Module furiosa.quantizer.ir.spec

Classes

class Add (shape: List[int])

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class Add(OperatorSpec):
    def kind(self):
        return 'Add'

    def __init__(self, shape: List[int]):
        self.shape = shape

Ancestors

• OperatorSpec

Subclasses

• Div
• Exp
• Gelu
• Mul
• Sigmoid
• Sub

Methods

def kind(self)

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def kind(self):
    return 'Add'

class AveragePool2d (input: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, kernel: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, stride: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, dilation: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, batch: int, channel: int, padding: furiosa_sdk_quantizer.ir.common.operator.Padding)

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class AveragePool2d(OperatorSpec):
    def kind(self):
        return 'AveragePool2d'

    def __init__(self, input: HeightWidth, kernel: HeightWidth, stride: HeightWidth, dilation: HeightWidth,
                 batch: int, channel: int, padding: Padding):
        self.input = input
        self.kernel = kernel
        self.stride = stride
        self.batch = batch
        self.channel = channel
        self.dilation = dilation
        self.padding_spec = PaddingSpecCustom(padding)

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'AveragePool2d'

class Clip (input_shape: List[int], min: Union[float, NoneType] = None, max: Union[float, NoneType] = None)

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class Clip(OperatorSpec):
    def kind(self):
        return 'Clip'

    def __init__(self, input_shape: List[int], min: Optional[float] = None, max: Optional[float] = None):
        self.input_shape = input_shape
        self.min = min
        self.max = max

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Clip'

class Concatenation (tensors: List[List[int]], axis: int)

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class Concatenation(OperatorSpec):
    def kind(self):
        return 'Concatenation'

    def __init__(self, tensors: List[List[int]], axis: int):
        self.tensors = tensors
        self.axis = axis

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Concatenation'

class Conv2d (input: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, kernel: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, stride: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, dilation: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, batch: int, input_channel: int, output_channel: int, groups: int, padding: furiosa_sdk_quantizer.ir.common.operator.Padding)

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class Conv2d(OperatorSpec):
    def kind(self):
        return 'Conv2d'

    def __init__(self, input: HeightWidth, kernel: HeightWidth, stride: HeightWidth, dilation: HeightWidth,
                 batch: int, input_channel: int, output_channel: int, groups: int, padding: Padding):
        self.input = input
        self.kernel = kernel
        self.stride = stride
        self.dilation = dilation
        self.batch = batch
        self.input_channel = input_channel
        self.output_channel = output_channel
        self.groups = groups
        self.padding_spec = PaddingSpecCustom(padding)

Ancestors

• OperatorSpec

Subclasses

• TrasnposeConv

Methods

def kind(self)

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def kind(self):
    return 'Conv2d'

class DepthToSpace (batch: int, height: int, width: int, channel: int, block_size: int, mode: str)

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class DepthToSpace(OperatorSpec):
    def kind(self):
        return 'DepthToSpace'

    def __init__(self, batch: int, height: int, width: int, channel: int, block_size: int, mode: str):
        self.batch = batch
        self.height = height
        self.width = width
        self.channel = channel
        self.block_size = block_size
        self.mode = mode

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'DepthToSpace'

class Div (shape: List[int])

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class Div(Add):
    def kind(self):
        return 'Div'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Div'

class Exp (shape: List[int])

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class Exp(Add):
    def kind(self):
        return 'Exp'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Exp'

class Expand (input_shape: List[int], output_shape: List[int])

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class Expand(Reshape):
    def kind(self):
        return 'Expand'

Ancestors

• Reshape
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Expand'

class Flatten (shape: List[int], axis: int)

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class Flatten(OperatorSpec):
    def kind(self):
        return 'Flatten'

    def __init__(self, shape: List[int], axis: int):
        self.shape = shape
        # The field `Axis` isn't in npu-tools.
        self.axis = axis

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Flatten'

class Gelu (shape: List[int])

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class Gelu(Add):
    def kind(self):
        return 'Gelu'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Gelu'

class Gemm (alpha: float, beta: float, m: int, k: int, n: int)

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class Gemm(OperatorSpec):
    def kind(self):
        return 'Gemm'

    def __init__(self, alpha: float, beta: float, m: int, k: int, n: int):
        self.alpha = alpha
        self.beta = beta
        self.m = m
        self.k = k
        self.n = n

