COMPMID-556: Fix CLDepthwiseConvolution3x3 Kernel.
Kernel was not sliding the input window.
Change-Id: Ia5903ceaed1243e86bee773a84102d8a1132dfa5
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111055
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp
index 208d06d..63586b0 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp
@@ -137,14 +137,16 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
- Window slice_in = window.first_slice_window_3D();
+ // Create input window and adjust
+ Window win_in = window;
+ win_in.adjust(Window::DimX, -_conv_pad_left, true);
+ win_in.adjust(Window::DimY, -_conv_pad_top, true);
+ win_in.set_dimension_step(Window::DimX, window.x().step() * _conv_stride_x);
+ win_in.set_dimension_step(Window::DimY, window.y().step() * _conv_stride_y);
+
+ Window slice_in = win_in.first_slice_window_3D();
Window slice_out = window.first_slice_window_3D();
Window slice_weights = window.first_slice_window_3D();
-
- slice_in.adjust(Window::DimX, -_conv_pad_left, true);
- slice_in.adjust(Window::DimY, -_conv_pad_top, true);
- slice_in.set_dimension_step(Window::DimX, window.x().step() * _conv_stride_x);
- slice_in.set_dimension_step(Window::DimY, window.y().step() * _conv_stride_y);
slice_weights.set_dimension_step(Window::DimX, 0);
slice_weights.set_dimension_step(Window::DimY, 0);
@@ -166,5 +168,5 @@
enqueue(queue, *this, slice_out);
}
- while(window.slide_window_slice_3D(slice_out));
+ while(window.slide_window_slice_3D(slice_out) && win_in.slide_window_slice_3D(slice_in));
}
diff --git a/tests/datasets/DepthwiseConvolutionDataset.h b/tests/datasets/DepthwiseConvolutionDataset.h
index 430d2c9..2c8347f 100644
--- a/tests/datasets/DepthwiseConvolutionDataset.h
+++ b/tests/datasets/DepthwiseConvolutionDataset.h
@@ -161,10 +161,10 @@
public:
SmallDepthwiseConvolutionDataset3x3()
{
- add_config(TensorShape(7U, 7U, 3U), TensorShape(3U, 3U, 3U), TensorShape(3U), TensorShape(5U, 5U, 3U), PadStrideInfo(1, 1, 0, 0));
+ add_config(TensorShape(7U, 7U, 3U, 2U), TensorShape(3U, 3U, 3U), TensorShape(3U), TensorShape(5U, 5U, 3U, 2U), PadStrideInfo(1, 1, 0, 0));
add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(11U, 14U, 11U), PadStrideInfo(3, 2, 1, 1));
- add_config(TensorShape(21U, 31U, 9U), TensorShape(3U, 3U, 9U), TensorShape(9U), TensorShape(21U, 15U, 9U), PadStrideInfo(1, 2, 1, 0));
- add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(31U, 14U, 11U), PadStrideInfo(1, 2, 0, 1));
+ add_config(TensorShape(21U, 31U, 9U, 4U), TensorShape(3U, 3U, 9U), TensorShape(9U), TensorShape(21U, 15U, 9U, 4U), PadStrideInfo(1, 2, 1, 0));
+ add_config(TensorShape(33U, 27U, 11U, 3U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(31U, 14U, 11U, 3U), PadStrideInfo(1, 2, 0, 1));
}
};
@@ -173,11 +173,11 @@
public:
LargeDepthwiseConvolutionDataset3x3()
{
- add_config(TensorShape(233U, 277U, 55U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(116U, 275U, 55U), PadStrideInfo(2, 1, 0, 0));
+ add_config(TensorShape(233U, 277U, 55U, 3U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(116U, 275U, 55U, 3U), PadStrideInfo(2, 1, 0, 0));
add_config(TensorShape(333U, 277U, 77U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(111U, 138U, 77U), PadStrideInfo(3, 2, 1, 0));
add_config(TensorShape(177U, 311U, 22U), TensorShape(3U, 3U, 22U), TensorShape(22U), TensorShape(177U, 156U, 22U), PadStrideInfo(1, 2, 1, 1));
add_config(TensorShape(233U, 277U, 55U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(231U, 138U, 55U), PadStrideInfo(1, 2, 0, 0));
- add_config(TensorShape(333U, 277U, 77U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(166U, 93U, 77U), PadStrideInfo(2, 3, 0, 1));
+ add_config(TensorShape(333U, 277U, 77U, 5U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(166U, 93U, 77U, 5U), PadStrideInfo(2, 3, 0, 1));
add_config(TensorShape(177U, 311U, 22U), TensorShape(3U, 3U, 22U), TensorShape(22U), TensorShape(89U, 311U, 22U), PadStrideInfo(2, 1, 1, 1));
}
};
diff --git a/tests/validation/CPP/DepthwiseConvolution.cpp b/tests/validation/CPP/DepthwiseConvolution.cpp
index ad06538..229e044 100644
--- a/tests/validation/CPP/DepthwiseConvolution.cpp
+++ b/tests/validation/CPP/DepthwiseConvolution.cpp
@@ -137,6 +137,7 @@
const int input_width = src.shape().x();
const int input_height = src.shape().y();
const int input_depth = src.shape().z();
+ const int num_batches = src.shape().total_size() / (input_width * input_height * input_depth);
const int filter_half_size = filter_width / 2;
const int pad_x = std::min(filter_half_size, static_cast<int>(conv_info.pad().first));
@@ -145,37 +146,40 @@
const int minimum_y = -pad_y + filter_half_size;
int out_pos = 0;
- for(int z = 0; z < input_depth; ++z)
+ for(int r = 0; r < num_batches; ++r)
{
- int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z)));
- for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second)
+ for(int z = 0; z < input_depth; ++z)
{
- for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first)
+ int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z)));
+ for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second)
{
- Coordinates coords(x, y, z);
- int filter_offset = filter_plane * z;
-
- uint32_t val = 0;
- for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j)
+ for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first)
{
- for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i)
- {
- coords.set(0, i);
- coords.set(1, j);
- auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, 0);
- uint8_t w_val = *(weights.data() + filter_offset);
- val += (in_val + input_offset) * (w_val + weights_offset);
- ++filter_offset;
- }
- }
- val += bias_val;
- val = asymm_rounding_divide_by_pow2(asymm_int_mult(val, output_multiplier), output_shift);
- val += output_offset;
- val = std::max<int32_t>(val, 0);
- val = std::min<int32_t>(val, 255);
+ Coordinates coords(x, y, z);
+ int filter_offset = filter_plane * z;
- // Store the result
- dst[out_pos++] = val;
+ uint32_t val = 0;
+ for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j)
+ {
+ for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i)
+ {
+ coords.set(0, i);
+ coords.set(1, j);
+ auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, 0);
+ uint8_t w_val = *(weights.data() + filter_offset);
+ val += (in_val + input_offset) * (w_val + weights_offset);
+ ++filter_offset;
+ }
+ }
+ val += bias_val;
+ val = asymm_rounding_divide_by_pow2(asymm_int_mult(val, output_multiplier), output_shift);
+ val += output_offset;
+ val = std::max<int32_t>(val, 0);
+ val = std::min<int32_t>(val, 255);
+
+ // Store the result
+ dst[out_pos++] = val;
+ }
}
}
}