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Diffstat (limited to 'src/core/GLES_COMPUTE/cs_shaders/softmax_layer.cs')
-rw-r--r--src/core/GLES_COMPUTE/cs_shaders/softmax_layer.cs363
1 files changed, 0 insertions, 363 deletions
diff --git a/src/core/GLES_COMPUTE/cs_shaders/softmax_layer.cs b/src/core/GLES_COMPUTE/cs_shaders/softmax_layer.cs
deleted file mode 100644
index 696773653a..0000000000
--- a/src/core/GLES_COMPUTE/cs_shaders/softmax_layer.cs
+++ /dev/null
@@ -1,363 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-
-layout(local_size_x = LOCAL_SIZE_X, local_size_y = LOCAL_SIZE_Y, local_size_z = LOCAL_SIZE_Z) in;
-
-#include "helpers_cs.h"
-
-#if defined(DATA_TYPE_FP16)
-precision mediump float;
-#endif // DATA_TYPE_FP16
-
-// Common definitions
-#define MAX_OP(x, y) max((x), (y))
-#define ADD_OP(x, y) ((x) + (y))
-#define SUB_OP(x, y) ((x) - (y))
-#define DIV_OP(x, y) ((x) / (y))
-#define EXP_OP(x) exp((x))
-
-const float float_min = -1.0 / 0.0;
-const vec4 vec4_min = vec4(float_min);
-
-#ifdef SOFTMAX_LAYER_MAX
-
-/** Identifies the maximum value across the 1st dimension.
- *
- * @note The data type must be passed at compile time using "#define DATA_TYPE_NAME". e.g. "#define DATA_TYPE_FP32"
- * @note In case the input is not multiple of 8 NON_MULTIPLE_OF_8 must be passed.
- *
- * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32
- * @param[in] src_attrs The attributes of the source tensor
- * @param[out] dst_ptr Pointer to the destination tensor slice. Supported data types: same as @p src_ptr
- * @param[in] dst_attrs The attributes of the destination tensor
- * @param[in] width Input image width
- */
-SHADER_PARAMS_DECLARATION
-{
- Tensor3DAttributes src_attrs;
- Tensor3DAttributes dst_attrs;
- uint width;
-};
-
-#if defined(DATA_TYPE_FP32)
-
-TENSOR_DECLARATION(1, srcBuffer, vec4[2], src_ptr, src_shift, 5, readonly);
-TENSOR_DECLARATION(2, dstBuffer, float, dst_ptr, dst_shift, 2, writeonly);
-
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
-
- // Initialize local maximum
- vec4 max_val = vec4_min;
-
- // Calculate max of row
- uint width3 = width >> 3;
- for(int i = 0; i < int(width3); i++)
- {
- vec4 data[2] = LOAD(src_ptr, IMAGE_OFFSET(src_iter, i << 3, 0));
- max_val = MAX_OP(data[0], max_val);
- max_val = MAX_OP(data[1], max_val);
- }
-
-#ifdef NON_MULTIPLE_OF_8
- // Handle non multiple of 8
- vec4 data[2] = LOAD(src_ptr, IMAGE_OFFSET(src_iter, width3 << 3, 0));
- int idx = 0;
- if(width >> 2 != width3 << 1)
- {
- max_val = MAX_OP(data[0], max_val);
- idx = 1;
- }
- for(int i = 0; i < int(width) % 4; i++)
- {
- max_val.x = MAX_OP(data[idx][i], max_val.x);
- }
-#endif /* NON_MULTIPLE_OF_8 */
-
- // Perform max reduction
- max_val.xy = MAX_OP(max_val.xy, max_val.zw);
- max_val.x = MAX_OP(max_val.x, max_val.y);
-
- // Store result
- STORE_CURRENT_ITEM(dst_ptr, dst_iter, max_val.x);
-}
-#elif defined(DATA_TYPE_FP16)
-
-TENSOR_DECLARATION(1, srcBuffer, uvec4, src_ptr, src_shift, 4, readonly);
-TENSOR_DECLARATION(2, dstBuffer, uint, dst_ptr, dst_shift, 2, writeonly);
-
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
-
- // Initialize local maximum
- vec4 max_val = vec4_min;
-
- // Calculate max of row
