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docs: start updating docs to reflect the rewrite

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Umut
2022-04-04 13:36:19 +02:00
parent f17745130e
commit 79685ed7dc
14 changed files with 137 additions and 219 deletions
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docs/user/tutorial/indexing.md
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@@ -9,16 +9,15 @@ Here are some examples of constant indexing:
### Extracting a single element
```python
import concrete.numpy as hnp
import concrete.numpy as cnp
import numpy as np
@cnp.compiler({"x": "encrypted"})
def f(x):
return x[1]
inputset = [np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8) for _ in range(10)]
compiler = hnp.NPFHECompiler(f, {"x": "encrypted"})
circuit = compiler.compile_on_inputset(inputset)
circuit = f.compile(inputset)
test_input = np.array([4, 2, 6], dtype=np.uint8)
expected_output = 2
@@ -29,16 +28,15 @@ assert np.array_equal(circuit.encrypt_run_decrypt(test_input), expected_output)
You can use negative indexing.
```python
import concrete.numpy as hnp
import concrete.numpy as cnp
import numpy as np
@cnp.compiler({"x": "encrypted"})
def f(x):
return x[-1]
inputset = [np.random.randint(0, 2 ** 3, size=(3,), dtype=np.uint8) for _ in range(10)]
compiler = hnp.NPFHECompiler(f, {"x": "encrypted"})
circuit = compiler.compile_on_inputset(inputset)
circuit = f.compile(inputset)
test_input = np.array([4, 2, 6], dtype=np.uint8)
expected_output = 6
@@ -49,16 +47,15 @@ assert np.array_equal(circuit.encrypt_run_decrypt(test_input), expected_output)
You can use multidimensional indexing as well.
```python
import concrete.numpy as hnp
import concrete.numpy as cnp
import numpy as np
@cnp.compiler({"x": "encrypted"})
def f(x):
return x[-1, 1]
inputset = [np.random.randint(0, 2 ** 3, size=(3, 2), dtype=np.uint8) for _ in range(10)]
compiler = hnp.NPFHECompiler(f, {"x": "encrypted"})
circuit = compiler.compile_on_inputset(inputset)
circuit = f.compile(inputset)
test_input = np.array([[4, 2], [1, 5], [7, 6]], dtype=np.uint8)
expected_output = 6
@@ -69,16 +66,15 @@ assert np.array_equal(circuit.encrypt_run_decrypt(test_input), expected_output)
### Extracting a slice
```python
import concrete.numpy as hnp
import concrete.numpy as cnp
import numpy as np
@cnp.compiler({"x": "encrypted"})
def f(x):
return x[1:4]
inputset = [np.random.randint(0, 2 ** 3, size=(5,), dtype=np.uint8) for _ in range(10)]
compiler = hnp.NPFHECompiler(f, {"x": "encrypted"})
circuit = compiler.compile_on_inputset(inputset)
circuit = f.compile(inputset)
test_input = np.array([4, 2, 6, 1, 7], dtype=np.uint8)
expected_output = np.array([2, 6, 1], dtype=np.uint8)