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MLPerf's pre.2021.1.submission branch update (DO NOT REVIEW) (#2083) 

* fixed code and updated unit tests to accomodate auto-reshaping graphs, to unlock full validation

* [CPU][BF16] bf16 for Gemm or MatMul was enabled (#1920)

# Conflicts:
#	inference-engine/thirdparty/mkl-dnn

* Fuse EmbeddingBag

Co-authored-by: Alexey Varyzgin <alexey.varyzgin@intel.com>
Co-authored-by: Vafin, Maxim <maxim.vafin@intel.com>
This commit is contained in:
Maxim Shevtsov 2020-09-04 18:20:25 +03:00 committed by GitHub
parent 05a57ebd8e
commit 1e6ca0627a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 110 additions and 5 deletions
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2
inference-engine/include/ie_precision.hpp
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@ -224,7 +224,7 @@ public:
(precisionInfo.value == Precision::Q78) || (precisionInfo.value == Precision::I16) ||
(precisionInfo.value == Precision::I8) || (precisionInfo.value == Precision::I32) ||
(precisionInfo.value == Precision::I64) || (precisionInfo.value == Precision::BIN) ||
(precisionInfo.value == Precision::CUSTOM);
(precisionInfo.value == Precision::BF16) || (precisionInfo.value == Precision::CUSTOM);
}
protected:

2
inference-engine/src/mkldnn_plugin/bf16transformer.h
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@ -13,7 +13,7 @@ namespace MKLDNNPlugin {
class BF16Transformer {
const InferenceEngine::details::caseless_set<std::string> _initbf16 =
{ "convolution", "fullyconnected", "innerproduct" };
{ "convolution", "fullyconnected", "innerproduct", "gemm" };
const InferenceEngine::details::caseless_set<std::string> _complementbf16 =
{ "relu", "tanh", "elu", "square", "abs", "sqrt", "linear", "bounded_relu", "soft_relu", "logistic",
"exp", "gelu", "clamp", "swish", "prelu", "pooling", "norm", "gather", "memory" };

17
inference-engine/src/mkldnn_plugin/nodes/mkldnn_gemm_node.cpp
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@ -122,8 +122,13 @@ void MKLDNNGemmNode::initSupportedPrimitiveDescriptors() {
auto inPrec0 = getCnnLayer()->insData[0].lock()->getPrecision();
auto inPrec1 = getCnnLayer()->insData[1].lock()->getPrecision();
if ((inPrec0 != Precision::U8 && inPrec0 != Precision::I8) || inPrec1 != Precision::I8 || isThreeInputs) {
inPrec0 = Precision::FP32;
inPrec1 = Precision::FP32;
if (inPrec0 == Precision::BF16 || inPrec1 == Precision::BF16) {
inPrec0 = Precision::BF16;
inPrec1 = Precision::BF16;
} else {
inPrec0 = Precision::FP32;
inPrec1 = Precision::FP32;
}
}
auto inputDataType0 = MKLDNNExtensionUtils::IEPrecisionToDataType(inPrec0);
@ -192,6 +197,11 @@ inline void process_gemm(char transa, char transb, int M, int N, int K, float al
mkldnn_sgemm(transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc);
}
inline void process_gemm(char transa, char transb, int M, int N, int K, float alpha, const uint16_t *A, int lda,
const uint16_t *B, int ldb, float beta, float *C, int ldc) {
mkldnn_gemm_bf16bf16f32(transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc);
}
inline void process_gemm(char transa, char transb, int M, int N, int K, float alpha, const uint8_t *A, int lda,
const int8_t *B, int ldb, float beta, float *C, int ldc) {
const int32_t co = 0;
@ -288,6 +298,9 @@ void MKLDNNGemmNode::execute(mkldnn::stream strm) {
case Precision::FP32:
process_data<float, float>();
break;
case Precision::BF16:
process_data<uint16_t, uint16_t>();
break;
case Precision::I8:
process_data<int8_t, int8_t>();
break;

2
inference-engine/thirdparty/mkl-dnn vendored

@ -1 +1 @@
Subproject commit 4f511de56e21b417f7c49c3f50cf7217350412ab
Subproject commit b96a54762aedf27711f8e9144d05b2697b03cc40

