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etnaviv/nn: Add support for signed 8-bit tensors

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The hardware only supports unsigned 8-bit tensors, but with the
configurable zero point we can map signed 8-bit integers to unsigned
8-bit integers by adding a constant offset of 128 to all values and to
the zero point setting.

This requires adding 128 to all input tensors and subtracting 128
from all output tensors during inference.

Reviewed-by: Tomeu Vizoso <tomeu@tomeuvizoso.net>
Signed-off-by: Philipp Zabel <p.zabel@pengutronix.de>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/31979>
This commit is contained in:
Philipp Zabel 2024-09-19 16:15:36 +02:00
parent f9c34a3eb0
commit 4153154423
5 changed files with 99 additions and 17 deletions
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31
src/gallium/drivers/etnaviv/etnaviv_ml.c
View file

@ -542,7 +542,19 @@ etna_ml_subgraph_invoke(struct pipe_context *pctx, struct pipe_ml_subgraph *psub
for (int i = 0; i < inputs_count; i++) {
struct pipe_resource *res = etna_ml_get_tensor(subgraph, input_idxs[i]);
pipe_buffer_write(pctx, res, offsets[input_idxs[i]], sizes[input_idxs[i]], inputs[i]);
if (is_signed[i]) {
struct pipe_transfer *dst_transfer;
const uint8_t *src = inputs[i];
uint8_t *dst_map;
dst_map = pipe_buffer_map_range(pctx, res, 0, sizes[input_idxs[i]], PIPE_MAP_WRITE, &dst_transfer);
assert(dst_map);
for (unsigned k = 0; k < sizes[input_idxs[i]]; k++) {
dst_map[k] = src[k] + 128;
}
pipe_buffer_unmap(pctx, dst_transfer);
} else {
pipe_buffer_write(pctx, res, offsets[input_idxs[i]], sizes[input_idxs[i]], inputs[i]);
}
}
unsigned i = 0;
@ -662,7 +674,22 @@ etna_ml_subgraph_read_outputs(struct pipe_context *context, struct pipe_ml_subgr
for (int i = 0; i < outputs_count; i++) {
struct pipe_resource *res = etna_ml_get_tensor(subgraph, output_idxs[i]);
pipe_buffer_read(context, res, 0, pipe_buffer_size(res), outputs[i]);
if (is_signed[i]) {
struct pipe_transfer *src_transfer;
uint8_t *src_map;
src_map = (uint8_t *) pipe_buffer_map_range(context,
res,
0, pipe_buffer_size(res),
PIPE_MAP_READ,
&src_transfer);
assert(src_map);
for (unsigned k = 0; k < pipe_buffer_size(res); k++) {
((uint8_t *)(outputs[i]))[k] = src_map[k] - 128;
}
pipe_buffer_unmap(context, src_transfer);
} else {
pipe_buffer_read(context, res, 0, pipe_buffer_size(res), outputs[i]);
}
}
}

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

@ -94,6 +94,7 @@ struct etna_operation {
unsigned weight_height;
uint8_t weight_zero_point;
float weight_scale;
bool weight_signed;
uint8_t addition_offset;

