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.. _op_ai_onnx_DequantizeLinear-10:

DequantizeLinear - version 10
=============================

This page documents version **10** of operator **DequantizeLinear**. See :doc:`DequantizeLinear` for the latest version (since version 25).

- **Domain**: ``ai.onnx``
- **Since version**: 10

The linear dequantization operator. It consumes a quantized tensor, a scale, a zero point to compute the full precision tensor.
The dequantization formula is y = (x - x_zero_point) \* x_scale. 'x_scale' and 'x_zero_point' are both scalars.
'x_zero_point' and 'x' must have same type. 'x' and 'y' must have same shape. In the case of dequantizing int32,
there's no zero point (zero point is supposed to be 0).

**Inputs**

- **x** (*T*): N-D quantized input tensor to be de-quantized.
- **x_scale** (*tensor(float)*): Scale for input 'x'. It's a scalar, which means a per-tensor/layer quantization.
- **x_zero_point** (*T*): Zero point for input 'x'. It's a scalar, which means a per-tensor/layer quantization. It's optional. 0 is the default value when it's not specified.

**Outputs**

- **y** (*tensor(float)*): N-D full precision output tensor. It has same shape as input 'x'.

**Type Constraints**

- **T**: Constrain 'x_zero_point' and 'x' to 8-bit/32-bit integer tensor.
  Allowed types: tensor(int32), tensor(int8), tensor(uint8).