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etnaviv/ml: Add support for Absolute

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Add a TP job that makes use of a look up table to implement a piecewise
linear approximation of the absolute function.

Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/34629>
This commit is contained in:
Tomeu Vizoso 2025-04-11 09:29:24 +02:00 • committed by Marge Bot
parent 519a8b0f4a
commit 67faa1525b
4 changed files with 92 additions and 1 deletions
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9
src/gallium/drivers/etnaviv/etnaviv_ml.c
View file

@ -473,6 +473,13 @@ lower_operations(struct etna_ml_subgraph *subgraph,
list_addtail(&operation->link, etna_operations);
break;
}
case PIPE_ML_OPERATION_TYPE_ABSOLUTE: {
etna_ml_lower_absolute(subgraph, poperation, operation);
operation->input_tensors[0] = input_tensors[0];
operation->output_tensors[0] = poperation->output_tensors[0]->index;
list_addtail(&operation->link, etna_operations);
break;
}
default:
unreachable("Unsupported ML operation type");
}
@ -592,6 +599,7 @@ count_tensors(const struct pipe_ml_operation *poperations,
case PIPE_ML_OPERATION_TYPE_SPLIT:
case PIPE_ML_OPERATION_TYPE_RESHAPE:
case PIPE_ML_OPERATION_TYPE_RELU:
case PIPE_ML_OPERATION_TYPE_ABSOLUTE:
break;
default:
unreachable("Unsupported ML operation type");
@ -678,6 +686,7 @@ etna_ml_operation_supported(struct pipe_context *pcontext,
}
case PIPE_ML_OPERATION_TYPE_RESHAPE:
case PIPE_ML_OPERATION_TYPE_RELU:
case PIPE_ML_OPERATION_TYPE_ABSOLUTE:
supported = true;
break;
default:

1
src/gallium/drivers/etnaviv/etnaviv_ml.h
View file

@ -27,6 +27,7 @@ enum etna_ml_tp_type {
ETNA_ML_TP_RESHUFFLE,
ETNA_ML_TP_PAD,
ETNA_ML_TP_RELU,
ETNA_ML_TP_ABSOLUTE,
};
enum etna_ml_tensor_layout {

78
src/gallium/drivers/etnaviv/etnaviv_ml_tp.c
View file

@ -1054,6 +1054,36 @@ etna_ml_lower_relu(struct etna_ml_subgraph *subgraph,
relu->output_channels;
}
void
etna_ml_lower_absolute(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *abs,
struct etna_operation *operation)
{
operation->type = ETNA_JOB_TYPE_TP;
operation->tp_type = ETNA_ML_TP_ABSOLUTE;
operation->stride = 1;
operation->input_count = 1;
operation->input_width = abs->input_tensors[0]->dims[1];
operation->input_height = abs->input_tensors[0]->dims[2];
operation->input_channels = abs->input_tensors[0]->dims[3];
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_zero_point = etna_tensor_zero_point(abs->input_tensors[0]);
operation->input_scale = abs->input_tensors[0]->scale;
operation->output_count = 1;
operation->output_width = abs->output_tensors[0]->dims[1];
operation->output_height = abs->output_tensors[0]->dims[2];
operation->output_channels = abs->output_tensors[0]->dims[3];
operation->output_zero_point = etna_tensor_zero_point(abs->output_tensors[0]);
operation->output_scale = abs->output_tensors[0]->scale;
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
}
static struct etna_bo *
create_relu_lut_bo(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation)
@ -1085,6 +1115,41 @@ create_relu_lut_bo(struct etna_ml_subgraph *subgraph,
return pwl_lut;
}
static struct etna_bo *
create_abs_lut_bo(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation)
{
struct pipe_context *context = subgraph->base.context;
struct etna_context *ctx = etna_context(context);
unsigned lut_length = 1024;
struct etna_bo *pwl_lut = etna_bo_new(ctx->screen->dev,
lut_length * sizeof(uint32_t),
DRM_ETNA_GEM_CACHE_WC);
etna_bo_cpu_prep(pwl_lut, DRM_ETNA_PREP_WRITE);
uint32_t *map = etna_bo_map(pwl_lut);
for (int i = 0; i < lut_length; i++) {
if (i < 16)
map[i] = 0x0;
else if (i < 496)
map[i] = 0x8000 + (i - 16) * 0x800;
else if (i < 512)
map[i] = 0xf7fff;
else if (i < 528)
map[i] = 0x100000;
else if (i < 1008)
map[i] = 0x8000 + (i - 528) * 0x800;
else if (i < 1024)
map[i] = 0xf7fff;
}
etna_bo_cpu_fini(pwl_lut);
return pwl_lut;
}
void
etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation,
@ -1151,6 +1216,16 @@ etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
}
break;
}
case ETNA_ML_TP_ABSOLUTE: {
unsigned tp_cores_used = etna_ml_get_core_info(ctx)->tp_core_count;
ML_DBG("absolute: input_width %d tp_cores_used %d\n", operation->input_width, tp_cores_used);
instruction->pwl_lut = create_abs_lut_bo(subgraph, operation);
for (unsigned i = 0; i < tp_cores_used; i++) {
instruction->configs[i] = create_pwl_lut_config(subgraph, operation, i, tp_cores_used, instruction->pwl_lut);
}
break;
}
}
instruction->type = ETNA_JOB_TYPE_TP;
instruction->tp_type = operation->tp_type;
@ -1179,7 +1254,8 @@ etna_ml_emit_operation_tp(struct etna_ml_subgraph *subgraph,
if (more_than_one_tp_job &&
(operation->tp_type == ETNA_ML_TP_PAD ||
operation->tp_type == ETNA_ML_TP_RELU)) {
operation->tp_type == ETNA_ML_TP_RELU ||
operation->tp_type == ETNA_ML_TP_ABSOLUTE)) {
etna_set_state(stream, VIVS_GL_UNK03950, j < tp_core_count - 1 ? 0x8 : 0x0);
} else {
etna_set_state(stream, VIVS_GL_UNK03950, 0x0);

5
src/gallium/drivers/etnaviv/etnaviv_ml_tp.h
View file

@ -31,6 +31,11 @@ etna_ml_lower_relu(struct etna_ml_subgraph *subgraph,
const struct pipe_tensor *input_tensor,
struct etna_operation *relu);
void
etna_ml_lower_absolute(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *pad,
struct etna_operation *operation);
void
etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
const struct etna_operation *operation,