49
src/gallium/drivers/etnaviv/etnaviv_ml_nn.c
View file

@ -199,9 +199,15 @@ pointwise_to_2x2(struct etna_ml_subgraph *subgraph, struct etna_operation *opera
uint8_t *map_out = output + channel * 2 * 2 * operation->input_channels;
map_out[0] = map_in[0];
map_out[1] = operation->weight_zero_point;
map_out[2] = operation->weight_zero_point;
map_out[3] = operation->weight_zero_point;
if (operation->weight_signed) {
map_out[1] = operation->weight_zero_point - 128;
map_out[2] = operation->weight_zero_point - 128;
map_out[3] = operation->weight_zero_point - 128;
} else {
map_out[1] = operation->weight_zero_point;
map_out[2] = operation->weight_zero_point;
map_out[3] = operation->weight_zero_point;
}
}
pipe_resource_reference(&operation->weight_tensor, NULL);
@ -231,6 +237,8 @@ expand_depthwise(struct etna_ml_subgraph *subgraph, struct etna_operation *opera
for (unsigned i = 0; i < operation->weight_width * operation->weight_height * operation->input_channels; i++) {
if (i % operation->input_channels == in_depth)
map_out[i] = map_in[i];
else if (operation->weight_signed)
map_out[i] = operation->weight_zero_point - 128;
else
map_out[i] = operation->weight_zero_point;
}
@ -380,7 +388,8 @@ strided_to_normal(struct etna_ml_subgraph *subgraph, struct etna_operation *oper
output = map_resource(output_res);
unsigned wdims_out[4] = {operation->output_channels, operation->weight_width, operation->weight_height, operation->input_channels};
reshape(input, output, operation->stride, operation->weight_zero_point, wdims_in, wdims_out);
int weight_zero_point = operation->weight_signed ? (operation->weight_zero_point - 128) : operation->weight_zero_point;
reshape(input, output, operation->stride, weight_zero_point, wdims_in, wdims_out);
pipe_resource_reference(&operation->weight_tensor, NULL);
operation->weight_tensor = output_res;
@ -415,6 +424,25 @@ calc_pooling_first_pixel(struct etna_ml_subgraph *subgraph,
return false;
}
static inline uint8_t
etna_tensor_zero_point(struct pipe_tensor *tensor)
{
if (tensor->is_signed) {
/*
* Since the hardware only supports unsigned 8-bit integers, signed
* tensors are shifted from the -128..127 range to 0..255 by adding 128
* when uploading and subtracting 128 when downloading the tensor.
* Tensor zero point and weight coefficients have to be adapted to
* account for this.
*/
assert(tensor->zero_point >= -128 && tensor->zero_point <= 127);
return tensor->zero_point + 128;
} else {
assert(tensor->zero_point >= 0 && tensor->zero_point <= 255);
return tensor->zero_point;
}
}
void
etna_ml_lower_convolution(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *poperation,
@ -442,21 +470,22 @@ etna_ml_lower_convolution(struct etna_ml_subgraph *subgraph,
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 = poperation->input_tensors[0]->zero_point;
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_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 = poperation->output_tensors[0]->zero_point;
operation->output_zero_point = etna_tensor_zero_point(poperation->output_tensors[0]);
operation->output_scale = poperation->output_tensors[0]->scale;
pipe_resource_reference(&operation->weight_tensor, poperation->conv.weight_tensor->resource);
operation->weight_width = poperation->conv.weight_tensor->dims[1];
operation->weight_height = poperation->conv.weight_tensor->dims[2];
operation->weight_zero_point = poperation->conv.weight_tensor->zero_point;
operation->weight_zero_point = etna_tensor_zero_point(poperation->conv.weight_tensor);
operation->weight_scale = poperation->conv.weight_tensor->scale;
operation->weight_signed = poperation->conv.weight_tensor->is_signed;
pipe_resource_reference(&operation->bias_tensor, poperation->conv.bias_tensor->resource);
@ -544,7 +573,7 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
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 = poperation->input_tensors[0]->zero_point;
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 *
@ -555,7 +584,7 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
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 = poperation->output_tensors[0]->zero_point;
operation->output_zero_point = etna_tensor_zero_point(poperation->output_tensors[0]);
operation->output_scale = poperation->output_tensors[0]->scale;
if (nn_core_version < 8) {
@ -564,6 +593,7 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
operation->weight_height = 2;
operation->weight_zero_point = 0x0;
operation->weight_scale = compute_weight_scale_add(poperation->input_tensors[1]->scale, poperation->input_tensors[0]->scale);
operation->weight_signed = false;
operation->addition_offset = compute_addition_offset(poperation->input_tensors[1]->scale, poperation->input_tensors[0]->scale, operation->weight_scale);
uint8_t *weight_map = map_resource(operation->weight_tensor);
@ -582,6 +612,7 @@ etna_ml_lower_add(struct etna_ml_subgraph *subgraph,
operation->weight_height = 1;
operation->weight_zero_point = 0x0;
operation->weight_scale = compute_weight_scale_add(poperation->input_tensors[1]->scale, poperation->input_tensors[0]->scale);
operation->weight_signed = false;
operation->addition_offset = compute_addition_offset(poperation->input_tensors[1]->scale, poperation->input_tensors[0]->scale, operation->weight_scale);
uint8_t (*weight_map)[operation->input_channels] = map_resource(operation->weight_tensor);

