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etnaviv/ml: Add support for tensor split and concatenation operations

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Just point previous and further operations to offsets in a combined
tensor.

Reviewed-by: Philipp Zabel <p.zabel@pengutronix.de>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/32498>
This commit is contained in:
Tomeu Vizoso
2024-12-05 09:15:36 +01:00
committed by Marge Bot
parent 4ced6480ea
commit c2d1f08116
6 changed files with 203 additions and 229 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/etnaviv/ci/etnaviv-vipnano-fails.txt
-77
View File
@@ -290,80 +290,3 @@ DepthwiseConv2D.Op/input_size_5_weight_size_5_channels_256_stride_2_padding_same
DepthwiseConv2D.Op/input_size_5_weight_size_5_channels_32_stride_2_padding_same_1_is_signed_0,Fail
YoloX.Whole,Fail
YoloXParam.Op/yolox005,Fail
YoloXParam.Op/yolox007,Fail
YoloXParam.Op/yolox008,Fail
YoloXParam.Op/yolox009,Fail
YoloXParam.Op/yolox010,Fail
YoloXParam.Op/yolox012,Fail
YoloXParam.Op/yolox014,Fail
YoloXParam.Op/yolox016,Fail
YoloXParam.Op/yolox017,Fail
YoloXParam.Op/yolox018,Fail
YoloXParam.Op/yolox019,Fail
YoloXParam.Op/yolox021,Fail
YoloXParam.Op/yolox022,Fail
YoloXParam.Op/yolox024,Fail
YoloXParam.Op/yolox025,Fail
YoloXParam.Op/yolox027,Fail
YoloXParam.Op/yolox029,Fail
YoloXParam.Op/yolox031,Fail
YoloXParam.Op/yolox032,Fail
YoloXParam.Op/yolox033,Fail
YoloXParam.Op/yolox034,Fail
YoloXParam.Op/yolox036,Fail
YoloXParam.Op/yolox037,Fail
YoloXParam.Op/yolox039,Fail
YoloXParam.Op/yolox040,Fail
YoloXParam.Op/yolox042,Fail
YoloXParam.Op/yolox044,Fail
YoloXParam.Op/yolox046,Fail
YoloXParam.Op/yolox047,Fail
YoloXParam.Op/yolox052,Fail
YoloXParam.Op/yolox053,Fail
YoloXParam.Op/yolox054,Fail
YoloXParam.Op/yolox055,Fail
YoloXParam.Op/yolox056,Fail
YoloXParam.Op/yolox058,Fail
YoloXParam.Op/yolox059,Fail
YoloXParam.Op/yolox062,Fail
YoloXParam.Op/yolox063,Fail
YoloXParam.Op/yolox064,Fail
YoloXParam.Op/yolox065,Fail
YoloXParam.Op/yolox067,Fail
YoloXParam.Op/yolox068,Fail
YoloXParam.Op/yolox071,Fail
YoloXParam.Op/yolox072,Fail
YoloXParam.Op/yolox073,Fail
YoloXParam.Op/yolox074,Fail
YoloXParam.Op/yolox076,Fail
YoloXParam.Op/yolox078,Fail
YoloXParam.Op/yolox080,Fail
YoloXParam.Op/yolox081,Fail
YoloXParam.Op/yolox082,Fail
YoloXParam.Op/yolox083,Fail
YoloXParam.Op/yolox085,Fail
YoloXParam.Op/yolox087,Fail
YoloXParam.Op/yolox089,Fail
YoloXParam.Op/yolox090,Fail
YoloXParam.Op/yolox091,Fail
YoloXParam.Op/yolox092,Fail
YoloXParam.Op/yolox094,Fail
YoloXParam.Op/yolox095,Fail
YoloXParam.Op/yolox096,Fail
YoloXParam.Op/yolox097,Fail
YoloXParam.Op/yolox100,Fail
YoloXParam.Op/yolox101,Fail
YoloXParam.Op/yolox102,Fail
YoloXParam.Op/yolox106,Fail
YoloXParam.Op/yolox107,Fail
YoloXParam.Op/yolox108,Fail
YoloXParam.Op/yolox111,Fail
YoloXParam.Op/yolox112,Fail
YoloXParam.Op/yolox113,Fail
YoloXParam.Op/yolox117,Fail
YoloXParam.Op/yolox118,Fail
YoloXParam.Op/yolox119,Fail
YoloXParam.Op/yolox122,Fail
YoloXParam.Op/yolox123,Fail
YoloXParam.Op/yolox124,Fail
src/etnaviv/ci/etnaviv-vipnano-si-plus-fails.txt
-77
View File
@@ -12,80 +12,3 @@ MobileDetParam.Op/mobiledet082,Fail
MobileDet.Whole,Fail
YoloX.Whole,Fail
YoloXParam.Op/yolox005,Fail
YoloXParam.Op/yolox007,Fail
YoloXParam.Op/yolox008,Fail
YoloXParam.Op/yolox009,Fail
YoloXParam.Op/yolox010,Fail
