furiosa.quantizer.ir.spec package

Module contents

class furiosa.quantizer.ir.spec.Add(shape: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Clip(input_shape: List[int], min: Optional[float] = None, max: Optional[float] = None)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Concatenation(tensors: List[List[int]], axis: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.DepthToSpace(batch: int, height: int, width: int, channel: int, block_size: int, mode: str)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Div(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.Exp(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.Expand(input_shape: List[int], output_shape: List[int])

Bases: furiosa.quantizer.ir.spec.Reshape

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class furiosa.quantizer.ir.spec.Flatten(shape: List[int], axis: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Gelu(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.Gemm(alpha: float, beta: float, m: int, k: int, n: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.LayerNorm(input_shape: List[int], eps: float)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.LpNorm(input_shape: List[int], p: int, axis: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.MatMul(lhs_shape: List[int], rhs_shape: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Mul(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.OperatorSpec

Bases: object

as_dict() → Dict[str, any]

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

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.PaddingSpecCustom(padding: furiosa.quantizer.ir.common.operator.Padding)

Bases: object

class furiosa.quantizer.ir.spec.ReduceL2(shape: List[int], axes: List[int])

Bases: furiosa.quantizer.ir.spec.ReduceMean

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class furiosa.quantizer.ir.spec.ReduceMean(shape: List[int], axes: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.ReduceSum(shape: List[int], axes: List[int])

Bases: furiosa.quantizer.ir.spec.ReduceMean

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class furiosa.quantizer.ir.spec.Reshape(input_shape: List[int], output_shape: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Resize(shape: List[int], roi: List[int], scales: List[float], sizes: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Sigmoid(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.Slice(shape: List[int], offset: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Softmax(input_shape: List[int], beta: float, axis: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Softplus(input_shape: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Spec(name: str, operator_spec: furiosa.quantizer.ir.spec.OperatorSpec)

Bases: object

as_dict() → Dict[str, any]

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class furiosa.quantizer.ir.spec.Split(shape: List[int], split: List[int], axis: int)

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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class furiosa.quantizer.ir.spec.Squeeze(shape: List[int], axes: List[int])

Bases: furiosa.quantizer.ir.spec.ReduceMean

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class furiosa.quantizer.ir.spec.Sub(shape: List[int])

Bases: furiosa.quantizer.ir.spec.Add

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class furiosa.quantizer.ir.spec.Transpose(shape: List[int], permutation: List[int])

Bases: furiosa.quantizer.ir.spec.OperatorSpec

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

Bases: furiosa.quantizer.ir.spec.Conv2d

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class furiosa.quantizer.ir.spec.Unsqueeze(shape: List[int], axes: List[int])

Bases: furiosa.quantizer.ir.spec.ReduceMean

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