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Gemm'

class LayerNorm (input_shape: List[int], eps: float)

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class LayerNorm(OperatorSpec):
    def kind(self):
        return 'LayerNorm'

    def __init__(self, input_shape: List[int], eps: float):
        self.input_shape = input_shape
        self.eps = eps

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'LayerNorm'

class LpNorm (input_shape: List[int], p: int, axis: int)

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class LpNorm(OperatorSpec):
    def kind(self):
        return 'LpNorm'

    def __init__(self, input_shape: List[int], p: int, axis: int):
        self.input_shape = input_shape
        self.p = p
        self.axis = axis

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'LpNorm'

class MatMul (lhs_shape: List[int], rhs_shape: List[int])

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class MatMul(OperatorSpec):
    def kind(self):
        return 'MatMul'

    def __init__(self, lhs_shape: List[int], rhs_shape: List[int]):
        self.lhs_shape = lhs_shape
        self.rhs_shape = rhs_shape

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'MatMul'

class MaxPool2d (input: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, kernel: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, stride: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, dilation: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, batch: int, channel: int, padding: furiosa_sdk_quantizer.ir.common.operator.Padding)

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class MaxPool2d(OperatorSpec):
    def kind(self):
        return 'MaxPool2d'

    def __init__(self, input: HeightWidth, kernel: HeightWidth, stride: HeightWidth, dilation: HeightWidth,
                 batch: int, channel: int, padding: Padding):
        self.input = input
        self.kernel = kernel
        self.stride = stride
        self.dilation = dilation
        self.batch = batch
        self.channel = channel
        self.padding_spec = PaddingSpecCustom(padding)

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'MaxPool2d'

class Mul (shape: List[int])

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class Mul(Add):
    def kind(self):
        return 'Mul'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Mul'

class OperatorSpec

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class OperatorSpec:
    def kind(self):
        raise NotImplementedError()

    def as_dict(self) -> Dict[str, any]:
        return {self.kind(): dict(map(lambda item: self._handle_nested_spec(*item), vars(self).items()))}

    @staticmethod
    def _handle_nested_spec(k, v):
        if hasattr(v, 'as_dict'):
            return k, getattr(v, 'as_dict')()
        else:
            return k, v

Subclasses

• Add
• AveragePool2d
• Clip
• Concatenation
• Conv2d
• DepthToSpace
• Flatten
• Gemm
• LayerNorm
• LpNorm
• MatMul
• MaxPool2d
• Pad
• ReduceMean
• Reshape
• Resize
• Slice
• Softmax
• Softplus
• Split
• Transpose

Methods

def as_dict(self) ‑> Dict[str, ]

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def as_dict(self) -> Dict[str, any]:
    return {self.kind(): dict(map(lambda item: self._handle_nested_spec(*item), vars(self).items()))}

def kind(self)

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def kind(self):
    raise NotImplementedError()

class Pad (shape: List[int], pad: List[furiosa_sdk_quantizer.ir.common.operator.HorizontalPadding])

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class Pad(OperatorSpec):
    def kind(self):
        return 'Pad'

    def __init__(self, shape: List[int], pad: List[HorizontalPadding]):
        self.shape = shape
        self.pad = pad

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Pad'

class PaddingSpecCustom (padding: furiosa_sdk_quantizer.ir.common.operator.Padding)

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class PaddingSpecCustom:
    def __init__(self, padding: Padding):
        self.Custom = padding

class ReduceL2 (shape: List[int], axes: List[int])

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class ReduceL2(ReduceMean):
    def kind(self):
        return 'ReduceL2'

Ancestors

• ReduceMean
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'ReduceL2'

class ReduceMean (shape: List[int], axes: List[int])

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class ReduceMean(OperatorSpec):
    def kind(self):
        return 'ReduceMean'

    def __init__(self, shape: List[int], axes: List[int]):
        self.shape = shape
        self.axes = axes

Ancestors

• OperatorSpec

Subclasses

• ReduceL2
• ReduceSum
• Squeeze
• Unsqueeze

Methods

def kind(self)

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def kind(self):
    return 'ReduceMean'

class ReduceSum (shape: List[int], axes: List[int])

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class ReduceSum(ReduceMean):
    def kind(self):
        return 'ReduceSum'