1
model-optimizer/automation/package_BOM.txt
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@ -119,6 +119,7 @@ extensions/front/create_tensor_nodes.py
extensions/front/disable_weights_quantize_value_propagation.py
extensions/front/div.py
extensions/front/eltwise_n.py
extensions/front/EmbeddingBagFuse.py
extensions/front/ExpandDimsToUnsqueeze.py
extensions/front/FillToBroadcast.py
extensions/front/flatten_to_reshape.py

91
model-optimizer/extensions/front/EmbeddingBagFuse.py Normal file
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@ -0,0 +1,91 @@
"""
Copyright (C) 2020 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from extensions.ops.embedding_bag import EmbeddingBagOffsetsSum
from mo.front.common.replacement import FrontReplacementSubgraph
from mo.graph.graph import Graph, rename_nodes
class EmbeddingBagFuse(FrontReplacementSubgraph):
enabled = True
def run_after(self):
from extensions.front.ExpandDimsToUnsqueeze import ExpandDimsToUnsqueeze
from extensions.front.AttributedGatherNormalizer import AttributedGatherNormalizer
return [ExpandDimsToUnsqueeze, AttributedGatherNormalizer]
def pattern(self):
return dict(
nodes=[
('weights', dict(op='Const')),
('concat_before', dict(op='Concat')),
('gather_before1_1', dict(op='Gather')),
('unsqueeze_before1_1', dict(op='Unsqueeze')),
('gather_before2_1', dict(op='Gather')),
('unsqueeze_before2_1', dict(op='Unsqueeze')),
('slice1', dict(op='Slice')),
('gather_after1', dict(op='Gather')),
('reduce1', dict(op='ReduceSum')),
('unsqueeze_after1', dict(op='Unsqueeze')),
('concat_after', dict(op='Concat')),
],
edges=[
('concat_before', 'gather_before1_1'),
('concat_before', 'gather_before2_1'),
('gather_before1_1', 'unsqueeze_before1_1'),
('gather_before2_1', 'unsqueeze_before2_1'),
('unsqueeze_before1_1', 'slice1', {'out': 0, 'in': 1}),
('unsqueeze_before2_1', 'slice1', {'out': 0, 'in': 2}),
('weights', 'gather_after1', {'out': 0, 'in': 0}),
('slice1', 'gather_after1', {'out': 0, 'in': 1}),
('gather_after1', 'reduce1'),
('reduce1', 'unsqueeze_after1'),
('unsqueeze_after1', 'concat_after'),
])
def replace_sub_graph(self, graph: Graph, match: dict):
concat_before = match['concat_before']
gather_after1 = match['gather_after1']
slice1 = match['slice1']
concat_after = match['concat_after']
weights_node = gather_after1.in_port(0).get_source().node
gather_after_axis = gather_after1.in_port(2).get_source().node.soft_get('value')
for dst_port in weights_node.out_port(0).get_destinations():
node = dst_port.node
if node.op == 'Gather':
# validate that all Gathers have same axis
if node.in_port(2).get_source().node.soft_get('value') != gather_after_axis:
return
dst_port.disconnect()
indices_node = slice1.in_port(0).get_source().node
slice_axis = slice1.in_port(3).get_source().node.soft_get('value')
for dst_port in indices_node.out_port(0).get_destinations():
node = dst_port.node
if node.op == 'Slice':
# validate that all Slices have same axis
if node.in_port(3).get_source().node.soft_get('value') != slice_axis:
return
dst_port.disconnect()
emb_bag = EmbeddingBagOffsetsSum(graph, {}).create_node()
weights_node.out_port(0).connect(emb_bag.in_port(0))
indices_node.out_port(0).connect(emb_bag.in_port(1))
concat_before.in_port(0).get_connection().set_destination(emb_bag.in_port(2))
concat_after.out_port(0).get_connection().set_source(emb_bag.out_port(0))
concat_name = concat_after.soft_get('name', concat_after.id)
rename_nodes([(concat_after, concat_name + '/TBD'), (emb_bag, concat_name)])
# remove this sub-graph since a lot of matchings will be obsolete
graph.remove_nodes_from(graph.dfs(concat_before.id, set()))