- uint width3 = width >> 3;
- for(int i = 0; i < int(width3); i++)
- {
- vec4 data[2] = LOAD_UNPACK8_HALF(src_ptr, IMAGE_OFFSET(src_iter, i << 3, 0));
- max_val = MAX_OP(data[0], max_val);
- max_val = MAX_OP(data[1], max_val);
- }
-
-#ifdef NON_MULTIPLE_OF_8
- // Handle non multiple of 8
- vec4 data[2] = LOAD_UNPACK8_HALF(src_ptr, IMAGE_OFFSET(src_iter, width3 << 3, 0));
- int idx = 0;
- if(width >> 2 != width3 << 1)
- {
- max_val = MAX_OP(data[0], max_val);
- idx = 1;
- }
- for(int i = 0; i < int(width) % 4; i++)
- {
- max_val.x = MAX_OP(data[idx][i], max_val.x);
- }
-#endif /* NON_MULTIPLE_OF_8 */
-
- // Perform max reduction
- max_val.xy = MAX_OP(max_val.xy, max_val.zw);
- max_val.x = MAX_OP(max_val.x, max_val.y);
-
- STORE_PACK2_CURRENT_ITEM_HALF(dst_ptr, dst_iter, max_val.xy);
-}
-#else // DATA_TYPE_FP32
-#error Data type not supported
-#endif // DATA_TYPE_FP32
-#elif defined(SOFTMAX_LAYER_SHIFT_EXP_SUM)
-
-/** Shifts the values of the input tensor by the max calculated in softmax_layer_max kernel,
- * then gets the exponent of each element as sums all elements across each row.
- *
- * @note The data type must be passed at compile time using "#define DATA_TYPE_NAME". e.g. "#define DATA_TYPE_FP32"
- * @note In case the input is not multiple of 8 NON_MULTIPLE_OF_8 must be passed.
- *
- * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32
- * @param[in] src_attrs The attributes of the source tensor
- * @param[in] max_ptr Pointer to the max values tensor slice. Supported data types: same as @p src_ptr
- * @param[in] max_attrs The attributes of the max values tensor
- * @param[out] dst_ptr Pointer to the destination tensor slice. Supported data types: same as @p src_ptr
- * @param[in] dst_attrs The attributes of the destination tensor
- * @param[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr
- * @param[in] sum_attrs The attributes of the sum values tensor
- * @param[in] width Input image width
- */
-SHADER_PARAMS_DECLARATION
-{
- Tensor3DAttributes src_attrs;
- Tensor3DAttributes max_attrs;
- Tensor3DAttributes dst_attrs;
- Tensor3DAttributes sum_attrs;
- uint width;
-};
-#if defined(DATA_TYPE_FP32)
-
-TENSOR_DECLARATION(1, srcBuffer, vec4[2], src_ptr, src_shift, 5, readonly);
-TENSOR_DECLARATION(2, maxBuffer, float, max_ptr, max_shift, 2, readonly);
-TENSOR_DECLARATION(3, dstBuffer, vec4[2], dst_ptr, dst_shift, 5, writeonly);
-TENSOR_DECLARATION(4, sumBuffer, float, sum_ptr, sum_shift, 2, writeonly);
-
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
- ImageIterator max_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(max_attrs, max_shift);
- ImageIterator sum_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(sum_attrs, sum_shift);
-
- // Load max value of 1D logits vector (row)
- vec4 max_val = vec4(LOAD_CURRENT_ITEM(max_ptr, max_iter));
-
- // Set sum vector
- vec4 sum1D = vec4(0);
-
- // Shift values, exp and sum
- uint width3 = width >> 3;
- for(int i = 0; i < int(width3); i++)
- {
- vec4 data[2];
- data = LOAD(src_ptr, IMAGE_OFFSET(src_iter, i << 3, 0));
- data[0] = SUB_OP(data[0], max_val);
- data[1] = SUB_OP(data[1], max_val);
- data[0] = EXP_OP(data[0]);
- data[1] = EXP_OP(data[1]);
