NEQLSTM: Add support for QASYMM8_SIGNED for input_to_forget_weights
* QLSTM only supports QSYMM8 for the argument input_to_forget_weights
* We add support for QASYMM8_SIGNED by dequantizing and requantizing to QSYMM8
* Resolves COMPMID-5184
Change-Id: I1cae18d81dafdb7ae722b520a1354cf4a56b9606
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7321
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
(cherry picked from commit 187a041dedf8e9db0c9e0652f13f8639dca880f3)
diff --git a/src/cpu/kernels/CpuQuantizeKernel.cpp b/src/cpu/kernels/CpuQuantizeKernel.cpp
index ecae5e7..9700c62 100644
--- a/src/cpu/kernels/CpuQuantizeKernel.cpp
+++ b/src/cpu/kernels/CpuQuantizeKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2021 Arm Limited.
+ * Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -55,7 +55,7 @@
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QASYMM16);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::QSYMM8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QASYMM16);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
return Status{};
@@ -123,6 +123,8 @@
{ "op_QASYMM8_SIGNED_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<int8_t, int8_t> },
{ "op_QASYMM8_SIGNED_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<int8_t> },
+ { "op_F32_QSYMM8", &CpuQuantizeKernel::run_quantize_qsymm8<float, int8_t> },
+
{ "op_F32_QASYMM8", &CpuQuantizeKernel::run_quantize_qasymm8<float, uint8_t> },
{ "op_F32_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<float, int8_t> },
{ "op_F32_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<float> },
@@ -158,6 +160,42 @@
}
template <typename TIn, typename TOut>
+void CpuQuantizeKernel::run_quantize_qsymm8(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ if(is_data_type_quantized_asymmetric(src->info()->data_type()))
+ {
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+ }
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(win_collapsed, [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const TIn *>(input.ptr());
+ auto output_ptr = reinterpret_cast<TOut *>(output.ptr());
+ int x = window_start_x;
+ for(; x <= (window_end_x - window_step); x += window_step)
+ {
+ wrapper::vstore(&output_ptr[x], vquantize_qasymm8<TOut>(load_value(&input_ptr[x]), uqinfo));
+ }
+ // Compute left-over elements
+ for(; x < window_end_x; ++x)
+ {
+ output_ptr[x] = quantize_qsymm8(input_ptr[x], dst->info()->quantization_info());
+ }
+ },
+ input, output);
+}
+
+template <typename TIn, typename TOut>
void CpuQuantizeKernel::run_quantize_qasymm8(const ITensor *src, ITensor *dst, const Window &window)
{
const auto window_start_x = static_cast<int>(window.x().start());
@@ -263,4 +301,4 @@
}
} // namespace kernels
} // namespace cpu
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute