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new bdcf137 Make convolution operator fully work with oneDNN v2.4+
(#20847)
bdcf137 is described below
commit bdcf1370ab8f76d66aee1599fbd021a3660fdd66
Author: bartekkuncer <[email protected]>
AuthorDate: Tue Feb 1 12:15:02 2022 +0100
Make convolution operator fully work with oneDNN v2.4+ (#20847)
* Restore full functionality to convolution
* Update src/operator/nn/dnnl/dnnl_convolution.cc
Co-authored-by: bgawrych <[email protected]>
Co-authored-by: bgawrych <[email protected]>
---
src/operator/nn/dnnl/dnnl_convolution.cc | 16 ++++++++++++----
tests/python/dnnl/subgraphs/subgraph_common.py | 5 +----
2 files changed, 13 insertions(+), 8 deletions(-)
diff --git a/src/operator/nn/dnnl/dnnl_convolution.cc
b/src/operator/nn/dnnl/dnnl_convolution.cc
index 072c157..d38009a 100644
--- a/src/operator/nn/dnnl/dnnl_convolution.cc
+++ b/src/operator/nn/dnnl/dnnl_convolution.cc
@@ -118,10 +118,18 @@
std::shared_ptr<dnnl::convolution_forward::primitive_desc> GetConvFwdImpl(
// suboptimal kernel for computation that has the expected memory
size requirements
auto conv_pd =
std::make_shared<dnnl::convolution_forward::primitive_desc>(desc, attr, engine);
- while (conv_pd->dst_desc().get_size() != GetArraySize(output) ||
- conv_pd->src_desc().get_size() != GetArraySize(data) ||
- (!param.dnnl_param.quantized &&
- conv_pd->weights_desc().get_size() !=
GetArraySize(weights))) {
+ while (
+ conv_pd->dst_desc().get_size() != GetArraySize(output) ||
+ conv_pd->src_desc().get_size() != GetArraySize(data) ||
+ (!param.dnnl_param.quantized &&
+ conv_pd->weights_desc().get_size() != GetArraySize(weights)) ||
+ // With the upgrade of oneDNN to version 2.4+
+ //
tests/python/dnnl/subgraphs/test_conv_subgraph.py::test_pos_conv_add[True-data_shape1]
+ // started failing. Switching away from primitive with weight
dnnl::format_tag
+ // ABcd4b16a4b in order to temporarily fix the issue until full
fix arrives.
+ // Tracking issue:
https://github.com/apache/incubator-mxnet/issues/20826.
+ (param.dnnl_param.quantized && conv_pd->weights_desc().dims()[1]
< 4 &&
+ conv_pd->weights_desc().data.padded_dims[1] == 16)) {
// next_impl() will visit desc and engine, please make sure they
are still alive here.
CHECK(conv_pd->next_impl()) << "No convolution implementation for
this request.";
}
diff --git a/tests/python/dnnl/subgraphs/subgraph_common.py
b/tests/python/dnnl/subgraphs/subgraph_common.py
index b3bf5b0..be2adb9 100644
--- a/tests/python/dnnl/subgraphs/subgraph_common.py
+++ b/tests/python/dnnl/subgraphs/subgraph_common.py
@@ -42,10 +42,7 @@ config = {
}
}
-DATA_SHAPE=[(64, 4, 10, 10), (4, 4, 24, 24), (1, 16, 32, 32)]
-# Second shape has been temporairly changed from (4, 3, 24, 24) to (4, 4, 24,
24) due to
-# a bug regarding conv+sum fuse with the amount of input channels < 4. It will
be reverted
-# as soon as the problem is fixed. Issue:
https://github.com/apache/incubator-mxnet/issues/20826.
+DATA_SHAPE=[(64, 4, 10, 10), (4, 3, 24, 24), (1, 16, 32, 32)]
# Helpers
class RELU6(nn.HybridBlock):