YoloXParam.Op/yolox012,Fail
YoloXParam.Op/yolox014,Fail
YoloXParam.Op/yolox016,Fail
YoloXParam.Op/yolox017,Fail
YoloXParam.Op/yolox018,Fail
YoloXParam.Op/yolox019,Fail
YoloXParam.Op/yolox021,Fail
YoloXParam.Op/yolox022,Fail
YoloXParam.Op/yolox024,Fail
YoloXParam.Op/yolox025,Fail
YoloXParam.Op/yolox027,Fail
YoloXParam.Op/yolox029,Fail
YoloXParam.Op/yolox031,Fail
YoloXParam.Op/yolox032,Fail
YoloXParam.Op/yolox033,Fail
YoloXParam.Op/yolox034,Fail
YoloXParam.Op/yolox036,Fail
YoloXParam.Op/yolox037,Fail
YoloXParam.Op/yolox039,Fail
YoloXParam.Op/yolox040,Fail
YoloXParam.Op/yolox042,Fail
YoloXParam.Op/yolox044,Fail
YoloXParam.Op/yolox046,Fail
YoloXParam.Op/yolox047,Fail
YoloXParam.Op/yolox052,Fail
YoloXParam.Op/yolox053,Fail
YoloXParam.Op/yolox054,Fail
YoloXParam.Op/yolox055,Fail
YoloXParam.Op/yolox056,Fail
YoloXParam.Op/yolox058,Fail
YoloXParam.Op/yolox059,Fail
YoloXParam.Op/yolox062,Fail
YoloXParam.Op/yolox063,Fail
YoloXParam.Op/yolox064,Fail
YoloXParam.Op/yolox065,Fail
YoloXParam.Op/yolox067,Fail
YoloXParam.Op/yolox068,Fail
YoloXParam.Op/yolox071,Fail
YoloXParam.Op/yolox072,Fail
YoloXParam.Op/yolox073,Fail
YoloXParam.Op/yolox074,Fail
YoloXParam.Op/yolox076,Fail
YoloXParam.Op/yolox078,Fail
YoloXParam.Op/yolox080,Fail
YoloXParam.Op/yolox081,Fail
YoloXParam.Op/yolox082,Fail
YoloXParam.Op/yolox083,Fail
YoloXParam.Op/yolox085,Fail
YoloXParam.Op/yolox087,Fail
YoloXParam.Op/yolox089,Fail
YoloXParam.Op/yolox090,Fail
YoloXParam.Op/yolox091,Fail
YoloXParam.Op/yolox092,Fail
YoloXParam.Op/yolox094,Fail
YoloXParam.Op/yolox095,Fail
YoloXParam.Op/yolox096,Fail
YoloXParam.Op/yolox097,Fail
YoloXParam.Op/yolox100,Fail
YoloXParam.Op/yolox101,Fail
YoloXParam.Op/yolox102,Fail
YoloXParam.Op/yolox106,Fail
YoloXParam.Op/yolox107,Fail
YoloXParam.Op/yolox108,Fail
YoloXParam.Op/yolox111,Fail
YoloXParam.Op/yolox112,Fail
YoloXParam.Op/yolox113,Fail
YoloXParam.Op/yolox117,Fail
YoloXParam.Op/yolox118,Fail
YoloXParam.Op/yolox119,Fail
YoloXParam.Op/yolox122,Fail
YoloXParam.Op/yolox123,Fail
YoloXParam.Op/yolox124,Fail
src/gallium/drivers/etnaviv/etnaviv_ml.c
+131 -37
View File
@@ -55,7 +55,7 @@ etna_ml_create_tensor(struct etna_ml_subgraph *subgraph, unsigned idx, unsigned
struct pipe_resource *res = tensors[idx];
if (res != NULL) {
assert(size == pipe_buffer_size(res) || size == pipe_buffer_size(res) / 2);
assert(size == sizes[idx]);
return;
}
@@ -239,11 +239,19 @@ dump_graph(struct list_head *etna_operations)
switch(operation->type) {
case ETNA_JOB_TYPE_TP:
ML_DBG("%3d %-4s %3d %3d",
i, "TP", operation->input_tensors[0], operation->output_tensor);
i, "TP", operation->input_tensors[0], operation->output_tensors[0]);
break;
case ETNA_JOB_TYPE_NN:
ML_DBG("%3d %-4s %3d %3d in2: %3d",
i, "NN", operation->input_tensors[0], operation->output_tensor, operation->input_tensors[1]);
i, "NN", operation->input_tensors[0], operation->output_tensors[0], operation->input_tensors[1]);
break;
case ETNA_JOB_TYPE_CONCAT:
ML_DBG("%3d %-4s %3d %3d in2: %3d",
i, "CONC", operation->input_tensors[0], operation->output_tensors[0], operation->input_tensors[1]);
break;
case ETNA_JOB_TYPE_SPLIT:
ML_DBG("%3d %-4s %3d %3d out2: %3d",
i, "SPLIT", operation->input_tensors[0], operation->output_tensors[0], operation->output_tensors[1]);
break;
}
ML_DBG("\n");
@@ -292,7 +300,7 @@ lower_operations(struct etna_ml_subgraph *subgraph,
