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bgawrych pushed a commit to branch v1.x
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The following commit(s) were added to refs/heads/v1.x by this push:
new c5d0adb [v1.x][BUGFIX] Fix
tests/python/dnnl/subgraphs/test_conv_subgraph.py (#20971)
c5d0adb is described below
commit c5d0adb3603f82d2d75893124affa23375cb32da
Author: bartekkuncer <[email protected]>
AuthorDate: Wed Mar 23 17:44:31 2022 +0100
[v1.x][BUGFIX] Fix tests/python/dnnl/subgraphs/test_conv_subgraph.py
(#20971)
* [v1.x][BUGFIX] Fix tests/python/dnnl/subgraphs/test_conv_subgraph.py
* Fix sanity
---
src/operator/nn/mkldnn/mkldnn_convolution.cc | 70 ++++++++++++++--------------
1 file changed, 35 insertions(+), 35 deletions(-)
diff --git a/src/operator/nn/mkldnn/mkldnn_convolution.cc
b/src/operator/nn/mkldnn/mkldnn_convolution.cc
index 2a2c6d7..78f95bd 100644
--- a/src/operator/nn/mkldnn/mkldnn_convolution.cc
+++ b/src/operator/nn/mkldnn/mkldnn_convolution.cc
@@ -109,41 +109,41 @@
std::shared_ptr<mkldnn::convolution_forward::primitive_desc> GetConvFwdImpl(
int mask = (param.requantize_scales.size() > 1) ? 2 : 0;
attr.set_output_scales(mask, param.requantize_scales);
}
- auto GetConvFwdPd =
- [¶m, &data, &weights, &output, &attr](const
mkldnn::convolution_forward::desc& desc) {
- auto engine = CpuEngine::Get()->get_engine();
- try {
- // MKLDNN introduced padded formats since 0.15 which require more
memory compared to the
- // actual size of the tensor. Currently, MKLDNN operators still
reuse memory from memory
- // planning, so here we need to select a suboptimal kernel for
computation that has the
- // expected memory size requirements
- auto conv_pd =
-
std::make_shared<mkldnn::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.mkldnn_param.quantized &&
- conv_pd->weights_desc().get_size() != GetArraySize(weights))
||
- // With the upgrade of MKLDNN to version 2.4+
- // tests/python/mkl/test_subgraph.py::test_pos_conv_add
started failing. Switching
- // away from primitive with weight mkldnn::format_tag
ABcd4b16a4b in order to
- // temporairly fix the issue until full fix arrives. Tracking
issue:
- // https://github.com/apache/incubator-mxnet/issues/20826.
- (param.mkldnn_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.";
- }
- return conv_pd;
- } catch (mkldnn::error& e) {
- if (e.status == mkldnn_unimplemented &&
param.mkldnn_param.quantized) {
- LOG(ERROR) << "AVX512-BW support or Intel(R) MKL dependency is "
- "required for int8 convolution";
- } else {
- LOG(ERROR) << e.message;
- }
- throw;
- }
- };
+ auto GetConvFwdPd = [¶m, &data, &weights, &output, &attr](
+ const mkldnn::convolution_forward::desc& desc) {
+ auto engine = CpuEngine::Get()->get_engine();
+ try {
+ // MKLDNN introduced padded formats since 0.15 which require more memory
compared to the
+ // actual size of the tensor. Currently, MKLDNN operators still reuse
memory from memory
+ // planning, so here we need to select a suboptimal kernel for
computation that has the
+ // expected memory size requirements
+ auto conv_pd =
+ std::make_shared<mkldnn::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.mkldnn_param.quantized &&
+ conv_pd->weights_desc().get_size() != GetArraySize(weights)) ||
+ // With the upgrade of MKLDNN to version 2.4+
+ // tests/python/mkl/test_subgraph.py::test_pos_conv_add started
failing. Switching away
+ // from blocking weights in order to temporarily fix the issue until
full fix arrives.
+ // Tracking issue:
https://github.com/apache/incubator-mxnet/issues/20826.
+ (param.mkldnn_param.quantized && conv_pd->weights_desc().dims()[1] <
4 &&
+ conv_pd->weights_desc().data.padded_dims[1] !=
conv_pd->weights_desc().dims()[1])) {
+ // 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.";
+ }
+ return conv_pd;
+ } catch (mkldnn::error& e) {
+ if (e.status == mkldnn_unimplemented && param.mkldnn_param.quantized) {
+ LOG(ERROR) << "AVX512-BW support or Intel(R) MKL dependency is "
+ "required for int8 convolution";
+ } else {
+ LOG(ERROR) << e.message;
+ }
+ throw;
+ }
+ };
if (param.conv_param.dilate.ndim() == 0 && bias_md_ptr == nullptr) {
mkldnn::convolution_forward::desc desc(prop,
