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-rw-r--r--src/cpu/kernels/CpuIm2ColKernel.cpp569
1 files changed, 210 insertions, 359 deletions
diff --git a/src/cpu/kernels/CpuIm2ColKernel.cpp b/src/cpu/kernels/CpuIm2ColKernel.cpp
index 55ac7c5192..39ba764c78 100644
--- a/src/cpu/kernels/CpuIm2ColKernel.cpp
+++ b/src/cpu/kernels/CpuIm2ColKernel.cpp
@@ -35,6 +35,8 @@
#include "src/core/CPP/Validate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
+#include "src/cpu/kernels/directconv2d/impl.h"
+#include "src/cpu/kernels/directconv2d/list.h"
#include <arm_neon.h>
#include <cstddef>
@@ -49,6 +51,198 @@ namespace cpu
{
namespace kernels
{
+void run_im2col_fp32_pad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<float, true, false>(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+void run_im2col_fp32_nopad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<float, false, false>(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+#if defined(ARM_COMPUTE_ENABLE_BF16)
+void run_im2col_bf16_pad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<bfloat16, true, false>(
+ src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+void run_im2col_bf16_nopad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<bfloat16, false, false>(
+ src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias);
+}
+#endif /* defined(ARM_COMPUTE_ENABLE_BF16) */
+
+void run_im2col_int8_nopad_nhwc(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<int8_t, false, false>(
+ src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+void run_im2col_uint8_nopad_nhwc(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<uint8_t, false, false>(
+ src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+void run_im2col_qasymm8_pad_nhwc(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+ arm_compute::cpu::kernels::run_im2col<qasymm8_t, true, false>(
+ src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right, has_bias);
+}
+
+void internal_run_im2col_fp16_pad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+/*
+ Note that when building with the option data_type_support=fp32 the fp16.cpp files won't be compiled and the linker
+ would fail with the error undefined arm_compute::cpu::kernels::run_im2col_fp16_pad.
+ To avoid this problem we only call to the actual fp16 kernel if ENABLE_FP16_KERNELS is defined.
+*/
+#if defined(ENABLE_FP16_KERNELS)
+ arm_compute::cpu::kernels::run_im2col_fp16_pad(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+#else // defined(ENABLE_FP16_KERNELS)
+ ARM_COMPUTE_UNUSED(src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right,
+ has_bias);
+#endif // defined(ENABLE_FP16_KERNELS)
+}
+
+void internal_run_im2col_fp16_nopad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+#if defined(ENABLE_FP16_KERNELS)
+ arm_compute::cpu::kernels::run_im2col_fp16_nopad(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+#else // defined(ENABLE_FP16_KERNELS)
+ ARM_COMPUTE_UNUSED(src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right,
+ has_bias);
+#endif // defined(ENABLE_FP16_KERNELS)
+}
+
+void internal_run_im2col_fp16_nchw_pad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+#if defined(ENABLE_FP16_KERNELS)
+ arm_compute::cpu::kernels::run_im2col_fp16_nchw_pad(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+#else // defined(ENABLE_FP16_KERNELS)
+ ARM_COMPUTE_UNUSED(src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right,
+ has_bias);
+#endif // defined(ENABLE_FP16_KERNELS)
+}
+
+void internal_run_im2col_fp16_nchw_nopad(const ITensor *src,
+ ITensor *dst,
+ const Window &window,
+ DataLayout data_layout,
