	"""

[fchollet]

Sure, we'll add it to the docs as part of a new layer category.