depthwise
GitOrigin-RevId: 950d2f4889
master
@@ -543,11 +543,11 @@ class RegionRestrictedConvolutionForward : public ConvolutionBase<param::Convolu | |||||
public: | public: | ||||
/** | /** | ||||
* \param[in] src (n, ic, ih, iw) | |||||
* \param[in] filter (oc, ic, fh, fw) | |||||
* \param[in] src (n, ic, ih, iw) or (n, g*icpg, ih, iw) | |||||
* \param[in] filter (oc, ic, fh, fw) or (g, ocpg, icpg, fh, fw) | |||||
* \param[in] rin (n, ih, iw) | * \param[in] rin (n, ih, iw) | ||||
* \param[in] rout (n, oh, ow) | * \param[in] rout (n, oh, ow) | ||||
* \param[out] dst (n, oc, oh, ow) | |||||
* \param[out] dst (n, oc, oh, ow) or (n, g*ocpg, oh, ow) | |||||
*/ | */ | ||||
virtual void exec( | virtual void exec( | ||||
_megdnn_tensor_in src, _megdnn_tensor_in filter, _megdnn_tensor_in rin, | _megdnn_tensor_in src, _megdnn_tensor_in filter, _megdnn_tensor_in rin, | ||||
@@ -592,11 +592,11 @@ class RegionRestrictedConvolutionBackwardData | |||||
public: | public: | ||||
/** | /** | ||||
* \param[in] filter (oc, ic, fh, fw) | |||||
* \param[in] diff (n, oc, oh, ow) | |||||
* \param[in] filter (oc, ic, fh, fw) or (g, ocpg, icpg, fh, fw) | |||||
* \param[in] diff (n, oc, oh, ow) or (n, g*ocpg, oh, ow) | |||||
* \param[in] rin (n, ih, iw) | * \param[in] rin (n, ih, iw) | ||||
* \param[in] rout (n, oh, ow) | * \param[in] rout (n, oh, ow) | ||||
* \param[out] grad (n, ic, ih, iw) | |||||
* \param[out] grad (n, ic, ih, iw) or (n, g*icpg, ih, iw) | |||||
*/ | */ | ||||
virtual void exec( | virtual void exec( | ||||
_megdnn_tensor_in filter, _megdnn_tensor_in diff, _megdnn_tensor_in rin, | _megdnn_tensor_in filter, _megdnn_tensor_in diff, _megdnn_tensor_in rin, | ||||
@@ -635,11 +635,11 @@ class RegionRestrictedConvolutionBackwardFilter | |||||
public: | public: | ||||
/** | /** | ||||
* \param[in] src (n, ic, ih, iw) | |||||
* \param[in] diff (n, oc, oh, ow) | |||||
* \param[in] src (n, ic, ih, iw) or (n, g*icpg, ih, iw) | |||||
* \param[in] diff (n, oc, oh, ow) or (n, g*ocpg, oh, ow) | |||||
* \param[in] rin (n, ih, iw) | * \param[in] rin (n, ih, iw) | ||||
* \param[in] rout (n, oh, ow) | * \param[in] rout (n, oh, ow) | ||||
* \param[out] grad (oc, ic, fh, fw) | |||||
* \param[out] grad (oc, ic, fh, fw) or (g, ocpg, icpg, fh, fw) | |||||
*/ | */ | ||||
virtual void exec( | virtual void exec( | ||||
_megdnn_tensor_in src, _megdnn_tensor_in diff, _megdnn_tensor_in rin, | _megdnn_tensor_in src, _megdnn_tensor_in diff, _megdnn_tensor_in rin, | ||||
@@ -20,7 +20,7 @@ void RegionRestrictedConvolutionForwardImpl::exec( | |||||
src.layout, dst.layout, fm, | src.layout, dst.layout, fm, | ||||
param().compute_mode == Param::ComputeMode::DEFAULT); | param().compute_mode == Param::ComputeMode::DEFAULT); | ||||
megdnn_assert( | megdnn_assert( | ||||
fm.group > 1 && src.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
src.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
param().compute_mode == Param::ComputeMode::DEFAULT && | param().compute_mode == Param::ComputeMode::DEFAULT && | ||||
fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | ||||
fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | ||||
@@ -76,7 +76,7 @@ void RegionRestrictedConvolutionBackwardDataImpl::exec( | |||||
diff.layout, grad.layout, fm, | diff.layout, grad.layout, fm, | ||||
param().compute_mode == Param::ComputeMode::DEFAULT); | param().compute_mode == Param::ComputeMode::DEFAULT); | ||||
megdnn_assert( | megdnn_assert( | ||||
fm.group > 1 && diff.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
diff.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
param().compute_mode == Param::ComputeMode::DEFAULT && | param().compute_mode == Param::ComputeMode::DEFAULT && | ||||
fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | ||||
fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | ||||
