concrete.ml.quantization.quantized_ops

module concrete.ml.quantization.quantized_ops

Quantized versions of the ONNX operators for post training quantization.

class QuantizedSigmoid

Quantized sigmoid op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedHardSigmoid

Quantized HardSigmoid op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedRelu

Quantized Relu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedPRelu

Quantized PRelu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedLeakyRelu

Quantized LeakyRelu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedHardSwish

Quantized Hardswish op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedElu

Quantized Elu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedSelu

Quantized Selu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedCelu

Quantized Celu op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedClip

Quantized clip op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedRound

Quantized round op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedPow

Quantized pow op.

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

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method can_fuse

can_fuse()

Determine if this op can be fused.

Gemm operation can not be fused since it must be performed over integer tensors and it combines different values of the input tensors.

Returns:

• bool: False, this operation can not be fused as it adds different encrypted integers

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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method can_fuse

can_fuse()

Determine if this op can be fused.

Gemm operation can not be fused since it must be performed over integer tensors and it combines different values of the input tensors.

Returns:

• bool: False, this operation can not be fused as it adds different encrypted integers

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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedSoftplus

Quantized Softplus op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedExp

Quantized Exp op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedLog

Quantized Log op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedAbs

Quantized Abs op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

class QuantizedIdentity

Quantized Identity op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method q_impl

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

class QuantizedReshape

Quantized Reshape op.

property op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

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 1 on all dimensions.

• group (int): number of convolution groups, default 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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method can_fuse

can_fuse() → bool

Determine if this op can be fused.

Conv operation can not be fused since it must be performed over integer tensors and it combines different elements of the input tensors.

Returns:

• bool: False, this operation can not be fused as it adds different encrypted integers

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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method can_fuse

can_fuse() → bool

Determine if this op can be fused.

Avg Pooling operation can not be fused since it must be performed over integer tensors and it combines different elements of the input tensors.

Returns:

• bool: False, this operation can not be fused as it adds different encrypted integers

method q_impl

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

class QuantizedPad

Quantized Padding 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 op_type

Get the type of this operation.

Returns:

• op_type (str): The type of this operation, in the ONNX referential

method can_fuse

can_fuse() → bool

Determine if this op can be fused.

Pad operation can not be fused since it must be performed over integer tensors.

Returns:

• bool: False, this operation can not be fused as it is manipulates integer tensors

class