- STORE(dst_ptr, IMAGE_OFFSET(dst_iter, i << 3, 0), data);
- sum1D = ADD_OP(sum1D, data[0]);
- sum1D = ADD_OP(sum1D, data[1]);
- }
-
-#ifdef NON_MULTIPLE_OF_8
- // Handle non multiple of 8
- vec4 data[2] = LOAD(src_ptr, IMAGE_OFFSET(src_iter, width3 << 3, 0));
- int idx = 0;
- if(width >> 2 != width3 << 1)
- {
- data[0] = SUB_OP(data[0], max_val);
- data[0] = EXP_OP(data[0]);
- sum1D = ADD_OP(sum1D, data[0]);
- idx = 1;
- }
- for(int i = 0; i < int(width) % 4; i++)
- {
- data[idx][i] = SUB_OP(data[idx][i], max_val.x);
- data[idx][i] = EXP_OP(data[idx][i]);
- sum1D.x = ADD_OP(sum1D.x, data[idx][i]);
- }
- STORE(dst_ptr, IMAGE_OFFSET(dst_iter, width3 << 3, 0), data);
-#endif /* NON_MULTIPLE_OF_8 */
-
- // Perform min/max reduction
- sum1D.xy = ADD_OP(sum1D.xy, sum1D.zw);
- sum1D.x = ADD_OP(sum1D.x, sum1D.y);
-
- // Calculate and store result
- STORE_CURRENT_ITEM(sum_ptr, sum_iter, sum1D.x);
-}
-#elif defined(DATA_TYPE_FP16)
-
-TENSOR_DECLARATION(1, srcBuffer, uvec4, src_ptr, src_shift, 4, readonly);
-TENSOR_DECLARATION(2, maxBuffer, uint, max_ptr, max_shift, 2, readonly);
-TENSOR_DECLARATION(3, dstBuffer, uvec4, dst_ptr, dst_shift, 4, writeonly);
-TENSOR_DECLARATION(4, sumBuffer, uint, sum_ptr, sum_shift, 2, writeonly);
-
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
- ImageIterator max_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(max_attrs, max_shift);
- ImageIterator sum_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(sum_attrs, sum_shift);
-
- // Load max value of 1D logits vector (row)
- vec2 datamaxinit = LOAD_UNPACK2_CURRENT_ITEM_HALF(max_ptr, max_iter);
- vec4 max_val = vec4(datamaxinit.x);
-
- // Set sum vector
- vec4 sum1D = vec4(0.f);
-
- // Shift values, exp and sum
- uint width3 = width >> 3;
- for(int i = 0; i < int(width3); i++)
- {
- vec4 data[2] = LOAD_UNPACK8_HALF(src_ptr, IMAGE_OFFSET(src_iter, i << 3, 0));
- data[0] = SUB_OP(data[0], max_val);
- data[1] = SUB_OP(data[1], max_val);
- data[0] = EXP_OP(data[0]);
- data[1] = EXP_OP(data[1]);
- STORE_PACK8_HALF(dst_ptr, IMAGE_OFFSET(dst_iter, i << 3, 0), data);
- sum1D = ADD_OP(sum1D, data[0]);
- sum1D = ADD_OP(sum1D, data[1]);
- }
-
-#ifdef NON_MULTIPLE_OF_8
- // Handle non multiple of 8
- vec4 data[2] = LOAD_UNPACK8_HALF(src_ptr, IMAGE_OFFSET(src_iter, width3 << 3, 0));
- int idx = 0;
- if(width >> 2 != width3 << 1)
- {
- data[0] = SUB_OP(data[0], max_val);
- data[0] = EXP_OP(data[0]);
- sum1D = ADD_OP(sum1D, data[0]);
- idx = 1;
- }
- for(int i = 0; i < int(width) % 4; i++)
- {
- data[idx][i] = SUB_OP(data[idx][i], max_val.x);
- data[idx][i] = EXP_OP(data[idx][i]);
- sum1D.x = ADD_OP(sum1D.x, data[idx][i]);
- }
- STORE_PACK8_HALF(dst_ptr, IMAGE_OFFSET(dst_iter, width3 << 3, 0), data);
-#endif /* NON_MULTIPLE_OF_8 */
- // Perform min/max reduction
- sum1D.xy = ADD_OP(sum1D.xy, sum1D.zw);
- sum1D.x = ADD_OP(sum1D.x, sum1D.y);
-
- // Calculate and store result
- STORE_PACK2_CURRENT_ITEM_HALF(sum_ptr, sum_iter, sum1D.xy);
-}
-#else // DATA_TYPE_FP32
-#error Data type not supported
-#endif // DATA_TYPE_FP32
-#elif defined(SOFTMAX_LAYER_NORM)
-
-/** Divides all the values of the input tensor by the sum calculated from softmax_layer_shift_exp_sum kernel.