@@ -120,7 +120,7 @@ void RegionRestrictedConvolutionBackwardFilterImpl::exec( | |||||
workspace.size); | workspace.size); | ||||
megdnn_assert( | megdnn_assert( | ||||
fm.group > 1 && src.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
src.layout.dtype.category() == DTypeCategory::FLOAT && | |||||
param().compute_mode == Param::ComputeMode::DEFAULT && | param().compute_mode == Param::ComputeMode::DEFAULT && | ||||
fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 && | ||||
fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip && | ||||
@@ -53,6 +53,7 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER) { | |||||
run(4, 8, 32, 5, 5 / 2, 1); | run(4, 8, 32, 5, 5 / 2, 1); | ||||
run(4, 8, 32, 7, 7 / 2, 1); | run(4, 8, 32, 7, 7 / 2, 1); | ||||
run(1, 2, 32, 9, 9 / 2, 1); | run(1, 2, 32, 9, 9 / 2, 1); | ||||
run(4, 1, 32, 9, 9 / 2, 1); | |||||
run(4, 8, 32, 11, 11 / 2, 1); | run(4, 8, 32, 11, 11 / 2, 1); | ||||
run(4, 8, 32, 13, 13 / 2, 1); | run(4, 8, 32, 13, 13 / 2, 1); | ||||
run(4, 8, 32, 15, 15 / 2, 1); | run(4, 8, 32, 15, 15 / 2, 1); | ||||
@@ -723,6 +724,7 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32) { | |||||
run(4, 8, 32, 25, 25 / 2, 1); | run(4, 8, 32, 25, 25 / 2, 1); | ||||
run(4, 8, 32, 27, 27 / 2, 1); | run(4, 8, 32, 27, 27 / 2, 1); | ||||
run(4, 8, 32, 29, 29 / 2, 1); | run(4, 8, 32, 29, 29 / 2, 1); | ||||
run(4, 1, 32, 29, 29 / 2, 1); | |||||
run(4, 8, 32, 31, 31 / 2, 1); | run(4, 8, 32, 31, 31 / 2, 1); | ||||
} | } | ||||
} | } | ||||
@@ -779,6 +781,7 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32_RIN_EQ_ROUT) { | |||||
run(4, 8, 32, 21, 21 / 2, 1); | run(4, 8, 32, 21, 21 / 2, 1); | ||||
run(4, 8, 32, 23, 23 / 2, 1); | run(4, 8, 32, 23, 23 / 2, 1); | ||||
run(4, 8, 32, 25, 25 / 2, 1); | run(4, 8, 32, 25, 25 / 2, 1); | ||||
run(4, 1, 32, 25, 25 / 2, 1); | |||||
run(4, 8, 32, 27, 27 / 2, 1); | run(4, 8, 32, 27, 27 / 2, 1); | ||||
run(4, 8, 32, 29, 29 / 2, 1); | run(4, 8, 32, 29, 29 / 2, 1); | ||||
run(4, 8, 32, 31, 31 / 2, 1); | run(4, 8, 32, 31, 31 / 2, 1); | ||||
@@ -841,6 +844,7 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_FILTER_FP32) { | |||||
run(4, 8, 32, 23, 23 / 2, 1); | run(4, 8, 32, 23, 23 / 2, 1); | ||||
run(4, 8, 32, 25, 25 / 2, 1); | run(4, 8, 32, 25, 25 / 2, 1); | ||||
run(4, 8, 32, 27, 27 / 2, 1); | run(4, 8, 32, 27, 27 / 2, 1); | ||||
run(4, 1, 32, 27, 27 / 2, 1); | |||||
run(4, 8, 32, 29, 29 / 2, 1); | run(4, 8, 32, 29, 29 / 2, 1); | ||||
run(4, 8, 32, 31, 31 / 2, 1); | run(4, 8, 32, 31, 31 / 2, 1); | ||||
} | } | ||||
@@ -899,6 +903,7 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_FILTER_FP32_RIN_EQ_ROUT) { | |||||
run(4, 8, 32, 17, 17 / 2, 1); | run(4, 8, 32, 17, 17 / 2, 1); | ||||
run(4, 8, 32, 19, 19 / 2, 1); | run(4, 8, 32, 19, 19 / 2, 1); | ||||
run(4, 8, 32, 21, 21 / 2, 1); | run(4, 8, 32, 21, 21 / 2, 1); | ||||
run(4, 1, 32, 21, 21 / 2, 1); | |||||
run(4, 8, 32, 23, 23 / 2, 1); | run(4, 8, 32, 23, 23 / 2, 1); | ||||
run(4, 8, 32, 25, 25 / 2, 1); | run(4, 8, 32, 25, 25 / 2, 1); | ||||
run(4, 8, 32, 27, 27 / 2, 1); | run(4, 8, 32, 27, 27 / 2, 1); | ||||
@@ -2016,7 +2016,12 @@ def region_restricted_conv( | |||||
stride_h, stride_w = expand_hw(stride) | stride_h, stride_w = expand_hw(stride) | ||||
dilate_h, dilate_w = expand_hw(dilation) | dilate_h, dilate_w = expand_hw(dilation) | ||||
sparse_type = "dense" if groups == 1 else "group" | |||||
sparse_type = "group" | |||||
assert groups > 0, ( | |||||
"RegionRestrictedConv expected grouped conv mode, \ | |||||
which requires groups > 0, but got groups=%d" | |||||
% (groups) | |||||
) | |||||
op = builtin.RegionRestrictedConvolution( | op = builtin.RegionRestrictedConvolution( | ||||
stride_h=stride_h, | stride_h=stride_h, | ||||
stride_w=stride_w, | stride_w=stride_w, | ||||
@@ -1050,8 +1050,8 @@ class RegionRestrictedConv(_ConvNd): | |||||
