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Commit 0d693fc3 authored by Nick Korovaiko's avatar Nick Korovaiko Committed by Robert Kimball
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fix Klockwork warnings CPU part 1 (#1902) 

* fix Klockwork warnings CPU part 1

* fix spelling error

* fix a typo
parent 92c1d504
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Showing with 45 additions and 23 deletions
src/ngraph/runtime/cpu/pass/cpu_collapse_dims.cpp
View file @ 0d693fc3
......@@ -98,7 +98,7 @@ static void collapse_dims(std::vector<size_t>& shape,
static bool collapse_broadcast(std::shared_ptr<Node> n)
{
bool replaced = false;
auto node = std::dynamic_pointer_cast<op::Broadcast>(n).get();
auto node = std::static_pointer_cast<op::Broadcast>(n).get();
auto input_shape = node->get_argument(0)->get_shape();
auto output_shape = node->get_shape();
auto operated_axes = node->get_broadcast_axes();
......@@ -147,7 +147,7 @@ template <typename T>
static bool collapse_reduction(std::shared_ptr<Node> n)
{
bool replaced = false;
auto node = std::dynamic_pointer_cast<T>(n).get();
auto node = std::static_pointer_cast<T>(n).get();
auto input_shape = node->get_argument(0)->get_shape();
auto output_shape = node->get_shape();
auto operated_axes = node->get_reduction_axes();
......
src/ngraph/runtime/cpu/pass/cpu_concat_inputs.cpp
View file @ 0d693fc3
......@@ -82,10 +82,10 @@ void ngraph::runtime::cpu::pass::ConcatInputs::concat_lstm_inputs()
std::shared_ptr<Node> bias =
std::make_shared<op::Add>(pattern_map[bias1], pattern_map[bias2]);
auto lstm_node = pattern_map[lstm_node_label]->get_arguments()[0];
auto batch_size = std::dynamic_pointer_cast<op::Lstm>(lstm_node)->get_batch_size();
auto feature_size =
std::dynamic_pointer_cast<op::Lstm>(lstm_node)->get_src_iter_feature_size();
auto lstm_node = std::static_pointer_cast<op::Lstm>(
pattern_map[lstm_node_label]->get_arguments()[0]);
auto batch_size = lstm_node->get_batch_size();
auto feature_size = lstm_node->get_src_iter_feature_size();
auto lstm_mkldnn_node = std::make_shared<op::Lstm>(
src_layer, src_iter, pattern_map[weights_i2h], pattern_map[weights_h2h], bias);
......@@ -105,6 +105,7 @@ void ngraph::runtime::cpu::pass::ConcatInputs::concat_lstm_inputs()
for (auto& goes : lstm_node->get_outputs().at(0).get_inputs())
{
auto goe_node = std::dynamic_pointer_cast<op::GetOutputElement>(goes->get_node());
NGRAPH_ASSERT(goe_node);
lstm_outputs.insert(goes->get_node());
// first output node of lstm
if (goe_node->get_n() == 0)
......
src/ngraph/runtime/cpu/pass/cpu_fusion.cpp
View file @ 0d693fc3
......@@ -309,6 +309,11 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_fprop_bn()
// get epsilon value
auto eps_ptr = std::dynamic_pointer_cast<op::Constant>(pattern_map[eps_label]);
if (!eps_ptr)
{
NGRAPH_DEBUG << "Eps must be a constant";
return false;
}
double epsilon = *(reinterpret_cast<const double*>(eps_ptr->get_data_ptr()));
auto bn_node = std::make_shared<op::BatchNormTraining>(
epsilon, pattern_map[gamma_label], pattern_map[beta_label], pattern_map[input]);
......@@ -408,12 +413,17 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_zero_padded_reshaped_conv(
auto pattern_map = m.get_pattern_map();
auto pad_value_op = std::dynamic_pointer_cast<op::Constant>(pattern_map[pad_value]);
if (!pad_value_op)
{
NGRAPH_DEBUG << "Pad value must be a constant";
return false;
}
const auto& matched_conv =
std::dynamic_pointer_cast<op::Convolution>(pattern_map[conv_label]);
const auto& matched_pad = std::dynamic_pointer_cast<op::Pad>(pattern_map[pad_label]);
std::static_pointer_cast<op::Convolution>(pattern_map[conv_label]);
const auto& matched_pad = std::static_pointer_cast<op::Pad>(pattern_map[pad_label]);
const auto& matched_reshape =
std::dynamic_pointer_cast<op::Reshape>(pattern_map[reshape_label]);
std::static_pointer_cast<op::Reshape>(pattern_map[reshape_label]);
const auto& input_order = matched_reshape->get_input_order();
auto hoisted_reshape_output_shape =
......@@ -485,10 +495,15 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_zero_padded_conv()
auto pattern_map = m.get_pattern_map();
auto pad_value_op = std::dynamic_pointer_cast<op::Constant>(pattern_map[pad_value]);
if (!pad_value_op)
{
NGRAPH_DEBUG << "Pad value must be a constant";
return false;
}
const auto& matched_conv =
std::dynamic_pointer_cast<op::Convolution>(pattern_map[conv_label]);
const auto& matched_pad = std::dynamic_pointer_cast<op::Pad>(pattern_map[pad_label]);
std::static_pointer_cast<op::Convolution>(pattern_map[conv_label]);
const auto& matched_pad = std::static_pointer_cast<op::Pad>(pattern_map[pad_label]);
if (!zero_padded_conv_consistency_check(m.get_match_root(),
pad_value_op,
......@@ -550,10 +565,15 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_zero_padded_conv_backprop_
auto pattern_map = m.get_pattern_map();