15
src/gallium/drivers/etnaviv/etnaviv_ml_nn_v8.c
View file

@ -192,8 +192,17 @@ static uint32_t calculate_bias_correction(struct etna_ml_subgraph *subgraph, con
else
input_channels = operation->input_channels;
for (unsigned i = 0; i < operation->weight_width * operation->weight_height * input_channels; i++) {
correction += (weights[i] - operation->weight_zero_point) * input_zero_point;
if (operation->weight_signed) {
/* See etna_tensor_zero_point() */
int8_t weight_zero_point = operation->weight_zero_point - 128;
for (unsigned i = 0; i < operation->weight_width * operation->weight_height * input_channels; i++) {
correction += (((int8_t *)weights)[i] - weight_zero_point) * input_zero_point;
}
} else {
for (unsigned i = 0; i < operation->weight_width * operation->weight_height * input_channels; i++) {
correction += (weights[i] - operation->weight_zero_point) * input_zero_point;
}
}
return correction;
@ -652,6 +661,8 @@ static void encode_superblock(struct etna_ml_subgraph *subgraph, const struct et
if (kernel_idx + block * block_size >= kernel_size)
weight = operation->weight_zero_point;
else if (operation->weight_signed)
weight = ((int8_t *)(weights_map[oc]))[kernel_idx + block * block_size] + 128;
else
weight = weights_map[oc][kernel_idx + block * block_size];

20
src/gallium/drivers/etnaviv/etnaviv_ml_tp.c
View file

@ -535,6 +535,18 @@ create_reshuffle_config(struct etna_ml_subgraph *subgraph, const struct etna_ope
return bo;
}
static inline uint8_t
etna_tensor_zero_point(struct pipe_tensor *tensor)
{
if (tensor->is_signed) {
assert(tensor->zero_point >= -128 && tensor->zero_point <= 127);
return tensor->zero_point + 128;
} else {
assert(tensor->zero_point >= 0 && tensor->zero_point <= 255);
return tensor->zero_point;
}
}
void
etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
const struct pipe_ml_operation *first_operation,
@ -548,7 +560,7 @@ etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
operation->input_width = first_operation->input_tensors[0]->dims[1];
operation->input_height = first_operation->input_tensors[0]->dims[2];
operation->input_channels = first_operation->input_tensors[0]->dims[3];
operation->input_zero_point = first_operation->input_tensors[0]->zero_point;
operation->input_zero_point = etna_tensor_zero_point(first_operation->input_tensors[0]);
operation->input_scale = first_operation->input_tensors[0]->scale;
operation->input_tensor_size = operation->input_width *
operation->input_height *
@ -559,7 +571,7 @@ etna_ml_lower_transpose(struct etna_ml_subgraph *subgraph,
operation->output_width = first_operation->input_tensors[0]->dims[1];
operation->output_height = first_operation->input_tensors[0]->dims[2];
operation->output_channels = first_operation->input_tensors[0]->dims[3];
operation->output_zero_point = first_operation->input_tensors[0]->zero_point;
operation->output_zero_point = etna_tensor_zero_point(first_operation->input_tensors[0]);
operation->output_scale = first_operation->input_tensors[0]->scale;
}
@ -606,7 +618,7 @@ etna_ml_lower_reshuffle(struct etna_ml_subgraph *subgraph,
operation->input_width = convolution->input_tensors[0]->dims[1];
operation->input_height = convolution->input_tensors[0]->dims[2];
operation->input_channels = convolution->input_tensors[0]->dims[3];
operation->input_zero_point = convolution->input_tensors[0]->zero_point;
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 *
@ -617,7 +629,7 @@ etna_ml_lower_reshuffle(struct etna_ml_subgraph *subgraph,
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 = convolution->input_tensors[0]->zero_point;
operation->output_zero_point = etna_tensor_zero_point(convolution->input_tensors[0]);
operation->output_scale = convolution->input_tensors[0]->scale;
/* When destriding a convolution, the transformation to be made to the input