.. SPDX-FileCopyrightText: 2020-2021 Intel Corporation .. .. SPDX-License-Identifier: CC-BY-4.0 ------- Minimum ------- **Versioned name**: *Minimum-1* **Category**: *Arithmetic* **Short description**: *Minimum* performs element-wise minimum operation with two given tensors applying multi-directional broadcast rules. **OpenVINO description**: This OP is as same as `OpenVINO OP `__ **Attributes**: * *auto_broadcast* * **Description**: specifies rules used for auto-broadcasting of input tensors. * **Range of values**: * *none* - no auto-broadcasting is allowed, all input shapes should match * *numpy* - numpy broadcasting rules, aligned with ONNX Broadcasting. Description is available in `ONNX docs `__. * **Type**: string * **Default value**: "numpy" * **Required**: *no* **Inputs** * **1**: ``input_1`` - the first input tensor. **Required.** * **Type**: T * **2**: ``input_2`` - the second input tensor. **Required.** * **Type**: T **Outputs** * **1**: ``output`` - the output of element-wise minimum operation. * **Type**: T **Types**: * **T**: f32, f16, bf16. * **Note**: Inputs and outputs have the same data type denoted by *T*. For example, if input is f32 tensor, then all other tensors have f32 data type. **Detailed description:** Before performing arithmetic operation, *input_1* and *input_2* are broadcasted if their shapes are different and ``auto_broadcast`` attributes is not ``none``. Broadcasting is performed according to ``auto_broadcast`` value. After broadcasting *Minimum* does the following with *input_1* and *input_2*: .. math:: output_{i} = min(input\_1_{i}, input\_2_{i})