concrete.ml.quantization.quantized_ops.md

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module `concrete.ml.quantization.quantized_ops`

Quantized versions of the ONNX operators for post training quantization.

class `QuantizedSigmoid`

Quantized sigmoid op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedHardSigmoid`

Quantized HardSigmoid op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedRelu`

Quantized Relu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedPRelu`

Quantized PRelu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedLeakyRelu`

Quantized LeakyRelu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedHardSwish`

Quantized Hardswish op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedElu`

Quantized Elu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedSelu`

Quantized Selu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedCelu`

Quantized Celu op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedClip`

Quantized clip op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedRound`

Quantized round op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedPow`

Quantized pow op.

Only works for a float constant power. This operation will be fused to a (potentially larger) TLU.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedGemm`

Quantized Gemm op.

method `init`

__init__(
    n_bits_output: int,
    int_input_names: Set[str] = None,
    constant_inputs: Optional[Dict[str, Any], Dict[int, Any]] = None,
    input_quant_opts: QuantizationOptions = None,
    **attrs
) → None

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

class `QuantizedMatMul`

Quantized MatMul op.

method `init`

__init__(
    n_bits_output: int,
    int_input_names: Set[str] = None,
    constant_inputs: Optional[Dict[str, Any], Dict[int, Any]] = None,
    input_quant_opts: QuantizationOptions = None,
    **attrs
) → None

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

class `QuantizedAdd`

Quantized Addition operator.

Can add either two variables (both encrypted) or a variable and a constant

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `can_fuse`

can_fuse() → bool

Determine if this op can be fused.

Add operation can be computed in float and fused if it operates over inputs produced by a single integer tensor. For example the expression x + x * 1.75, where x is an encrypted tensor, can be computed with a single TLU.

Returns:

bool: Whether the number of integer input tensors allows computing this op as a TLU

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

class `QuantizedTanh`

Quantized Tanh op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedSoftplus`

Quantized Softplus op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedExp`

Quantized Exp op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedLog`

Quantized Log op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedAbs`

Quantized Abs op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

class `QuantizedIdentity`

Quantized Identity op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

class `QuantizedReshape`

Quantized Reshape op.

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

Reshape the input integer encrypted tensor.

Args:

q_inputs: an encrypted integer tensor at index 0 and one constant shape at index 1
attrs: additional optional reshape options

Returns:

result (QuantizedArray): reshaped encrypted integer tensor

class `QuantizedConv`

Quantized Conv op.

method `init`

__init__(
    n_bits_output: int,
    int_input_names: Set[str] = None,
    constant_inputs: Optional[Dict[str, Any], Dict[int, Any]] = None,
    input_quant_opts: QuantizationOptions = None,
    **attrs
) → None

Construct the quantized convolution operator and retrieve parameters.

Args:

n_bits_output: number of bits for the quantization of the outputs of this operator
int_input_names: names of integer tensors that are taken as input for this operation
constant_inputs: the weights and activations
input_quant_opts: options for the input quantizer
attrs: convolution options
dilations (Tuple[int]): dilation of the kernel. Default to 1 on all dimensions.
group (int): number of convolution groups. Default to 1.
kernel_shape (Tuple[int]): shape of the kernel. Should have 2 elements for 2d conv
pads (Tuple[int]): padding in ONNX format (begin, end) on each axis
strides (Tuple[int]): stride of the convolution on each axis

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

Compute the quantized convolution between two quantized tensors.

Allows an optional quantized bias.

Args:

q_inputs: input tuple, contains
x (numpy.ndarray): input data. Shape is N x C x H x W for 2d
w (numpy.ndarray): weights tensor. Shape is (O x I x Kh x Kw) for 2d
b (numpy.ndarray, Optional): bias tensor, Shape is (O,)
attrs: convolution options handled in constructor

Returns:

res (QuantizedArray): result of the quantized integer convolution

class `QuantizedAvgPool`

Quantized Average Pooling op.

method `init`

__init__(
    n_bits_output: int,
    int_input_names: Set[str] = None,
    constant_inputs: Optional[Dict[str, Any], Dict[int, Any]] = None,
    input_quant_opts: QuantizationOptions = None,
    **attrs
) → None

property int_input_names

Get the names of encrypted integer tensors that are used by this op.

Returns:

List[str]: the names of the tensors

method `q_impl`

q_impl(*q_inputs: QuantizedArray, **attrs) → QuantizedArray

class `QuantizedMaxPool`

Quantized Max Pooling op.

method `init`

__init__(
    n_bits_output: int,
    int_input_names: Set[str] = None,
    constant_inputs: Optional[Dict[str, Any], Dict[int, Any]] = None,

module concrete.ml.quantization.quantized_ops

class QuantizedSigmoid

class QuantizedHardSigmoid

class QuantizedRelu

class QuantizedPRelu

class QuantizedLeakyRelu

class QuantizedHardSwish

class QuantizedElu

class QuantizedSelu

class QuantizedCelu

class QuantizedClip

class QuantizedRound

class QuantizedPow

class QuantizedGemm

method __init__

method q_impl

class QuantizedMatMul

method __init__

method q_impl

class QuantizedAdd

method can_fuse

method q_impl

class QuantizedTanh

class QuantizedSoftplus

class QuantizedExp

class QuantizedLog

class QuantizedAbs

class QuantizedIdentity

method q_impl

class QuantizedReshape

method q_impl

class QuantizedConv

method __init__

method q_impl

class QuantizedAvgPool

method __init__

method q_impl

class QuantizedMaxPool

method __init__

module `concrete.ml.quantization.quantized_ops`

class `QuantizedSigmoid`

class `QuantizedHardSigmoid`

class `QuantizedRelu`

class `QuantizedPRelu`

class `QuantizedLeakyRelu`

class `QuantizedHardSwish`

class `QuantizedElu`

class `QuantizedSelu`

class `QuantizedCelu`

class `QuantizedClip`

class `QuantizedRound`

class `QuantizedPow`

class `QuantizedGemm`

method `init`

method `q_impl`

class `QuantizedMatMul`

method `init`

method `q_impl`

class `QuantizedAdd`

method `can_fuse`

method `q_impl`

class `QuantizedTanh`

class `QuantizedSoftplus`

class `QuantizedExp`

class `QuantizedLog`

class `QuantizedAbs`

class `QuantizedIdentity`

method `q_impl`

class `QuantizedReshape`

method `q_impl`

class `QuantizedConv`

method `init`

method `q_impl`

class `QuantizedAvgPool`

method `init`

method `q_impl`

class `QuantizedMaxPool`

method `init`