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chore: prepare release 1.4.1
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fd0r committed Feb 12, 2024
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1 change: 0 additions & 1 deletion README.md
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Expand Up @@ -193,7 +193,6 @@ To cite Concrete ML, notably in academic papers, please use the following entry,
<img src="https://github.com/zama-ai/concrete-ml/assets/157474013/8ef18a7e-671b-495c-8346-fa75227d0af3">
</a>


## License.

This software is distributed under the BSD-3-Clause-Clear license. If you have any questions, please contact us at [email protected].
2 changes: 1 addition & 1 deletion docs/conf.py
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Expand Up @@ -27,7 +27,7 @@
root_url = root_url if root_url.endswith("/") else root_url + "/"

# The full version, including alpha/beta/rc tags
release = "1.4.0"
release = "1.4.1"


# -- General configuration ---------------------------------------------------
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52 changes: 26 additions & 26 deletions docs/developer-guide/api/concrete.ml.onnx.ops_impl.md
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Expand Up @@ -1333,10 +1333,12 @@ ______________________________________________________________________
```python
numpy_avgpool(
x: ndarray,
ceil_mode: int,
kernel_shape: Tuple[int, ],
pads: Tuple[int, ] = None,
strides: Tuple[int, ] = None
auto_pad: str = 'NOTSET',
ceil_mode: int = 0,
count_include_pad: int = 1,
pads: Optional[Tuple[int, ]] = None,
strides: Optional[Tuple[int, ]] = None
) → Tuple[ndarray]
```

Expand All @@ -1348,24 +1350,22 @@ See: https://github.com/onnx/onnx/blob/main/docs/Operators.md#AveragePool

**Args:**

- <b>`x`</b> (numpy.ndarray): input data (many dtypes are supported). Shape is N x C x H x W for 2d
- <b>`ceil_mode`</b> (int): ONNX rounding parameter, expected 0 (torch style dimension computation)
- <b>`kernel_shape`</b> (Tuple\[int, ...\]): shape of the kernel. Should have 2 elements for 2d conv
- <b>`pads`</b> (Tuple\[int, ...\]): padding in ONNX format (begin, end) on each axis
- <b>`strides`</b> (Tuple\[int, ...\]): stride of the convolution on each axis
- <b>`x`</b> (numpy.ndarray): Input data of shape (N, C, H, W), as only 2D inputs are currently supported.
- <b>`kernel_shape`</b> (Tuple\[int, ...\]): The size of the kernel along each axis. Currently, only 2D kernels are supported.
- <b>`auto_pad`</b> (str): Only the default "NOTSET" value is currently supported, which means explicit padding is used.
- <b>`ceil_mode`</b> (int): Whether to use ONNX's ceil (1) or floor (0, the default) to compute the output shape.
- <b>`count_include_pad`</b> (int): Whether include pad pixels when calculating values for the edges. Currently, setting this parameter to 0 is not supported in Concrete ML.
- <b>`pads`</b> (Tuple\[int, ...\]): Padding for the beginning and ending along each spatial axis. Expected format is \[x1_begin, x2_begin...x1_end, x2_end, ...\] where xi_begin (resp. xi_end) is the number of pixels added at the beginning (resp. end) of axis `i`.
- <b>`strides`</b> (Tuple\[int, ...\]): Stride along each spatial axis. If not present, the stride defaults to 1 along each spatial axis.

**Returns:**

- <b>`res`</b> (numpy.ndarray): a tensor of size (N x InChannels x OutHeight x OutWidth).
- <b>`See https`</b>: //pytorch.org/docs/stable/generated/torch.nn.AvgPool2d.html

**Raises:**

- <b>`AssertionError`</b>: if the pooling arguments are wrong

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1376"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1404"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_maxpool`

Expand Down Expand Up @@ -1406,7 +1406,7 @@ See: https://github.com/onnx/onnx/blob/main/docs/Operators.md#MaxPool

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1479"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1507"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_cast`

Expand All @@ -1431,7 +1431,7 @@ See: https://github.com/onnx/onnx/blob/main/docs/Operators.md#Cast

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1504"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1532"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_batchnorm`

Expand Down Expand Up @@ -1473,7 +1473,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#BatchNormalization-

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1575"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1603"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_flatten`

Expand All @@ -1496,7 +1496,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Flatten-13.

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1593"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1621"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_or`

Expand All @@ -1519,7 +1519,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Or-7

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1611"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1639"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_or_float`

Expand All @@ -1542,7 +1542,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Or-7

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1629"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1657"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_round`

Expand All @@ -1564,7 +1564,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Round-11 Remark tha

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1646"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1674"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_pow`

Expand All @@ -1587,7 +1587,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Pow-13

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1772"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1800"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_floor`

Expand All @@ -1609,7 +1609,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Floor-1

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1786"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1814"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_max`

Expand All @@ -1634,7 +1634,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Max-1

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1803"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1831"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_min`

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______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1820"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1848"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_sign`

Expand All @@ -1681,7 +1681,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sign-9

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1834"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1862"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_neg`

Expand All @@ -1703,7 +1703,7 @@ See https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Sign-9

______________________________________________________________________

<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1848"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
<a href="../../../src/concrete/ml/onnx/ops_impl.py#L1876"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>

## <kbd>function</kbd> `numpy_concatenate`

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