+ const PadStrideInfo &conv_info,
+ std::pair<unsigned int, unsigned int> convolved_dims,
+ const Size2D &kernel_dims,
+ const Size2D &dilation,
+ uint32_t input_pad_right,
+ bool has_bias)
+{
+#if defined(ENABLE_FP16_KERNELS)
+ arm_compute::cpu::kernels::run_im2col_fp16_nchw_nopad(src, dst, window, data_layout, conv_info, convolved_dims,
+ kernel_dims, dilation, input_pad_right, has_bias);
+#else // defined(ENABLE_FP16_KERNELS)
+ ARM_COMPUTE_UNUSED(src, dst, window, data_layout, conv_info, convolved_dims, kernel_dims, dilation, input_pad_right,
+ has_bias);
+#endif // defined(ENABLE_FP16_KERNELS)
+}
+
namespace
{
Status validate_arguments(const ITensorInfo *input,
@@ -86,340 +280,8 @@ Status validate_arguments(const ITensorInfo *input,
return Status{};
}
-
-template <typename T, bool has_pads>
-inline void linearize_volume_nchw(const uint8_t *const in_ptr,
- T *out_ptr,
- bool has_bias,
- int top_left_x,
- int top_left_y,
- int kernel_width,
- int kernel_height,
- int kernel_depth,
- int input_w,
- int input_h,
- int input_stride_x,
- int input_stride_y,
- int input_stride_z,
- int pad_value,
- int dilation_x,
- int dilation_y)
-{
- const int kernel_size2 = kernel_width * kernel_height;
- const int x_e = top_left_x + kernel_width * dilation_x;
- const int y_e = top_left_y + kernel_height * dilation_y;
-
- // Linearize volume
- int d = 0;
- // This for loop linearize a volume with 3 slices. This allows:
- // 1) to reduce the iterations of the outer for loop "d"
- // 2) to have an optimized im2col for the first convolution layer where usually we have 3 IFMs
- for (; d <= (kernel_depth - 3); d += 3)
- {
- for (int y = top_left_y; y < y_e; y += dilation_y)
- {
- if ((y < 0 || y >= input_h) && has_pads)
- {
- // All the values will be the offset (will be zeros when not quantized)
- for (int x = top_left_x; x < x_e; x += dilation_x, ++out_ptr)
- {
- *(out_ptr + 0 * kernel_size2) = pad_value;
- *(out_ptr + 1 * kernel_size2) = pad_value;
- *(out_ptr + 2 * kernel_size2) = pad_value;
- }
- }
- else
- {
- for (int x = top_left_x; x < x_e; x += dilation_x, ++out_ptr)
- {
- if ((x < 0 || x >= input_w) && has_pads)
- {
- *(out_ptr + 0 * kernel_size2) = pad_value;
- *(out_ptr + 1 * kernel_size2) = pad_value;
- *(out_ptr + 2 * kernel_size2) = pad_value;
- }
- else
- {
- *(out_ptr + 0 * kernel_size2) = *(reinterpret_cast<const T *>(
- in_ptr + ((d + 0) * input_stride_z + y * input_stride_y + x * input_stride_x)));
- *(out_ptr + 1 * kernel_size2) = *(reinterpret_cast<const T *>(
- in_ptr + ((d + 1) * input_stride_z + y * input_stride_y + x * input_stride_x)));
- *(out_ptr + 2 * kernel_size2) = *(reinterpret_cast<const T *>(
- in_ptr + ((d + 2) * input_stride_z + y * input_stride_y + x * input_stride_x)));
- }
- }
- }
- }
- out_ptr += 2 * kernel_size2;
- }
-
- // Left over
- for (; d < kernel_depth; d++)
- {
- for (int y = top_left_y; y < y_e; y += dilation_y)
- {
- if ((y < 0 || y >= input_h) && has_pads)
- {
- // All the values will be the offset (will be zeros when not quantized)
- memset(static_cast<void *>(out_ptr), pad_value, kernel_width * sizeof(T));
- out_ptr += kernel_width;
- }
- else
- {
- for (int x = top_left_x; x < x_e; x += dilation_x, ++out_ptr)
- {
- if ((x < 0 || x >= input_w) && has_pads)
- {
- *out_ptr = pad_value;
- }
- else
- {
- *out_ptr = *(reinterpret_cast<const T *>(
- in_ptr + (d * input_stride_z + y * input_stride_y + x * input_stride_x)));
- }
- }
- }
- }
- }
-
- // Append 1 if the convolution layer has biases
- if (has_bias)
- {
- *out_ptr = static_cast<T>(1);
- }
-}
-
-template <typename T, bool has_pads>