- *
- * @note The data type must be passed at compile time using "#define DATA_TYPE_NAME". e.g. "#define DATA_TYPE_FP32"
- *
- * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: F16/F32
- * @param[in] src_attrs The attributes of the source tensor
- * @param[in] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr
- * @param[in] sum_attrs The attributes of the sum values tensor
- * @param[out] dst_ptr Pointer to the destination tensor slice. Supported data types: same as @p src_ptr
- * @param[in] dst_attrs The attributes of the destination tensor
- */
-SHADER_PARAMS_DECLARATION
-{
- Tensor3DAttributes src_attrs;
- Tensor3DAttributes sum_attrs;
- Tensor3DAttributes dst_attrs;
-};
-#if defined(DATA_TYPE_FP32)
-TENSOR_DECLARATION(1, srcBuffer, vec4[2], src_ptr, src_shift, 5, readonly);
-TENSOR_DECLARATION(2, sumBuffer, float, sum_ptr, sum_shift, 2, readonly);
-TENSOR_DECLARATION(3, dstBuffer, vec4[2], dst_ptr, dst_shift, 5, writeonly);
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
- ImageIterator sum_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR_NO_STEP(sum_attrs, sum_shift);
-
- // Load max value of 1D logits vector (row)
- vec4 sum_val = vec4(LOAD(sum_ptr, IMAGE_OFFSET(sum_iter, 0, gl_GlobalInvocationID.y)));
-
- vec4 data[2] = LOAD_CURRENT_ITEM(src_ptr, src_iter);
- data[0] = DIV_OP(data[0], sum_val);
- data[1] = DIV_OP(data[1], sum_val);
- STORE_CURRENT_ITEM(dst_ptr, dst_iter, data);
-}
-#elif defined(DATA_TYPE_FP16)
-TENSOR_DECLARATION(1, srcBuffer, uvec4, src_ptr, src_shift, 4, readonly);
-TENSOR_DECLARATION(2, sumBuffer, uint, sum_ptr, sum_shift, 2, readonly);
-TENSOR_DECLARATION(3, dstBuffer, uvec4, dst_ptr, dst_shift, 4, writeonly);
-void main(void)
-{
- ImageIterator src_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(src_attrs, src_shift);
- ImageIterator dst_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR(dst_attrs, dst_shift);
- ImageIterator sum_iter = CONVERT_TENSOR3D_TO_IMAGE_ITERATOR_NO_STEP(sum_attrs, sum_shift);
-
- // Load max value of 1D logits vector (row)
- vec4 sum_val = vec4(LOAD_UNPACK2_HALF(sum_ptr, IMAGE_OFFSET(sum_iter, 0, gl_GlobalInvocationID.y)).x);
-
- vec4 data[2] = LOAD_UNPACK8_CURRENT_ITEM_HALF(src_ptr, src_iter);
- data[0] = DIV_OP(data[0], sum_val);
- data[1] = DIV_OP(data[1], sum_val);
- STORE_PACK8_CURRENT_ITEM_HALF(dst_ptr, dst_iter, data);
-}
-#else // DATA_TYPE_FP32
-#error Data type not supported
-#endif // DATA_TYPE_FP32
-#endif // SOFTMAX_LAYER_MAX
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