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docs(frontend-python): Simplify and unify README and quick start example

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Bourgerie Quentin
2024-02-15 10:51:53 +01:00
parent 0ef3e0cfba
commit aadae42e0c
2 changed files with 49 additions and 41 deletions
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35
README.md
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@@ -90,40 +90,21 @@ def add(x, y):
return x + y
compiler = fhe.Compiler(add, {"x": "encrypted", "y": "encrypted"})
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1), (3, 2), (6, 1), (1, 7), (4, 5), (5, 4)]
print(f"Compiling...")
print(f"Compilation...")
circuit = compiler.compile(inputset)
print(f"Generating keys...")
print(f"Key generation...")
circuit.keygen()
examples = [(3, 4), (1, 2), (7, 7), (0, 0)]
for example in examples:
encrypted_example = circuit.encrypt(*example)
encrypted_result = circuit.run(encrypted_example)
result = circuit.decrypt(encrypted_result)
print(f"Evaluation of {' + '.join(map(str, example))} homomorphically = {result}")
```
print(f"Homomorphic evaluation...")
encrypted_x, encrypted_y = circuit.encrypt(2, 6)
encrypted_result = circuit.run(encrypted_x, encrypted_y)
result = circuit.decrypt(encrypted_result)
Or if you have a simple function that you can decorate, and you don't care about explicit steps of key generation, encryption, evaluation and decryption:
```python
from concrete import fhe
@fhe.compiler({"x": "encrypted", "y": "encrypted"})
def add(x, y):
return x + y
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1), (3, 2), (6, 1), (1, 7), (4, 5), (5, 4)]
print(f"Compiling...")
circuit = add.compile(inputset)
examples = [(3, 4), (1, 2), (7, 7), (0, 0)]
for example in examples:
result = circuit.encrypt_run_decrypt(*example)
print(f"Evaluation of {' + '.join(map(str, example))} homomorphically = {result}")
assert result == add(2, 6)
```
*This example is explained in more detail [in this part of the documentation](https://docs.zama.ai/concrete/getting-started/quick_start).*

55
docs/get-started/quick_start.md
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@@ -10,18 +10,22 @@ from concrete import fhe
def add(x, y):
return x + y
compiler = fhe.Compiler(add, {"x": "encrypted", "y": "clear"})
compiler = fhe.Compiler(add, {"x": "encrypted", "y": "encrypted"})
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1)]
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1), (3, 2), (6, 1), (1, 7), (4, 5), (5, 4)]
print(f"Compilation...")
circuit = compiler.compile(inputset)
x = 4
y = 4
print(f"Key generation...")
circuit.keygen()
clear_evaluation = add(x, y)
homomorphic_evaluation = circuit.encrypt_run_decrypt(x, y)
print(f"Homomorphic evaluation...")
encrypted_x, encrypted_y = circuit.encrypt(2, 6)
encrypted_result = circuit.run(encrypted_x, encrypted_y)
result = circuit.decrypt(encrypted_result)
print(x, "+", y, "=", clear_evaluation, "=", homomorphic_evaluation)
assert result == add(2, 6)
```
## Importing the library
@@ -47,6 +51,13 @@ def add(x, y):
To compile the function, you need to create a `Compiler` by specifying the function to compile and the encryption status of its inputs:
<!--pytest-codeblocks:skip-->
```python
compiler = fhe.Compiler(add, {"x": "encrypted", "y": "encrypted"})
```
To set that e.g. `y` is in the clear, it would be
<!--pytest-codeblocks:skip-->
```python
compiler = fhe.Compiler(add, {"x": "encrypted", "y": "clear"})
@@ -60,11 +71,13 @@ It should be in iterable, yielding tuples, of the same length as the number of a
<!--pytest-codeblocks:skip-->
```python
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1)]
inputset = [(2, 3), (0, 0), (1, 6), (7, 7), (7, 1), (3, 2), (6, 1), (1, 7), (4, 5), (5, 4)]
```
Here, our inputset is made of 10 pairs of integers, whose the minimum pair is `(0, 0)` and the maximum is `(7, 7)`.
{% hint style="warning" %}
All inputs in the inputset will be evaluated in the graph, which takes time. If you're experiencing long compilation times, consider providing a smaller inputset.
Choosing a representative inputset is critical to allow the compiler to find accurate bounds of all the intermediate values (find more details [here](https://docs.zama.ai/concrete/explanations/compilation#bounds-measurement). Later if you evaluate the circuit with values that make under or overflows it results to an undefined behavior.
{% endhint %}
{% hint style="warning" %}
@@ -74,22 +87,36 @@ There is a utility function called `fhe.inputset(...)` for easily creating rando
## Compiling the function
You can use the `compile` method of a `Compiler` class with an inputset to perform the compilation and get the resulting circuit back:
You can use the `compile` method of the `Compiler` class with an inputset to perform the compilation and get the resulting circuit back:
<!--pytest-codeblocks:skip-->
```python
print(f"Compilation...")
circuit = compiler.compile(inputset)
```
## Performing homomorphic evaluation
## Generating the keys
You can use the `encrypt_run_decrypt` method of a `Circuit` class to perform homomorphic evaluation:
You can use the `keygen` method of the `Circuit` class to generate the keys (public and private):
<!--pytest-codeblocks:skip-->
```python
homomorphic_evaluation = circuit.encrypt_run_decrypt(4, 4)
print(f"Key generation...")
circuit.keygen()
```
{% hint style="info" %}
`circuit.encrypt_run_decrypt(*args)` is just a convenient way to do everything at once. It is implemented as `circuit.decrypt(circuit.run(circuit.encrypt(*args)))`.
If you don't call the key generation explicitly keys will be generated lazily when it needed.
{% endhint %}
## Performing homomorphic evaluation
Now you can easily perform the homomorphic evaluation using the `encrypt`, `run` and `decrypt` methods of the `Circuit`:
<!--pytest-codeblocks:skip-->
```python
print(f"Homomorphic evaluation...")
encrypted_x, encrypted_y = circuit.encrypt(2, 6)
encrypted_result = circuit.run(encrypted_x, encrypted_y)
result = circuit.decrypt(encrypted_result)
```