-inline void linearize_volume_nhwc(const uint8_t *const in_ptr,
- T *out_ptr,
- bool has_bias,
- int start_x,
- int start_y,
- int kernel_width,
- int kernel_height,
- int input_w,
- int input_h,
- int input_c,
- int input_stride_y,
- int input_stride_z,
- int pad_value,
- int dilation_x,
- int dilation_y)
-{
- const int end_x = start_x + kernel_width * dilation_x;
- const int end_y = start_y + kernel_height * dilation_y;
- const int pad_quant = kernel_width * input_c;
- const int element_size = static_cast<int>(sizeof(T));
- if ((start_y >= 0) && (end_y < input_h) && (start_x >= 0) && (end_x < input_w) && (dilation_x == 1) &&
- (input_stride_y == input_c * element_size))
- {
- for (int y = start_y; y < end_y; y += dilation_y)
- {
- //optimized for no dilation and no boundary pixels
- memcpy(out_ptr, reinterpret_cast<const T *>(in_ptr + (y * input_stride_z + start_x * input_stride_y)),
- input_c * kernel_width * element_size);
- out_ptr += input_c * kernel_width;
- }
- }
- else
- {
- for (int y = start_y; y < end_y; y += dilation_y)
- {
- if (y < 0 || y >= input_h)
- {
- memset(static_cast<void *>(out_ptr), pad_value, pad_quant * element_size);
- out_ptr += pad_quant;
- }
- else if (dilation_x > 1 || start_x < 0 || end_x >= input_w || input_stride_y != input_c * element_size)
- {
- for (int x = start_x; x < end_x; x += dilation_x)
- {
- if (x < 0 || x >= input_w)
- {
- memset(static_cast<void *>(out_ptr), pad_value, input_c * element_size);
- out_ptr += input_c;
- }
- else
- {
- memcpy(out_ptr, reinterpret_cast<const T *>(in_ptr + (y * input_stride_z + x * input_stride_y)),
- input_c * element_size);
- out_ptr += input_c;
- }
- }
- }
- else
- {
- //optimized for no dilation and no boundary pixels
- memcpy(out_ptr, reinterpret_cast<const T *>(in_ptr + (y * input_stride_z + start_x * input_stride_y)),
- input_c * kernel_width * element_size);
- out_ptr += input_c * kernel_width;
- }
- }
- }
- // Append 1 if the convolution layer has biases
- if (has_bias)
- {
- *out_ptr = static_cast<T>(1);
- }
-}
-
-template <typename T, bool has_pads>
-inline void linearize_volume_nhwc(const uint8_t *const in_ptr,
- T *out_ptr,
- bool has_bias,
- int start_x,
- int start_y,
- int kernel_width,
- int kernel_height,
- int input_w,
- int input_h,
- int input_c,
- int input_stride_y,
- int input_stride_z,
- int pad_value,
- int dilation_x,
- int dilation_y,
- int pad_right)
-{
- const int end_x = start_x + kernel_width * dilation_x;
- const int end_y = start_y + kernel_height * dilation_y;
- const int pad_quant = kernel_width * (input_c + pad_right);
- const int element_size = static_cast<int>(sizeof(T));
- const int channel_chunk_size = input_c * element_size;
-
- if ((start_y >= 0) && (end_y < input_h) && (start_x >= 0) && (end_x < input_w) && (dilation_x == 1) &&
- (input_stride_y == channel_chunk_size))
- {
- for (int y = start_y; y < end_y; y += dilation_y)
- {
- const uint8_t *offset_ptr = in_ptr + (y * input_stride_z + start_x * input_stride_y);
- for (int e = 0; e < kernel_width; e++)
- {
- memcpy(out_ptr, reinterpret_cast<const T *>(offset_ptr + e * channel_chunk_size), channel_chunk_size);
- out_ptr += input_c + pad_right;
- }
- }
- }
- else
- {
- for (int y = start_y; y < end_y; y += dilation_y)
- {
- if (y < 0 || y >= input_h)
- {
- memset(static_cast<void *>(out_ptr), pad_value, pad_quant * element_size);
- out_ptr += pad_quant;
- }
- else if (dilation_x > 1 || start_x < 0 || end_x >= input_w || input_stride_y != channel_chunk_size)
- {
- for (int x = start_x; x < end_x; x += dilation_x)
- {
- if (x < 0 || x >= input_w)
- {
- memset(static_cast<void *>(out_ptr), pad_value, (input_c + pad_right) * element_size);
