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teflon/tests: prep test executor for signed convolutions

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Subtract 128 from the input and output tensor zero points, to keep
them in int8_t range (conv2d.tflite is set up for uint8_t).

Set weight tensor zero point to zero, as required by TensorFlow Lite
for int8_t weight tensors.

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 2024-10-09 17:20:16 +02:00
parent 4153154423
commit 563316417a
1 changed files with 12 additions and 2 deletions
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14
src/gallium/targets/teflon/test_executor.cpp
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@ -99,6 +99,8 @@ patch_conv2d(unsigned operation_index,
input_tensor->shape.data()[2] = input_size;
input_tensor->shape.data()[3] = input_channels;
input_tensor->type = is_signed ? tflite::TensorType_INT8 : tflite::TensorType_UINT8;
if (is_signed)
input_tensor->quantization->zero_point[0] -= 128;
/* Bias */
auto bias_tensor = subgraph->tensors[bias_index];
@ -125,6 +127,8 @@ patch_conv2d(unsigned operation_index,
weight_tensor->shape.data()[3] = input_channels;
}
weight_tensor->type = is_signed ? tflite::TensorType_INT8 : tflite::TensorType_UINT8;
if (is_signed)
weight_tensor->quantization->zero_point[0] = 0;
auto weights_data = &model->buffers[weights_buffer_index]->data;
std::vector<int> weight_shape;
@ -149,6 +153,8 @@ patch_conv2d(unsigned operation_index,
output_tensor->shape.data()[2] = output_size;
output_tensor->shape.data()[3] = output_channels;
output_tensor->type = is_signed ? tflite::TensorType_INT8 : tflite::TensorType_UINT8;
if (is_signed)
output_tensor->quantization->zero_point[0] -= 128;
}
std::vector<uint8_t>
@ -173,7 +179,7 @@ conv2d_generate_model(int input_size,
}
static void
patch_quant_for_add(tflite::ModelT *model)
patch_quant_for_add(tflite::ModelT *model, bool is_signed)
{
auto subgraph = model->subgraphs[0];
auto add_op = subgraph->operators[2];
@ -182,11 +188,15 @@ patch_quant_for_add(tflite::ModelT *model)
auto input_tensor = subgraph->tensors[input_index];
input_tensor->quantization->scale[0] = randf(0.0078125, 0.4386410117149353);
input_tensor->quantization->zero_point[0] = rand() % 255;
if (is_signed)
input_tensor->quantization->zero_point[0] -= 128;
input_index = add_op->inputs.data()[1];
input_tensor = subgraph->tensors[input_index];
input_tensor->quantization->scale[0] = randf(0.0078125, 0.4386410117149353);
input_tensor->quantization->zero_point[0] = rand() % 255;
if (is_signed)
input_tensor->quantization->zero_point[0] -= 128;
}
std::vector<uint8_t>
@ -204,7 +214,7 @@ add_generate_model(int input_size,
patch_conv2d(0, &model, input_size, weight_size, input_channels, output_channels, stride, padding_same, is_signed, depthwise);
patch_conv2d(1, &model, input_size, weight_size, input_channels, output_channels, stride, padding_same, is_signed, depthwise);
patch_quant_for_add(&model);
patch_quant_for_add(&model, is_signed);
/* Output */
auto subgraph = model.subgraphs[0];