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+/*
+ * Copyright (c) 2019-2022 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "helpers.h"
+
+#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(EPSILON) && defined(WIDTH)
+/** This function normalizes the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension.
+ *
+ * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
+ * @attention Data type should be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
+ * @attention Width of the input tensor should be passed using the -DWIDTH compile flag, e.g. -DWIDTH=16
+ * @attention Normalization epsilon parameter should be given as a preprocessor argument with -DEPSILON=value. e.g. -DEPSILON=0.001f
+ *
+ * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32
+ * @param[in] input_stride_x Stride of the first 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 first source tensor in Y dimension (in bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor
+ * @param[out] output_ptr (Optional) Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in] output_stride_x (Optional) Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] output_step_x (Optional) output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] output_stride_y (Optional) Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] output_step_y (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination tensor
+ */
+__kernel void mean_stddev_normalization(
+ IMAGE_DECLARATION(input)
+#ifndef IN_PLACE
+ ,
+ IMAGE_DECLARATION(output)
+#endif /* IN_PLACE */
+)
+{
+ // Get pixels pointer
+ Image in = CONVERT_TO_IMAGE_STRUCT(input);
+#ifdef IN_PLACE
+ Image out = in;
+#else /* IN_PLACE */
+ Image out = CONVERT_TO_IMAGE_STRUCT(output);
+#endif /* IN_PLACE */
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ sum = 0.f;
+#ifdef MEANSTDNORM_HALF
+ VEC_DATA_TYPE(float, VEC_SIZE)
+#else /* MEANSTDNORM_HALF */
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+#endif /* MEANSTDNORM_HALF */
+ sum_sq = 0.f;
+ // Calculate partial sum
+ int i = 0;
+ for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE)
+ {
+ // Load data
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&in, i, 0));
+
+ sum += data;
+#ifdef MEANSTDNORM_HALF
+ VEC_DATA_TYPE(float, VEC_SIZE)
+ dsq = CONVERT(data * data, VEC_DATA_TYPE(float, VEC_SIZE));
+ sum_sq += dsq;
+#else /* MEANSTDNORM_HALF */
+ sum_sq += data * data;
+#endif /* MEANSTDNORM_HALF */
+ }
+ // Perform reduction
+ sum = SUM_REDUCE(sum, VEC_SIZE);
+ sum_sq = SUM_REDUCE(sum_sq, VEC_SIZE);
+
+#if VEC_SIZE > 1
+#define sum sum.s0
+#define sum_sq sum_sq.s0
+#endif // VEC_SIZE > 1
+
+ // Left-overs loop
+ for(; i < WIDTH; ++i)
+ {
+ DATA_TYPE data = *((__global DATA_TYPE *)offset(&in, i, 0));
+
+ sum += data;
+ sum_sq += data * data;
+ }
+
+ DATA_TYPE mean = sum / WIDTH;
+ DATA_TYPE var = (sum_sq / WIDTH) - (mean * mean);
+ DATA_TYPE stddev_inv = 1.f / sqrt(var + EPSILON);
+
+ i = 0;
+ for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE)
+ {
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&in, i, 0));
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ res = (data - mean) * stddev_inv;
+ VSTORE(VEC_SIZE)
+ (res, 0, (__global DATA_TYPE *)offset(&out, i, 0));
+ }
+ for(; i < WIDTH; ++i)
+ {
+ DATA_TYPE data = *((__global DATA_TYPE *)offset(&in, i, 0));
+
+ *((__global DATA_TYPE *)offset(&out, i, 0)) = (data - mean) * stddev_inv;
+ }
+}
+#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(EPSILON) && defined(WIDTH) */