tvm.relax.op.qdq 源代码

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"""Relax quantize/dequantize operators"""

from ..expr import Expr
from . import _ffi_api




def quantize(data: Expr, scale: Expr, zero_point: Expr, axis: int = -1, out_dtype: str = "int8"):
    r"""Quantize op
    This operator takes input and produces quantized output. The input tensor can be of any shape.
    The output shape is the same as input shape.

    Q_output = clamp((round(input_tensor/scale) + zero_point), out_dtype::min, out_dtype::max)

    Parameters
    ----------
    data : tvm.relax.Expr
        The input tensor to be quantized.

    scale : tvm.relax.Expr
        The output scale.

    zero_point : tvm.relax.Expr
        The output zero_point.

    axis : int
        The channel axis for quantization. Default value is -1 which corresponds to the last axis.

    out_dtype : str, optional
        The data type of the output tensor.

    Returns
    -------
    result : tvm.relax.Expr
        The computed result.
    """

    return _ffi_api.quantize(data, scale, zero_point, axis, out_dtype)





def dequantize(
    data: Expr, scale: Expr, zero_point: Expr, axis: int = -1, out_dtype: str = "float32"
):
    r"""Dequantize op
    This operator takes input and produces dequantized output. The input tensor can be of any shape.
    The output shape is the same as input shape.

    output = clamp(scale * (input_tensor - zero_point), out_dtype::min, out_dtype::max)

    Parameters
    ----------
    data : tvm.relax.Expr
        The input tensor to be dequantized.

    scale : tvm.relax.Expr
        The input scale.

    zero_point : tvm.relax.Expr
        The input zero_point.

    axis : int
        The channel axis for dequantization. Default value is -1 which corresponds to the last axis.

    out_dtype : str, optional
        The data type of the output tensor.

    Returns
    -------
    result : tvm.relax.Expr
        The computed result.
    """

    return _ffi_api.dequantize(data, scale, zero_point, axis, out_dtype)