ML_DBG("Adding detranspose for convolution operation.\n");
struct etna_operation *detranspose = calloc(1, sizeof(*operation));
etna_ml_lower_detranspose(subgraph, operation, detranspose);
operation->output_tensor = detranspose->input_tensors[0];
operation->output_tensors[0] = detranspose->input_tensors[0];
list_addtail(&detranspose->link, etna_operations);
}
break;
@@ -305,38 +313,118 @@ lower_operations(struct etna_ml_subgraph *subgraph,
if (needs_detranspose(poperations, count, poperation)) {
struct etna_operation *detranspose = calloc(1, sizeof(*operation));
etna_ml_lower_detranspose(subgraph, operation, detranspose);
operation->output_tensor = detranspose->input_tensors[0];
operation->output_tensors[0] = detranspose->input_tensors[0];
list_addtail(&detranspose->link, etna_operations);
}
break;
}
case PIPE_ML_OPERATION_TYPE_CONCATENATION: {
bool do_transpose = needs_transpose(poperations, count, poperation);
struct etna_operation *operation = calloc(1, sizeof(*operation));
operation->type = ETNA_JOB_TYPE_CONCAT;
assert(poperation->input_count <= MAX_TENSORS);
unsigned input_size = 0;
for (int i = 0; i < poperation->input_count; i++) {
unsigned input_tensor = poperation->input_tensors[i]->index;
if (do_transpose) {
struct etna_operation *operation = calloc(1, sizeof(*operation));
etna_ml_lower_transpose(subgraph, poperation->input_tensors[i], operation, &input_tensor);
list_addtail(&operation->link, etna_operations);
}
operation->input_tensors[i] = input_tensor;
operation->input_tensor_sizes[i] = poperation->input_tensors[i]->dims[1] *
poperation->input_tensors[i]->dims[2] *
poperation->input_tensors[i]->dims[3];
input_size += input_size;
}
operation->input_count = poperation->input_count;
operation->output_tensors[0] = poperation->output_tensors[0]->index;
operation->output_width = poperation->output_tensors[0]->dims[1];
operation->output_height = poperation->output_tensors[0]->dims[2];
operation->output_channels = poperation->output_tensors[0]->dims[3];
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
list_addtail(&operation->link, etna_operations);
if (needs_detranspose(poperations, count, poperation)) {
struct etna_operation *detranspose = calloc(1, sizeof(*operation));
etna_ml_lower_detranspose(subgraph, operation, detranspose);
operation->output_tensors[0] = detranspose->input_tensors[0];
list_addtail(&detranspose->link, etna_operations);
}
break;
}
case PIPE_ML_OPERATION_TYPE_SPLIT: {
struct etna_operation *operation = calloc(1, sizeof(*operation));
operation->type = ETNA_JOB_TYPE_SPLIT;
operation->input_tensors[0] = poperation->input_tensors[1]->index;
operation->input_tensor_sizes[0] = poperation->input_tensors[1]->dims[1] *
poperation->input_tensors[1]->dims[2] *
poperation->input_tensors[1]->dims[3];
assert(poperation->output_count <= MAX_TENSORS);
for (int i = 0; i < poperation->output_count; i++) {
operation->output_tensors[i] = poperation->output_tensors[i]->index;
operation->output_tensor_sizes[i] = poperation->output_tensors[i]->dims[1] *
poperation->output_tensors[i]->dims[2] *
poperation->output_tensors[i]->dims[3];
}
operation->output_count = poperation->output_count;
list_addtail(&operation->link, etna_operations);
break;
}
default:
unreachable("Unsupported ML operation type");
}
}
/* Create combined input tensors first */
