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ethosu: Add fully-connected operation

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Add support for fully-connected convolution. FC convolution lowering is
nearly the same, so refactor the existing convolution code to support
both.

Signed-off-by: Rob Herring (Arm) <robh@kernel.org>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/39975>
This commit is contained in:
Rob Herring (Arm) 2026-02-17 12:48:32 -06:00 • committed by Marge Bot
parent ed65f84921
commit fe97dab8b0
2 changed files with 64 additions and 28 deletions
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88
src/gallium/drivers/ethosu/ethosu_lower.c
View file

@ -159,30 +159,18 @@ ethosu_find_first_producer(const struct pipe_ml_operation *poperations, unsigned
}
static void
ethosu_lower_convolution(struct ethosu_subgraph *subgraph,
const struct pipe_ml_operation *poperation,
struct pipe_tensor *input_tensor,
struct ethosu_operation *operation)
lower_conv_common(struct ethosu_subgraph *subgraph,
const struct pipe_ml_operation *poperation,
struct pipe_tensor *input_tensor,
struct pipe_tensor *weight,
int32_t *bias_data,
struct ethosu_operation *operation)
{
uint8_t *bias_data = poperation->conv.bias_tensor ? poperation->conv.bias_tensor->data : NULL;
operation->type = ETHOSU_OPERATION_TYPE_CONVOLUTION;
operation->conv.depthwise = is_depthwise(poperation);
set_feature_maps(subgraph, input_tensor, poperation->output_tensors[0], operation);
operation->kernel.height = poperation->conv.weight_tensor->dims[1];
operation->kernel.width = poperation->conv.weight_tensor->dims[2];
operation->kernel.stride_y = poperation->conv.stride_y;
operation->kernel.stride_x = poperation->conv.stride_x;
operation->kernel.depthwise = is_depthwise(poperation);
operation->kernel.scale = poperation->conv.weight_tensor->scale;
operation->kernel.zero_point = poperation->conv.weight_tensor->zero_point;
operation->kernel.is_signed = poperation->conv.weight_tensor->is_signed;
/* Per-channel quantization support */
struct pipe_tensor *weight = poperation->conv.weight_tensor;
unsigned num_channels = poperation->output_tensors[0]->dims[3];
if (weight->scales != NULL) {
@ -195,21 +183,57 @@ ethosu_lower_convolution(struct ethosu_subgraph *subgraph,
memcpy(operation->kernel.zero_points, weight->zero_points, num_channels * sizeof(int));
}
allocate_feature_maps(subgraph, operation);
ethosu_sched_operation(subgraph, operation);
fill_coefs(subgraph, operation, bias_data, weight->data,
weight->dims[0] * weight->dims[1] * weight->dims[2] * weight->dims[3]);
}
static void
ethosu_lower_fully_connected(struct ethosu_subgraph *subgraph,
const struct pipe_ml_operation *poperation,
struct pipe_tensor *input_tensor,
struct ethosu_operation *operation)
{
operation->kernel.scale = poperation->fcon.weight_tensor->scale;
operation->kernel.zero_point = poperation->fcon.weight_tensor->zero_point;
operation->kernel.is_signed = poperation->fcon.weight_tensor->is_signed;
lower_conv_common(subgraph, poperation, input_tensor,
poperation->fcon.weight_tensor,
(int32_t *)poperation->fcon.bias_tensor->data,
operation);
}
static void
ethosu_lower_convolution(struct ethosu_subgraph *subgraph,
const struct pipe_ml_operation *poperation,
struct pipe_tensor *input_tensor,
struct ethosu_operation *operation)
{
int32_t *bias_data = poperation->conv.bias_tensor ? (int32_t *)poperation->conv.bias_tensor->data : NULL;
operation->conv.depthwise = is_depthwise(poperation);
operation->kernel.height = poperation->conv.weight_tensor->dims[1];
operation->kernel.width = poperation->conv.weight_tensor->dims[2];
operation->kernel.stride_y = poperation->conv.stride_y;
operation->kernel.stride_x = poperation->conv.stride_x;
operation->kernel.depthwise = is_depthwise(poperation);
operation->kernel.scale = poperation->conv.weight_tensor->scale;
operation->kernel.zero_point = poperation->conv.weight_tensor->zero_point;
operation->kernel.is_signed = poperation->conv.weight_tensor->is_signed;
operation->pad.top = poperation->conv.padding_top;
operation->pad.bottom = poperation->conv.padding_bottom;
operation->pad.left = poperation->conv.padding_left;
operation->pad.right = poperation->conv.padding_right;
allocate_feature_maps(subgraph, operation);
ethosu_sched_operation(subgraph, operation);
fill_coefs(subgraph, operation, (int32_t *)bias_data,
poperation->conv.weight_tensor->data,
poperation->conv.weight_tensor->dims[0] *
poperation->conv.weight_tensor->dims[1] *
poperation->conv.weight_tensor->dims[2] *
poperation->conv.weight_tensor->dims[3]);
lower_conv_common(subgraph, poperation, input_tensor,
poperation->conv.weight_tensor,
(int32_t *)bias_data,
operation);
}
static void
@ -445,6 +469,14 @@ ethosu_lower_graph(struct ethosu_subgraph *subgraph,
switch (poperations[i].type) {
case PIPE_ML_OPERATION_TYPE_FULLY_CONNECTED: {
struct pipe_tensor *input_tensor = poperations[i].input_tensors[0];
ethosu_lower_fully_connected(subgraph, &poperations[i], input_tensor, &operation);
util_dynarray_append(&subgraph->operations, operation);
break;
}
case PIPE_ML_OPERATION_TYPE_CONVOLUTION: {
struct pipe_tensor *input_tensor = poperations[i].input_tensors[0];
const struct pipe_ml_operation *producer = ethosu_find_first_producer(poperations, count, input_tensor->index);

4
src/gallium/drivers/ethosu/ethosu_ml.c
View file

@ -126,6 +126,10 @@ ethosu_ml_operation_supported(struct pipe_ml_device *pdevice,
return false;
switch (operation->type) {
case PIPE_ML_OPERATION_TYPE_FULLY_CONNECTED: {
supported = true;
break;
}
case PIPE_ML_OPERATION_TYPE_CONVOLUTION: {
/*
* Dilation is not yet implemented.