Refer to :class:`~.module.padding.Pad` for more information. | Refer to :class:`~.module.padding.Pad` for more information. | ||||
Note: | Note: | ||||
* ``weight`` usually has shape ``(out_channels, in_channels, height, width)`` , | |||||
if groups is not 1, shape will be ``(groups, out_channels // groups, in_channels // groups, height, width)`` | |||||
* weight shape will be ``(groups, out_channels // groups, in_channels // groups, height, width)``, | |||||
becasue RegionRestrictedConv support grouped conv only. | |||||
Examples: | Examples: | ||||
>>> import numpy as np | >>> import numpy as np | ||||
@@ -1071,7 +1071,7 @@ class RegionRestrictedConv(_ConvNd): | |||||
in_channels: int, | in_channels: int, | ||||
out_channels: int, | out_channels: int, | ||||
kernel_size: Union[int, Tuple[int, int]], | kernel_size: Union[int, Tuple[int, int]], | ||||
groups: int, | |||||
groups: int = 1, | |||||
bias: bool = True, | bias: bool = True, | ||||
stride: Union[int, Tuple[int, int]] = 1, | stride: Union[int, Tuple[int, int]] = 1, | ||||
padding: Union[int, Tuple[int, int]] = 0, | padding: Union[int, Tuple[int, int]] = 0, | ||||
@@ -1111,9 +1111,6 @@ class RegionRestrictedConv(_ConvNd): | |||||
ichl = self.in_channels | ichl = self.in_channels | ||||
ochl = self.out_channels | ochl = self.out_channels | ||||
kh, kw = self.kernel_size | kh, kw = self.kernel_size | ||||
if group == 1: | |||||
# Assume format is NCHW | |||||
return (ochl, ichl, kh, kw) | |||||
assert ( | assert ( | ||||
ichl % group == 0 and ochl % group == 0 | ichl % group == 0 and ochl % group == 0 | ||||
@@ -971,17 +971,16 @@ def test_region_restricted_conv_forward_backward_naive(bias): | |||||
@pytest.mark.skipif( | @pytest.mark.skipif( | ||||
not is_cuda_available(), reason="rrconv cuda kernel requires cuda available" | not is_cuda_available(), reason="rrconv cuda kernel requires cuda available" | ||||
) | ) | ||||
@pytest.mark.parametrize("bias", [True, False]) | |||||
def test_region_restricted_conv_forward_backward_cuda(bias): | |||||
@pytest.mark.parametrize("bias, groups", [(True, 1), (True, 3), (False, 1), (False, 3)]) | |||||
def test_region_restricted_conv_forward_backward_cuda(bias, groups): | |||||
import megengine as mge | import megengine as mge | ||||
import megengine.module as M | import megengine.module as M | ||||
from megengine.autodiff import GradManager | from megengine.autodiff import GradManager | ||||
import megengine.distributed as dist | |||||
# params | # params | ||||
handle = "gpu0" | handle = "gpu0" | ||||
N = 1 | N = 1 | ||||
GROUP = 3 | |||||
GROUP = groups | |||||
FH = FW = 2 | FH = FW = 2 | ||||
IH = IW = 2 | IH = IW = 2 | ||||
OH = OW = 1 | OH = OW = 1 | ||||
@@ -1051,8 +1050,8 @@ def test_region_restricted_conv_forward_backward_cuda(bias): | |||||
@pytest.mark.skipif( | @pytest.mark.skipif( | ||||
not is_cuda_available(), reason="rrconv cuda kernel requires cuda available" | not is_cuda_available(), reason="rrconv cuda kernel requires cuda available" | ||||
) | ) | ||||
@pytest.mark.parametrize("bias", [True, False]) | |||||
def test_region_restricted_conv_forward_backward_uint8(bias): | |||||
@pytest.mark.parametrize("bias, groups", [(True, 1), (True, 3), (False, 1), (False, 3)]) | |||||
def test_region_restricted_conv_forward_backward_uint8(bias, groups): | |||||
import megengine as mge | import megengine as mge | ||||
import megengine.module as M | import megengine.module as M | ||||
from megengine.autodiff import GradManager | from megengine.autodiff import GradManager | ||||
@@ -1060,7 +1059,7 @@ def test_region_restricted_conv_forward_backward_uint8(bias): | |||||
# params | # params | ||||
handle = "gpu0" | handle = "gpu0" | ||||
N = 1 | N = 1 | ||||
GROUP = 2 | |||||
GROUP = groups | |||||
FH = FW = 1 | FH = FW = 1 | ||||
IH = IW = 4 | IH = IW = 4 | ||||
OH = OW = 4 | OH = OW = 4 | ||||