list_for_each_entry(struct etna_operation, operation, etna_operations, link) {
if (operation->input_count == 1)
continue;
if (operation->type == ETNA_JOB_TYPE_CONCAT) {
etna_ml_create_tensor(subgraph, operation->output_tensors[0], operation->output_tensor_sizes[0]);
etna_ml_create_tensor(subgraph, operation->input_tensors[0], operation->input_tensor_size);
unsigned offset = 0;
for (int i = 0; i < operation->input_count; i++) {
reference_tensor_with_offset(subgraph,
operation->output_tensors[0],
operation->input_tensors[i],
offset,
operation->input_tensor_sizes[i]);
offset += operation->input_tensor_sizes[i];
}
} else if (operation->type == ETNA_JOB_TYPE_SPLIT) {
etna_ml_create_tensor(subgraph, operation->input_tensors[0], operation->input_tensor_sizes[0]);
for (int i = 1; i < operation->input_count; i++)
unsigned offset = 0;
for (int i = 0; i < operation->output_count; i++) {
reference_tensor_with_offset(subgraph,
operation->input_tensors[0],
operation->output_tensors[i],
offset,
operation->output_tensor_sizes[i]);
offset += operation->output_tensor_sizes[i];
}
} else if (operation->type == ETNA_JOB_TYPE_NN && operation->input_count > 1) { /* Add */
etna_ml_destroy_tensor(subgraph, operation->input_tensors[0]);
etna_ml_create_tensor(subgraph, operation->input_tensors[0], operation->input_tensor_sizes[0] +
operation->input_tensor_sizes[1]);
reference_tensor_with_offset(subgraph,
operation->input_tensors[0],
operation->input_tensors[i],
i * operation->input_tensor_size / operation->input_count,
operation->input_tensor_size / operation->input_count);
}
/* Create all other input tensors */
list_for_each_entry(struct etna_operation, operation, etna_operations, link) {
if (operation->input_count != 1)
continue;
etna_ml_create_tensor(subgraph, operation->input_tensors[0], operation->input_tensor_size);
operation->input_tensors[1],
operation->input_tensor_sizes[0],
operation->input_tensor_sizes[1]);
} else {
etna_ml_create_tensor(subgraph, operation->input_tensors[0], operation->input_tensor_sizes[0]);
}
}
/* Create any output tensors that aren't inputs to other operations, these
@@ -344,12 +432,11 @@ lower_operations(struct etna_ml_subgraph *subgraph,
*/
ML_DBG("Ensuring all output tensors have their memory backing.\n");
list_for_each_entry(struct etna_operation, operation, etna_operations, link) {
struct pipe_resource *res = etna_ml_get_tensor(subgraph, operation->output_tensor);
struct pipe_resource *res = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
if (res != NULL)
continue;
unsigned size = operation->output_width * operation->output_height * operation->output_channels;
etna_ml_create_tensor(subgraph, operation->output_tensor, size);
etna_ml_create_tensor(subgraph, operation->output_tensors[0], operation->output_tensor_sizes[0]);
}
if (DBG_ENABLED(ETNA_DBG_ML_MSGS))
@@ -377,6 +464,8 @@ count_tensors(const struct pipe_ml_operation *poperations,
tensor_count = MAX2(tensor_count, poperation->conv.bias_tensor->index);
break;
case PIPE_ML_OPERATION_TYPE_ADD:
case PIPE_ML_OPERATION_TYPE_CONCATENATION:
case PIPE_ML_OPERATION_TYPE_SPLIT:
break;
default:
unreachable("Unsupported ML operation type");
@@ -437,6 +526,9 @@ etna_ml_subgraph_create(struct pipe_context *pcontext,
case ETNA_JOB_TYPE_TP:
etna_ml_compile_operation_tp(subgraph, operation, &instruction);
break;
