Visible to Intel only — GUID: wws1709771079070
Ixiasoft
Visible to Intel only — GUID: wws1709771079070
Ixiasoft
2.5.2.13. Parameter Group: layout_transform_params
These parameters configure the input tensor layout transformation module of the FPGA AI Suite IP.
Parameter: layout_transform_params/enable_bias_scale
When true, the layout transform can apply bias and scale values to the input as part of the transform operation. The bias and scale values are set by the compiler. Otherwise, this operation is done in the runtime software if applicable, or in the PE array.
Parameter: layout_transform_params/do_u8_fp16_conversion
When true, this parameter enables hardware to convert 8-bit integer input values to FP16 format, and 8-bit unsigned integers must be given as inputs. Otherwise, no conversion is done and you must write FP16 values at the input.
- Legal values:
- [true, false]
Parameters: layout_transform_params/max_channels, layout_transform_params/max_feature_height, layout_transform_params/max_feature_width, layout_transform_params/max_feature_depth, layout_transform_params/max_stride_height, layout_transform_params/ max_stride_width, layout_transform_params/max_stride_depth, layout_transform_params/max_pad_top, layout_transform_params/max_pad_left, layout_transform_params/max_pad_depth, layout_transform_params/ max_filter_width, layout_transform_params/max_filter_height, layout_transform_params/max_filter_depth
This group configures the range of feature shapes, padding, and convolution strides that the layout transform hardware module supports. The values in this configuration represent the maximum allowed values for each parameter. However, the resource usage of the layout transform is sensitive to the parameterization, so set these values as close to the actual values as possible.
The parameters of the first convolution in the graph must fit within the maximum range configured here. The exact parameters required by the layout transform module are reported by the FPGA AI Suite compiler in a file named input_transform_dump_<graphname>.csv.
For more information about the input tensor layout transform, refer to Input Feature Tensor In-Memory Format.