COMPMID-3046: Add CLRequantizationLayerKernel
Change-Id: I034f5aa023642f2323372495ddd14fc62b4c12e0
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2681
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/quantization_layer.cl b/src/core/CL/cl_kernels/quantization_layer.cl
index 41d9957..cfb2bb6 100644
--- a/src/core/CL/cl_kernels/quantization_layer.cl
+++ b/src/core/CL/cl_kernels/quantization_layer.cl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -29,7 +29,7 @@
#if defined(VEC_SIZE) && defined(DATA_TYPE_IN) && defined(DATA_TYPE_OUT) && defined(SCALE) && defined(OFFSET) && defined(MIN_QUANT_VAL) && defined(MAX_QUANT_VAL)
-/** This performs the quantization of floating point inputs to 8-bit unsigned integers.
+/** This performs the quantization of floating point inputs or 8-bit quantized integers to 8-bit integers.
*
* @note Input data type should be given as a preprocessor argument using -DDATA_TYPE_IN=type. e.g. -DDATA_TYPE=short
* @note Output data type should be given as a preprocessor argument using -DDATA_TYPE_OUT=type. e.g. -DDATA_TYPE=short
@@ -38,8 +38,9 @@
* @note Quantization offset should be given as a preprocessor argument using -DOFFSET=offset. e.g. -DOFFSET=125
* @note Minimum value for quantized type should be given as a preprocessor argument using -DMIN_QUANT_VAL=value. e.g. -DMIN_QUANT_VAL=0
* @note Maximum value for quantized type should be given as a preprocessor argument using -DMAX_QUANT_VAL=value. e.g. -DMAXIN_QUANT_VAL=255
+ * @note If the input data type if a floating point (F16 or F32) the preprocessor argument should be give as -DIS_FLOAT
*
- * @param[in] input_ptr Pointer to the source tensor. Supported data types: F32
+ * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/F16/F32
* @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)
* @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes)
@@ -47,7 +48,7 @@
* @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor
- * @param[out] output_ptr Pointer to the destination tensor. Supported data types: U8
+ * @param[out] output_ptr Pointer to the destination tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
* @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
@@ -72,16 +73,30 @@
output.ptr -= max(xi - (int)LAST_ACCESSED_X, 0) * output_stride_x;
// Load data
+#if defined(IS_FLOAT)
+ // Load data
VEC_DATA_TYPE(DATA_TYPE_IN, VEC_SIZE)
- val = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE_IN *)input.ptr);
+ val_float = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE_IN *)input.ptr);
// Create scale and offset vectors
const VEC_DATA_TYPE(DATA_TYPE_IN, VEC_SIZE) vscale = SCALE;
- const VEC_DATA_TYPE(int, VEC_SIZE) voffset = OFFSET;
+ const VEC_DATA_TYPE(int, VEC_SIZE) voffset = OFFSET;
+#else // defined(IS_FLOAT)
+ // Load data
+ VEC_DATA_TYPE(DATA_TYPE_IN, VEC_SIZE)
+ val = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE_IN *)input.ptr);
+
+ const VEC_DATA_TYPE(float, VEC_SIZE)
+ val_float = CONVERT(val, VEC_DATA_TYPE(float, VEC_SIZE));
+
+ // Create scale and offset vectors
+ const VEC_DATA_TYPE(float, VEC_SIZE) vscale = SCALE;
+ const VEC_DATA_TYPE(int, VEC_SIZE) voffset = OFFSET;
+#endif // defined(IS_FLOAT)
// Quantize
VEC_DATA_TYPE(int, VEC_SIZE)
- res = CLAMP(CONVERT_RTE_VEC(val / vscale, int, VEC_SIZE) + voffset, MIN_QUANT_VAL, MAX_QUANT_VAL);
+ res = CLAMP(CONVERT_RTE_VEC(val_float / vscale, int, VEC_SIZE) + voffset, MIN_QUANT_VAL, MAX_QUANT_VAL);
// Store result
VSTORE(VEC_SIZE)
@@ -90,4 +105,4 @@