case ETNA_JOB_TYPE_CONCAT:
case ETNA_JOB_TYPE_SPLIT:
continue;
}
util_dynarray_append(&subgraph->operations, struct etna_vip_instruction, instruction);
@@ -452,17 +544,17 @@ etna_ml_subgraph_create(struct pipe_context *pcontext,
}
static void
dump_buffer(const uint32_t *ptr, unsigned size, char *name, int operation_nr, int suboperation_nr)
dump_buffer(const uint8_t *ptr, char *name, int operation_nr, int suboperation_nr, int offset, unsigned size)
{
char buffer[255];
snprintf(buffer, sizeof(buffer), "mesa-%s-%03u-%03u.bin", name, operation_nr, suboperation_nr);
ML_DBG("Dumping buffer from 0x%lx to %s\n", ptr, buffer);
ML_DBG("Dumping buffer from 0x%lx at offset %d with size %d to %s\n", ptr, offset, size, buffer);
FILE *f = fopen(buffer, "wb");
assert(f);
fwrite(ptr, 1, size, f);
fwrite(ptr + offset, 1, size, f);
if(ferror(f)) {
ML_DBG("Error in writing to file: %s\n", strerror(errno));
}
@@ -471,10 +563,12 @@ dump_buffer(const uint32_t *ptr, unsigned size, char *name, int operation_nr, in
}
static void
dump_bo(struct etna_bo *bo, char *name, int operation_nr, int suboperation_nr)
dump_bo(struct etna_bo *bo, char *name, int operation_nr, int suboperation_nr, int offset, int size)
{
const uint32_t *map = etna_bo_map(bo);
dump_buffer(map, etna_bo_size(bo), name, operation_nr, suboperation_nr);
const uint8_t *map = etna_bo_map(bo);
if (size == 0)
size = etna_bo_size(bo) - offset;
dump_buffer(map, name, operation_nr, suboperation_nr, offset, size);
}
static void
@@ -576,12 +670,12 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
switch (operation->type) {
case ETNA_JOB_TYPE_TP:
for (unsigned j = 0; j < tp_core_count && operation->configs[j]; j++) {
dump_bo(operation->configs[j], "tp", i, j);
dump_bo(operation->configs[j], "tp", i, j, 0, 0);
}
break;
case ETNA_JOB_TYPE_NN:
dump_bo(operation->configs[0], "nn", i, 0);
dump_bo(operation->coefficients, "compressed", i, 0);
dump_bo(operation->configs[0], "nn", i, 0, 0, 0);
dump_bo(operation->coefficients, "compressed", i, 0, 0, 0);
break;
default:
unreachable("Unsupported ML operation type");
@@ -623,7 +717,7 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
close_batch(pctx);
if (DBG_ENABLED(ETNA_DBG_DUMP_SHADERS))
dump_buffer(ctx->stream->buffer, ctx->stream->offset * 4, "cmd", i, 0);
dump_buffer((uint8_t *)ctx->stream->buffer, "cmd", i, 0, 0, ctx->stream->offset * 4);
pctx->flush(pctx, NULL, 0);
@@ -631,11 +725,11 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
struct pipe_transfer *transfer = NULL;
pipe_buffer_map(pctx, operation->input, PIPE_MAP_READ, &transfer);
dump_bo(etna_resource(operation->input)->bo, "input", i, 0);
dump_bo(etna_resource(operation->input)->bo, "input", i, 0, operation->input_offset, 0);
pipe_buffer_unmap(pctx, transfer);
pipe_buffer_map(pctx, operation->output, PIPE_MAP_READ, &transfer);
dump_bo(etna_resource(operation->output)->bo, "output", i, 0);
dump_bo(etna_resource(operation->output)->bo, "output", i, 0, operation->output_offset, 0);
pipe_buffer_unmap(pctx, transfer);
}
src/gallium/drivers/etnaviv/etnaviv_ml.h
+12 -4
View File
@@ -25,6 +25,8 @@
enum etna_job_type {
ETNA_JOB_TYPE_NN,
ETNA_JOB_TYPE_TP,
ETNA_JOB_TYPE_CONCAT, /* Fake operation, won't execute on HW. Hack will go away after the move to NIR. */
ETNA_JOB_TYPE_SPLIT, /* Fake operation, won't execute on HW. Hack will go away after the move to NIR. */