auto pad_value_op = std::dynamic_pointer_cast<op::Constant>(pattern_map[pad_value]);
if (!pad_value_op)
{
NGRAPH_DEBUG << "Pad value must be a constant";
return false;
}
const auto& matched_conv =
std::dynamic_pointer_cast<op::ConvolutionBackpropFilters>(pattern_map[conv_label]);
const auto& matched_pad = std::dynamic_pointer_cast<op::Pad>(pattern_map[pad_label]);
std::static_pointer_cast<op::ConvolutionBackpropFilters>(pattern_map[conv_label]);
const auto& matched_pad = std::static_pointer_cast<op::Pad>(pattern_map[pad_label]);
if (!zero_padded_conv_consistency_check(m.get_match_root(),
pad_value_op,
......@@ -615,7 +635,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias()
<< m.get_match_root()->get_name();
auto pattern_map = m.get_pattern_map();
auto conv = std::dynamic_pointer_cast<op::Convolution>(m.get_match_root()->get_argument(0));
auto conv = std::static_pointer_cast<op::Convolution>(m.get_match_root()->get_argument(0));
if (conv->get_input_shape(0).size() == 4)
{
auto bias = m.get_match_root()->get_argument(1)->get_argument(0);
......@@ -668,7 +688,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias_bprop()
auto pattern_map = m.get_pattern_map();
auto conv_bprop =
std::dynamic_pointer_cast<op::ConvolutionBackpropFilters>(m.get_match_root());
std::static_pointer_cast<op::ConvolutionBackpropFilters>(m.get_match_root());
if (conv_bprop->get_input_shape(0).size() == 4 &&
conv_bprop->get_input_shape(1).size() == 4 &&
......@@ -750,7 +770,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_batch_norm_relu()
<< m.get_match_root()->get_name();
auto pattern_map = m.get_pattern_map();
auto m_bn = std::dynamic_pointer_cast<op::BatchNormTraining>(
auto m_bn = std::static_pointer_cast<op::BatchNormTraining>(
m.get_match_root()->get_argument(0)->get_inputs().at(0).get_output().get_node());
// as of now, only MKLDNN supports this fusion
......@@ -766,6 +786,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_batch_norm_relu()
for (auto bn_in : m_bn->get_output_inputs(0))
{
auto mgoe = std::dynamic_pointer_cast<op::GetOutputElement>(bn_in->get_node());
NGRAPH_ASSERT(mgoe);
mgoes[mgoe->get_n()] = mgoe;
}
......@@ -881,7 +902,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_relu()
NGRAPH_DEBUG << "In a callback for construct_conv_relu against "
<< m.get_match_root()->get_name();
auto conv = std::dynamic_pointer_cast<op::Convolution>(m.get_match_root()->get_argument(0));
auto conv = std::static_pointer_cast<op::Convolution>(m.get_match_root()->get_argument(0));
// These checks are to make sure a MKLDNN Convolution kernel can be used.
bool data_dilated = false;
......@@ -949,7 +970,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias_relu()
<< m.get_match_root()->get_name();
auto conv =
std::dynamic_pointer_cast<op::ConvolutionBias>(m.get_match_root()->get_argument(0));
std::static_pointer_cast<op::ConvolutionBias>(m.get_match_root()->get_argument(0));
// These checks are to make sure a MKLDNN Convolution kernel can be used.
bool data_dilated = false;
......@@ -1113,7 +1134,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_add_relu()
<< m.get_match_root()->get_name();
auto conv_m =
std::dynamic_pointer_cast<op::ConvolutionAdd>(m.get_match_root()->get_argument(0));
std::static_pointer_cast<op::ConvolutionAdd>(m.get_match_root()->get_argument(0));
if (conv_m->get_users().size() > 1)
{
NGRAPH_DEBUG << "Convolution has more than one user";
......@@ -1255,7 +1276,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias_add_relu()
<< m.get_match_root()->get_name();
auto conv_m =
std::dynamic_pointer_cast<op::ConvolutionBiasAdd>(m.get_match_root()->get_argument(0));
std::static_pointer_cast<op::ConvolutionBiasAdd>(m.get_match_root()->get_argument(0));
if (conv_m->get_users().size() > 1)
{
NGRAPH_DEBUG << "Convolution has more than one user";
......@@ -1395,7 +1416,7 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_bounded_relu()
return false;
}
auto alpha_const_op = std::dynamic_pointer_cast<op::Constant>(pattern_map[alpha]);
auto alpha_const_op = std::static_pointer_cast<op::Constant>(pattern_map[alpha]);
float alpha_val = *(static_cast<float const*>(alpha_const_op->get_data_ptr()));
NGRAPH_DEBUG << "relu_input: " << pattern_map[relu_input] << " min_val: "
<< *(static_cast<float const*>(alpha_const_op->get_data_ptr()));
......@@ -1437,8 +1458,8 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias_folded_batch_nor
<< m.get_match_root()->get_name();
auto pattern_map = m.get_pattern_map();
auto m_bn = std::dynamic_pointer_cast<op::BatchNormInference>(m.get_match_root());
auto m_conv = std::dynamic_pointer_cast<op::ConvolutionBias>(m_bn->get_argument(2));
auto m_bn = std::static_pointer_cast<op::BatchNormInference>(m.get_match_root());
auto m_conv = std::static_pointer_cast<op::ConvolutionBias>(m_bn->get_argument(2));
if (m_conv->get_users().size() > 1)
{
......
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