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teflon: Support fused ReLU6 activation via output saturation

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If the output tensor quantization range does not exceed 6.0, ReLU6 can
be replaced with ReLU: output values larger than 6.0 are clipped by
output saturation.

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/32388>
This commit is contained in:
Philipp Zabel
2024-11-27 10:05:49 +01:00
committed by Marge Bot
parent 6370acbead
commit dddec9a66d
1 changed files with 52 additions and 8 deletions
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src/gallium/frontends/teflon/tfl_device.c
+52 -8
View File
@@ -116,7 +116,8 @@ fill_operation(struct teflon_delegate *delegate, TfLiteContext *tf_context, TfLi
TfLiteConvParams* params = (TfLiteConvParams*)node->builtin_data;
assert(params->activation == kTfLiteActNone ||
params->activation == kTfLiteActRelu);
params->activation == kTfLiteActRelu ||
params->activation == kTfLiteActRelu6);
if (node_registration->version >= 2) {
assert(params->dilation_width_factor == 1);
assert(params->dilation_height_factor == 1);
@@ -125,12 +126,14 @@ fill_operation(struct teflon_delegate *delegate, TfLiteContext *tf_context, TfLi
operation->conv.stride_y = params->stride_height;
operation->conv.padding_same = params->padding == kTfLitePaddingSame;
operation->conv.depthwise = false;
operation->conv.relu = params->activation == kTfLiteActRelu;
operation->conv.relu = params->activation == kTfLiteActRelu ||
params->activation == kTfLiteActRelu6;
} else {
TfLiteDepthwiseConvParams* params = (TfLiteDepthwiseConvParams*)node->builtin_data;
assert(params->activation == kTfLiteActNone ||
params->activation == kTfLiteActRelu);
params->activation == kTfLiteActRelu ||
params->activation == kTfLiteActRelu6);
if (node_registration->version >= 2) {
assert(params->dilation_width_factor == 1);
assert(params->dilation_height_factor == 1);
@@ -139,7 +142,8 @@ fill_operation(struct teflon_delegate *delegate, TfLiteContext *tf_context, TfLi
operation->conv.stride_y = params->stride_height;
operation->conv.padding_same = params->padding == kTfLitePaddingSame;
operation->conv.depthwise = true;
operation->conv.relu = params->activation == kTfLiteActRelu;
operation->conv.relu = params->activation == kTfLiteActRelu ||
params->activation == kTfLiteActRelu6;
}
operation->conv.pointwise = operation->conv.weight_tensor->dims[1] == 1 && \
operation->conv.weight_tensor->dims[2] == 1;
@@ -405,6 +409,48 @@ tensor_quantization_supported(TfLiteTensor *tensor)
return false;
}
static bool
fused_relu6_supported(TfLiteTensor *tensor)
{
TfLiteAffineQuantization *affine;
int quantized_max;
switch (tensor->type) {
case kTfLiteInt8:
quantized_max = INT8_MAX;
break;
case kTfLiteUInt8:
quantized_max = UINT8_MAX;
break;
default:
return false;
}
assert(tensor->quantization.type == kTfLiteAffineQuantization);
affine = (TfLiteAffineQuantization *)tensor->quantization.params;
assert(affine->scale->size == affine->zero_point->size);
for (int i = 0; i < affine->zero_point->size; i++) {
if ((quantized_max - affine->zero_point->data[i]) * affine->scale->data[i] > 6.0f)
return false;
}
return true;
}
static bool
fused_activation_supported(TfLiteFusedActivation activation, TfLiteTensor *tensor)
{
switch (activation) {
case kTfLiteActNone:
case kTfLiteActRelu:
return true;
case kTfLiteActRelu6:
return fused_relu6_supported(tensor);
default:
return false;
}
}
static TfLiteStatus
PrepareDelegate(TfLiteContext *context, TfLiteDelegate *delegate)
{
@@ -436,8 +482,7 @@ PrepareDelegate(TfLiteContext *context, TfLiteDelegate *delegate)
tensor_quantization_supported(weight_tensor) &&
tensor_quantization_supported(bias_tensor) &&
tensor_quantization_supported(output_tensor) &&
(params->activation == kTfLiteActNone ||
params->activation == kTfLiteActRelu) &&
fused_activation_supported(params->activation, output_tensor) &&
(registration->version < 2 ||
(params->dilation_width_factor == 1 &&
params->dilation_height_factor == 1))) {
@@ -457,8 +502,7 @@ PrepareDelegate(TfLiteContext *context, TfLiteDelegate *delegate)
tensor_quantization_supported(weight_tensor) &&
tensor_quantization_supported(bias_tensor) &&
tensor_quantization_supported(output_tensor) &&
(params->activation == kTfLiteActNone ||
params->activation == kTfLiteActRelu) &&
fused_activation_supported(params->activation, output_tensor) &&
(registration->version < 2 ||
(params->dilation_width_factor == 1 &&
params->dilation_height_factor == 1))) {