Ancestors

• ReduceMean
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'ReduceSum'

class Reshape (input_shape: List[int], output_shape: List[int])

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class Reshape(OperatorSpec):
    def kind(self):
        return 'Reshape'

    def __init__(self, input_shape: List[int], output_shape: List[int]):
        self.input_shape = input_shape
        self.output_shape = output_shape

Ancestors

• OperatorSpec

Subclasses

• Expand

Methods

def kind(self)

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def kind(self):
    return 'Reshape'

class Resize (shape: List[int], roi: List[int], scales: List[float], sizes: List[int])

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class Resize(OperatorSpec):
    def kind(self):
        return 'Resize'

    def __init__(self, shape: List[int], roi: List[int], scales: List[float], sizes: List[int]):
        self.shape = shape
        self.roi = roi
        self.scales = scales
        self.sizes = sizes

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Resize'

class Sigmoid (shape: List[int])

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class Sigmoid(Add):
    def kind(self):
        return 'Sigmoid'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Sigmoid'

class Slice (shape: List[int], offset: List[int])

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class Slice(OperatorSpec):
    def kind(self):
        return 'Slice'

    def __init__(self, shape: List[int], offset: List[int]):
        self.shape = shape
        self.offset = offset

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Slice'

class Softmax (input_shape: List[int], beta: float, axis: int)

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class Softmax(OperatorSpec):
    def kind(self):
        return 'Softmax'

    def __init__(self, input_shape: List[int], beta: float, axis: int):
        self.input_shape = input_shape
        self.beta = beta
        self.axis = axis

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Softmax'

class Softplus (input_shape: List[int])

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class Softplus(OperatorSpec):
    def kind(self):
        return 'Softplus'

    def __init__(self, input_shape: List[int]):
        self.input_shape = input_shape

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Softplus'

class Spec (name: str, operator_spec: OperatorSpec)

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class Spec:
    def __init__(self, name: str, operator_spec: "OperatorSpec"):
        self.name = name
        self.option = operator_spec

    def kind(self):
        raise NotImplementedError()

    def as_dict(self) -> Dict[str, any]:
        return {
            'name': self.name,
            'option': {
                # quantizer only supports 'OperatorSpec'.
                'Operator': self.option.as_dict(),
            }
        }

Methods

def as_dict(self) ‑> Dict[str, ]

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def as_dict(self) -> Dict[str, any]:
    return {
        'name': self.name,
        'option': {
            # quantizer only supports 'OperatorSpec'.
            'Operator': self.option.as_dict(),
        }
    }

def kind(self)

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def kind(self):
    raise NotImplementedError()

class Split (shape: List[int], split: List[int], axis: int)

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class Split(OperatorSpec):
    def kind(self):
        return 'Split'

    def __init__(self, shape: List[int], split: List[int], axis: int):
        self.shape = shape
        self.split = split
        self.axis = axis

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Split'

class Squeeze (shape: List[int], axes: List[int])

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class Squeeze(ReduceMean):
    def kind(self):
        return 'Squeeze'

Ancestors

• ReduceMean
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Squeeze'

class Sub (shape: List[int])

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class Sub(Add):
    def kind(self):
        return 'Sub'

Ancestors

• Add
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Sub'

class Transpose (shape: List[int], permutation: List[int])

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class Transpose(OperatorSpec):
    def kind(self):
        return 'Transpose'

    def __init__(self, shape: List[int], permutation: List[int]):
        self.shape = shape
        self.permutation = permutation

Ancestors

• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Transpose'

class TrasnposeConv (input: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, kernel: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, stride: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, dilation: furiosa_sdk_quantizer.ir.common.operator.HeightWidth, batch: int, input_channel: int, output_channel: int, groups: int, padding: furiosa_sdk_quantizer.ir.common.operator.Padding)

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class TrasnposeConv(Conv2d):
    def kind(self):
        return 'TransposeConv'

Ancestors

• Conv2d
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'TransposeConv'

class Unsqueeze (shape: List[int], axes: List[int])

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class Unsqueeze(ReduceMean):
    def kind(self):
        return 'Unsqueeze'

Ancestors

• ReduceMean
• OperatorSpec

Methods

def kind(self)

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def kind(self):
    return 'Unsqueeze'