};
enum etna_ml_tp_type {
@@ -57,7 +59,7 @@ struct etna_vip_instruction {
struct etna_bo *kernel;
};
#define MAX_INPUTS 10
#define MAX_TENSORS 10
struct etna_operation {
struct list_head link;
@@ -73,16 +75,22 @@ struct etna_operation {
unsigned stride;
unsigned input_tensors[MAX_INPUTS];
unsigned input_tensors[MAX_TENSORS];
unsigned input_count;
unsigned input_tensor_size;
unsigned input_tensor_sizes[MAX_TENSORS];
/* The following apply to the first input tensor only */
unsigned input_width;
unsigned input_height;
unsigned input_channels;
uint8_t input_zero_point;
float input_scale;
unsigned output_tensor;
unsigned output_tensors[MAX_TENSORS];
unsigned output_count;
unsigned output_tensor_sizes[MAX_TENSORS];
/* The following apply to the first output tensor only */
unsigned output_width;
unsigned output_height;
unsigned output_channels;
src/gallium/drivers/etnaviv/etnaviv_ml_nn.c
+28 -15
View File
@@ -3,6 +3,7 @@
* SPDX-License-Identifier: MIT
*/
#include "pipe/p_state.h"
#include "util/u_inlines.h"
#include "etnaviv_context.h"
@@ -473,7 +474,7 @@ etna_ml_lower_convolution(struct etna_ml_subgraph *subgraph,
operation->input_zero_point = etna_tensor_zero_point(poperation->input_tensors[0]);
operation->input_scale = poperation->input_tensors[0]->scale;
operation->output_tensor = poperation->output_tensors[0]->index;
operation->output_tensors[0] = poperation->output_tensors[0]->index;
operation->output_width = poperation->output_tensors[0]->dims[1];
operation->output_height = poperation->output_tensors[0]->dims[2];
operation->output_channels = poperation->output_tensors[0]->dims[3];
@@ -506,10 +507,14 @@ etna_ml_lower_convolution(struct etna_ml_subgraph *subgraph,
else if (operation->input_channels > 1)
transpose(subgraph, operation);
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
ML_DBG("%dx%dx%d\n", operation->input_width, operation->input_height, operation->input_channels);
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
}
static float
@@ -560,6 +565,7 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
assert(poperation->type == PIPE_ML_OPERATION_TYPE_ADD);
operation->type = ETNA_JOB_TYPE_NN;
operation->addition = true;
operation->depthwise = false;
operation->pointwise = false;
@@ -567,26 +573,33 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
operation->padding_same = false;
operation->stride = 1;
operation->input_tensors[0] = poperation->input_tensors[0]->index;
operation->input_tensors[1] = poperation->input_tensors[1]->index;
operation->input_count = 2;
operation->input_width = poperation->input_tensors[0]->dims[1];
operation->input_height = poperation->input_tensors[0]->dims[2];
operation->input_channels = poperation->input_tensors[0]->dims[3];
operation->input_zero_point = etna_tensor_zero_point(poperation->input_tensors[0]);
operation->input_scale = poperation->input_tensors[0]->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels *
2;
operation->output_tensor = poperation->output_tensors[0]->index;
operation->input_tensors[0] = poperation->input_tensors[0]->index;
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_tensors[1] = poperation->input_tensors[1]->index;
operation->input_tensor_sizes[1] = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_count = 2;
