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docs(frontend): add documentation for fhe modules
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aPere3 authored and BourgerieQuentin committed Apr 4, 2024
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1 change: 1 addition & 0 deletions docs/SUMMARY.md
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* [Reuse arguments](compilation/reuse_arguments.md)
* [Multi precision](compilation/multi_precision.md)
* [Multi parameters](compilation/multi_parameters.md)
* [Modules](compilation/modules.md)
* [Decorator](compilation/decorator.md)
* [Direct circuits](compilation/direct_circuits.md)

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51 changes: 51 additions & 0 deletions docs/compilation/modules.md
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# Modules

{% hint style="warning" %}
Modules are still experimental. They are only compatible with [composition](../compilation/composition.md), which means the outputs of every functions can be used directly as inputs for other functions. The crypto-parameters used in this mode are large and thus, the execution is likely to slow.
{% endhint %}

In some cases, deploying a server that can execute different functions is useful. *Concrete* can compile FHE _modules_, that can contain many different functions to execute at once. All the functions are compiled in a single step and can be [deployed with the same artifacts](../guides/deploy.md#deployment-of-modules). Here is an example:

```python
from concrete import fhe

@fhe.module()
class MyModule:
@fhe.function({"x": "encrypted"})
def inc(x):
return x + 1 % 20

@fhe.function({"x": "encrypted"})
def dec(x):
return x - 1 % 20
```

You can compile the FHE module `MyModule` using the `compile` method. To do that, you need to provide a dictionnary of input sets for every function:

```python
inputset = list(range(20))
my_module = MyModule.compile({"inc": inputset, "dec": inputset})
```

{% hint style="warning" %}
Note that here we can see a current limitation of modules: The configuration must use the `parameter_selection_strategy` of `v0`, and activate the `composable` flag.
{% endhint %}

After the module has been compiled, we can encrypt and call the different functions in the following way:

```python
x = 5
x_enc = my_module.inc.encrypt(x)
x_inc_enc = my_module.inc.run(x_enc)
x_inc = my_module.inc.decrypt(x_inc_enc)
assert x_inc == 6

x_inc_dec_enc = my_module.dec.run(x_inc_enc)
x_inc_dec = my_module.dec.decrypt(x_inc_dec_enc)
assert x_inc_dec == 5

for _ in range(10):
x_enc = my_module.inc.run(x_enc)
x_dec = my_module.inc.decrypt(x_enc)
assert x_dec == 15
```
55 changes: 55 additions & 0 deletions docs/guides/deploy.md
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decrypted_result = client.decrypt(deserialized_result)
assert decrypted_result == 49
```

# Deployment of modules

Deploying a [module](../compilation/modules.md#modules) follows the same logic as the deployment of circuits. Assuming a module compiled in the following way:

<!--pytest-codeblocks:skip-->
```python
from concrete import fhe

@fhe.module()
class MyModule:
@fhe.function({"x": "encrypted"})
def inc(x):
return x + 1

@fhe.function({"x": "encrypted"})
def dec(x):
return x - 1

inputset = list(range(20))
my_module = MyModule.compile({"inc": inputset, "dec": inputset})
)
```

You can extract the server from the module and save it in a file:

<!--pytest-codeblocks:skip-->
```python
my_module.server.save("server.zip")
```

The only noticeable difference between the deployment of modules and the deployment of circuits is that the methods `Client::encrypt`, `Client::decrypt` and `Server::run` must contain an extra `function_name` argument specifying the name of the targeted function.

The encryption of an argument for the `inc` function of the module would be:

<!--pytest-codeblocks:skip-->
```python
arg = client.encrypt(7, function_name="inc")
serialized_arg = arg.serialize()
```

The execution of the `inc` function would be :

<!--pytest-codeblocks:skip-->
```python
result = server.run(deserialized_arg, evaluation_keys=deserialized_evaluation_keys, function_name="inc")
serialized_result = result.serialize()
```

Finally, decrypting a result from the execution of `dec` would be:

<!--pytest-codeblocks:skip-->
```python
decrypted_result = client.decrypt(deserialized_result, function_name="dec")
```

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