- out_ptr += input_c + pad_right;
- }
- else
- {
- memcpy(out_ptr, reinterpret_cast<const T *>(in_ptr + (y * input_stride_z + x * input_stride_y)),
- channel_chunk_size);
- out_ptr += input_c + pad_right;
- }
- }
- }
- else
- {
- const uint8_t *offset_ptr = in_ptr + (y * input_stride_z + start_x * input_stride_y);
- for (int e = 0; e < kernel_width; e++)
- {
- memcpy(out_ptr, reinterpret_cast<const T *>(offset_ptr + e * channel_chunk_size),
- channel_chunk_size);
- out_ptr += input_c + pad_right;
- }
- }
- }
- }
- // Append 1 if the convolution layer has biases
- if (has_bias)
- {
- *out_ptr = static_cast<T>(1);
- }
-}
-
} // namespace
-template <typename T, bool has_pads, bool is_nchw>
-void CpuIm2ColKernel::run_im2col(const ITensor *src, ITensor *dst, const Window &window)
-{
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
-
- const unsigned int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
- const unsigned int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
- const unsigned int channel_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
-
- const int input_w = src->info()->dimension(width_idx);
- const int input_h = src->info()->dimension(height_idx);
- const int input_c = src->info()->dimension(channel_idx);
- const int input_stride_x = src->info()->strides_in_bytes().x();
- const int input_stride_y = src->info()->strides_in_bytes().y();
- const int input_stride_z = src->info()->strides_in_bytes().z();
- const int pad_left = _conv_info.pad_left();
- const int pad_top = _conv_info.pad_top();
- const int stride_x = _conv_info.stride().first;
- const int stride_y = _conv_info.stride().second;
- const int pad_value =
- is_data_type_quantized(src->info()->data_type()) ? src->info()->quantization_info().uniform().offset : 0;
-
- Window window_in_out(window);
- // The first three dimensions of the input and output are increased by the inner loops
- window_in_out.set(Window::DimX, Window::Dimension(0, 0, 0));
- window_in_out.set(Window::DimY, Window::Dimension(0, 0, 0));
- window_in_out.set(Window::DimZ, Window::Dimension(0, 0, 0));
-
- // Create iterators
- Iterator in(src, window_in_out);
- Iterator out(dst, window_in_out);
-
- execute_window_loop(
- window,
- [&](const Coordinates &id)
- {
- const int start_w = id[width_idx] * stride_x - pad_left;
- const int start_h = id[height_idx] * stride_y - pad_top;
-
- // Get pointers
- const uint8_t *const input_ptr = in.ptr();
- auto output_ptr =
- reinterpret_cast<T *>(out.ptr() + (id[width_idx] + id[height_idx] * _convolved_dims.first) *
- dst->info()->strides_in_bytes().y());
-
- // Linearize volume
- if (is_nchw)
- {
- linearize_volume_nchw<T, has_pads>(
- input_ptr, output_ptr, _has_bias, start_w, start_h, _kernel_width, _kernel_height, input_c, input_w,
- input_h, input_stride_x, input_stride_y, input_stride_z, pad_value, _dilation.x(), _dilation.y());
- }
- else
- {
- if (_input_pad_right > 0)
- {
- linearize_volume_nhwc<T, has_pads>(input_ptr, output_ptr, _has_bias, start_w, start_h,
- _kernel_width, _kernel_height, input_w, input_h, input_c,
- input_stride_y, input_stride_z, pad_value, _dilation.x(),
- _dilation.y(), _input_pad_right);
- }
- else
- {
- linearize_volume_nhwc<T, has_pads>(
- input_ptr, output_ptr, _has_bias, start_w, start_h, _kernel_width, _kernel_height, input_w,
- input_h, input_c, input_stride_y, input_stride_z, pad_value, _dilation.x(), _dilation.y());
- }
- }
- },
- in, out);
-}
-
void CpuIm2ColKernel::configure(const ITensorInfo *src,
ITensorInfo *dst,
const Size2D &kernel_dims,
@@ -453,25 +315,20 @@ void CpuIm2ColKernel::configure(const ITensorInfo *src,