operation->output_tensors[0] = poperation->output_tensors[0]->index;
operation->output_width = poperation->output_tensors[0]->dims[1];
operation->output_height = poperation->output_tensors[0]->dims[2];
operation->output_channels = poperation->output_tensors[0]->dims[3];
operation->output_zero_point = etna_tensor_zero_point(poperation->output_tensors[0]);
operation->output_scale = poperation->output_tensors[0]->scale;
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
if (nn_core_version < 8) {
operation->weight_tensor = etna_ml_create_resource(context, 8);
operation->weight_width = 2;
@@ -807,8 +820,8 @@ create_nn_config(struct etna_ml_subgraph *subgraph, const struct etna_operation
}
}
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
offset = etna_ml_get_offset(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
offset = etna_ml_get_offset(subgraph, operation->output_tensors[0]);
map->out_image_address = etna_bo_gpu_va(etna_resource(output)->bo) + offset;
map->out_image_x_size = output_width;
map->out_image_y_size = output_height;
@@ -983,7 +996,7 @@ etna_ml_compile_operation_nn(struct etna_ml_subgraph *subgraph, const struct etn
assert(input);
pipe_resource_reference(&instruction->input, input);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
assert(output);
pipe_resource_reference(&instruction->output, output);
src/gallium/drivers/etnaviv/etnaviv_ml_tp.c
+32 -19
View File
@@ -266,8 +266,8 @@ create_transpose_config(struct etna_ml_subgraph *subgraph, const struct etna_ope
unsigned offset = etna_ml_get_offset(subgraph, operation->input_tensors[0]);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo) + offset;
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
offset = etna_ml_get_offset(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
offset = etna_ml_get_offset(subgraph, operation->output_tensors[0]);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo) + offset;
map->out_loop_1_inc = operation->input_width * operation->input_height;
@@ -316,8 +316,8 @@ create_detranspose_config(struct etna_ml_subgraph *subgraph, const struct etna_o
unsigned offset = etna_ml_get_offset(subgraph, operation->input_tensors[0]);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo) + offset;
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
offset = etna_ml_get_offset(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
offset = etna_ml_get_offset(subgraph, operation->output_tensors[0]);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo) + offset;
map->out_loop_0_inc = input_channels;
@@ -468,8 +468,8 @@ create_reshuffle_config(struct etna_ml_subgraph *subgraph, const struct etna_ope
unsigned offset = etna_ml_get_offset(subgraph, operation->input_tensors[0]);
map->in_image_base_address = etna_bo_gpu_va(etna_resource(input)->bo) + offset;
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
offset = etna_ml_get_offset(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
offset = etna_ml_get_offset(subgraph, operation->output_tensors[0]);
map->out_image_base_address = etna_bo_gpu_va(etna_resource(output)->bo) + offset;
for (unsigned i = 0; i < tp_core; i++) {
@@ -566,17 +566,20 @@ etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
operation->input_channels = input_tensor->dims[3];
operation->input_zero_point = etna_tensor_zero_point(input_tensor);