*((__global DATA_TYPE_OUT *)(output.ptr)) = (DATA_TYPE_OUT)CLAMP(CONVERT_RTE(((float) * (__global DATA_TYPE_IN *)input.ptr) / ((float)SCALE), int) + (int)OFFSET, MIN_QUANT_VAL, MAX_QUANT_VAL);
#endif // defined(VEC_SIZE) && defined(LAST_ACCESSED_X)
}
-#endif //defined(VEC_SIZE) && defined(DATA_TYPE_IN) && defined(DATA_TYPE_OUT) && defined(SCALE) && defined(OFFSET) && defined(MIN_QUANT_VAL) && defined(MAX_QUANT_VAL)
+#endif // defined(VEC_SIZE) && defined(DATA_TYPE_IN) && defined(DATA_TYPE_OUT) && defined(SCALE) && defined(OFFSET) && defined(MIN_QUANT_VAL) && defined(MAX_QUANT_VAL)
diff --git a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp b/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
index 3d7aff0..ab3b5d2 100644
--- a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
@@ -41,7 +41,7 @@
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F32, DataType::F16);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
// Output must always be initialized
@@ -62,8 +62,7 @@
const bool multi_access_x = (input_width_x / vec_size_x > 0);
if(multi_access_x)
{
- win.set(Window::DimX,
- Window::Dimension(win.x().start(), ceil_to_multiple(win.x().end(), vec_size_x), vec_size_x));
+ win.set(Window::DimX, Window::Dimension(win.x().start(), ceil_to_multiple(win.x().end(), vec_size_x), vec_size_x));
}
Coordinates coord;
@@ -99,10 +98,53 @@
const UniformQuantizationInfo qinfo = output->info()->quantization_info().uniform();
const DataType output_data_type = output->info()->data_type();
+ float scale_to_apply = qinfo.scale;
+ int32_t offset_to_apply = qinfo.offset;
+ if(is_data_type_quantized_asymmetric(_input->info()->data_type()))
+ {
+ /*
+ * In case of requantization of a quantized input tensor to an output tensor with another quantization
+ * instead of of apply dequantization and then a quantization functions, we just compute new scale and
+ * offset to apply.
+ *
+ * Assuming:
+ * - q_i as input quantized value
+ * - q_o as output quantized value
+ * - z_i as input quantization offset value
+ * - z_o as output quantization offset value
+ * - s_i as input quantization scale value
+ * - s_o as output quantization scale value
+ * - z_n as new quantization offset value
+ * - s_n as new quantization scale value
+ *
+ * q_o = ( q_i - z_i ) * s_i / s_o + z_o
+ *
+ * We can rewrite the formula as:
+ *
+ * q_o = ( q_i * s_i / s_o ) - z_i * s_i / s_o + z_o
+ *
+ * q_o = q_i / s_n + z_n
+ *
+ * Where:
+ *
+ * s_n = s_o / s_i
+ *
+ * z_n = - z_i * s_i / s_o + z_o
+ *
+ */
+ const UniformQuantizationInfo qinfo_in = _input->info()->quantization_info().uniform();
+ scale_to_apply /= qinfo_in.scale;
+ // In order to minimize flooring we convert the offset to a float,
+ // then compute the new offset in the float domain,
+ // finally we convert it back as int32_t
+ offset_to_apply -= static_cast<int32_t>(static_cast<float>(qinfo_in.offset) * qinfo_in.scale / qinfo.scale);
+ }
+
// Create kernel
CLBuildOptions build_opts;
- build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(qinfo.scale));
- build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(qinfo.offset));
+ build_opts.add_option_if(is_data_type_float(_input->info()->data_type()), "-DIS_FLOAT");
+ build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(scale_to_apply));
+ build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(offset_to_apply));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x));
build_opts.add_option("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output_data_type));