switch (src->data_type())
{
case DataType::F32:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<float, false, true>
- : &CpuIm2ColKernel::run_im2col<float, true, true>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_fp32_nchw_nopad : &run_im2col_fp32_nchw_pad;
+ break;
+ case DataType::F16:
+ _func = (!conv_info.has_padding()) ? &internal_run_im2col_fp16_nchw_nopad
+ : &internal_run_im2col_fp16_nchw_pad;
break;
#if defined(ARM_COMPUTE_ENABLE_BF16)
case DataType::BFLOAT16:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<bfloat16, false, true>
- : &CpuIm2ColKernel::run_im2col<bfloat16, true, true>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_bf16_nchw_nopad : &run_im2col_bf16_nchw_pad;
break;
#endif /* defined(ARM_COMPUTE_ENABLE_BF16) */
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::F16:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<float16_t, false, true>
- : &CpuIm2ColKernel::run_im2col<float16_t, true, true>;
- break;
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
case DataType::QASYMM8_SIGNED:
case DataType::QASYMM8:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<qasymm8_t, false, true>
- : &CpuIm2ColKernel::run_im2col<qasymm8_t, true, true>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_qasymm8_nchw_nopad : &run_im2col_qasymm8_nchw_pad;
break;
default:
ARM_COMPUTE_ERROR("Data type not supported");
@@ -483,28 +340,21 @@ void CpuIm2ColKernel::configure(const ITensorInfo *src,
switch (src->data_type())
{
case DataType::F32:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<float, false, false>
- : &CpuIm2ColKernel::run_im2col<float, true, false>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_fp32_nopad : &run_im2col_fp32_pad;
+ break;
+ case DataType::F16:
+ _func = (!conv_info.has_padding()) ? &internal_run_im2col_fp16_nopad : &internal_run_im2col_fp16_pad;
break;
#if defined(ARM_COMPUTE_ENABLE_BF16)
case DataType::BFLOAT16:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<bfloat16, false, false>
- : &CpuIm2ColKernel::run_im2col<bfloat16, true, false>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_bf16_nopad : &run_im2col_bf16_pad;
break;
#endif /* defined(ARM_COMPUTE_ENABLE_BF16) */
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::F16:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<float16_t, false, false>
- : &CpuIm2ColKernel::run_im2col<float16_t, true, false>;
- break;
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
case DataType::QASYMM8:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<uint8_t, false, false>
- : &CpuIm2ColKernel::run_im2col<qasymm8_t, true, false>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_uint8_nopad_nhwc : &run_im2col_qasymm8_pad_nhwc;
break;
case DataType::QASYMM8_SIGNED:
- _func = (!conv_info.has_padding()) ? &CpuIm2ColKernel::run_im2col<int8_t, false, false>
- : &CpuIm2ColKernel::run_im2col<qasymm8_t, true, false>;
+ _func = (!conv_info.has_padding()) ? &run_im2col_int8_nopad_nhwc : &run_im2col_qasymm8_pad_nhwc;
break;
default:
ARM_COMPUTE_ERROR("Data type not supported");
@@ -552,7 +402,8 @@ void CpuIm2ColKernel::run_op(ITensorPack &tensors, const Window &window, const T
auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
auto dst = tensors.get_tensor(TensorType::ACL_DST);
- (this->*_func)(src, dst, window);
+ _func(src, dst, window, _data_layout, _conv_info, _convolved_dims, Size2D(_kernel_width, _kernel_height), _dilation,
+ _input_pad_right, _has_bias);
}
const char *CpuIm2ColKernel::name() const
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-28 19:20:07 +0000