operation->input_scale = input_tensor->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
*output_tensor = etna_ml_allocate_tensor(subgraph);
operation->output_tensor = *output_tensor;
operation->output_tensors[0] = *output_tensor;
operation->output_width = operation->input_width;
operation->output_height = operation->input_height;
operation->output_channels = operation->input_channels;
operation->output_zero_point = operation->input_zero_point;
operation->output_scale = operation->input_scale;
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
}
void
@@ -594,16 +597,20 @@ etna_ml_lower_detranspose(struct etna_ml_subgraph *subgraph,
operation->input_channels = convolution->output_channels;
operation->input_zero_point = convolution->output_zero_point;
operation->input_scale = convolution->output_scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
operation->output_tensor = convolution->output_tensor;
operation->output_tensors[0] = convolution->output_tensors[0];
operation->output_count = 1;
operation->output_width = convolution->output_width;
operation->output_height = convolution->output_height;
operation->output_channels = convolution->output_channels;
operation->output_zero_point = convolution->output_zero_point;
operation->output_scale = convolution->output_scale;
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
}
void
@@ -624,17 +631,20 @@ etna_ml_lower_reshuffle(struct etna_ml_subgraph *subgraph,
operation->input_channels = convolution->input_tensors[0]->dims[3];
operation->input_zero_point = etna_tensor_zero_point(convolution->input_tensors[0]);
operation->input_scale = convolution->input_tensors[0]->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
operation->input_channels;
operation->input_tensor_sizes[0] = operation->input_width *
operation->input_height *
operation->input_channels;
*output_tensor = etna_ml_allocate_tensor(subgraph);
operation->output_tensor = *output_tensor;
operation->output_tensors[0] = *output_tensor;
operation->output_width = DIV_ROUND_UP(operation->input_width, operation->stride);
operation->output_height = DIV_ROUND_UP(operation->input_height, operation->stride);
operation->output_channels = operation->input_channels * operation->stride * operation->stride;
operation->output_zero_point = etna_tensor_zero_point(convolution->input_tensors[0]);
operation->output_scale = convolution->input_tensors[0]->scale;
operation->output_tensor_sizes[0] = operation->output_width *
operation->output_height *
operation->output_channels;
/* When destriding a convolution, the transformation to be made to the input
* tensor will depend on the size of the weight tensor.
@@ -663,10 +673,13 @@ etna_ml_compile_operation_tp(struct etna_ml_subgraph *subgraph,
assert(input);
pipe_resource_reference(&instruction->input, input);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensor);
struct pipe_resource *output = etna_ml_get_tensor(subgraph, operation->output_tensors[0]);
assert(output);
pipe_resource_reference(&instruction->output, output);
instruction->input_offset = etna_ml_get_offset(subgraph, operation->input_tensors[0]);
instruction->output_offset = etna_ml_get_offset(subgraph, operation->output_tensors[0]);
switch (operation->tp_type) {
case ETNA_ML_TP_TRANSPOSE:
instruction->configs[0] = create_transpose_config(subgraph, operation);