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Merged
merged 2 commits into from
Mar 7, 2019
Merged

Fix build failure #7

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37b94d0
Fix build failure
wweic Mar 2, 2019
a0ad239
Fix dict syntax
Mar 7, 2019
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3 changes: 0 additions & 3 deletions Jenkinsfile
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Original file line number Diff line number Diff line change
Expand Up @@ -98,7 +98,6 @@ stage('Build') {
echo set\\(USE_GRAPH_RUNTIME ON\\) >> config.cmake
echo set\\(USE_STACKVM_RUNTIME ON\\) >> config.cmake
echo set\\(USE_GRAPH_RUNTIME_DEBUG ON\\) >> config.cmake
echo set\\(USE_ANTLR ON\\) >> config.cmake
echo set\\(USE_BLAS openblas\\) >> config.cmake
echo set\\(CMAKE_CXX_COMPILER g++\\) >> config.cmake
echo set\\(CMAKE_CXX_FLAGS -Werror\\) >> config.cmake
Expand Down Expand Up @@ -134,7 +133,6 @@ stage('Build') {
echo set\\(USE_LLVM llvm-config-4.0\\) >> config.cmake
echo set\\(USE_NNPACK ON\\) >> config.cmake
echo set\\(NNPACK_PATH /NNPACK/build/\\) >> config.cmake
echo set\\(USE_ANTLR ON\\) >> config.cmake
echo set\\(CMAKE_CXX_COMPILER g++\\) >> config.cmake
echo set\\(CMAKE_CXX_FLAGS -Werror\\) >> config.cmake
"""
Expand All @@ -143,7 +141,6 @@ stage('Build') {
timeout(time: max_time, unit: 'MINUTES') {
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_cpp_unittest.sh"
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_python_vta.sh"
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_rust.sh"
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_golang.sh"
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_python_unittest.sh"
sh "${docker_run} tvmai/ci-cpu ./tests/scripts/task_python_integration.sh"
Expand Down
2 changes: 1 addition & 1 deletion cmake/modules/ANTLR.cmake
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Expand Up @@ -3,7 +3,7 @@ if(USE_ANTLR)
/usr/local/lib/antlr-*-complete.jar
/usr/local/Cellar/*antlr-*-complete.jar)

if(DEFINED ANTLR4)
if(ANTLR4)
# Get the first element of the list of antlr jars.
# Sort and reverse the list so the item selected is the highest
# version in lib or else in Cellar if no lib installation exists.
Expand Down
15 changes: 7 additions & 8 deletions nnvm/python/nnvm/top/nn.py
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Expand Up @@ -61,10 +61,9 @@ def schedule_log_softmax(_, outs, target):
@reg.register_compute("dense")
def compute_dense(attrs, inputs, _):
"""Compute definition of dense"""
with tvm.target.create(attrs.get_string("target")):
if attrs.get_bool("use_bias"):
return topi.nn.dense(inputs[0], inputs[1], bias=inputs[2])
return topi.nn.dense(inputs[0], inputs[1])
if attrs.get_bool("use_bias"):
return topi.nn.dense(inputs[0], inputs[1], bias=inputs[2])
return topi.nn.dense(inputs[0], inputs[1])

@reg.register_schedule("dense")
def schedule_dense(_, outs, target):
Expand Down Expand Up @@ -313,22 +312,22 @@ def schedule_conv2d_transpose(attrs, outs, target):

@reg.register_alter_op_layout("max_pool2d")
def alter_pooling_layout_max_pool2d(attrs, inputs, tinfos):
with tvm.target.create(attrs.get_string("target")):
with tvm.target.create(attrs["target"]):
return topi.nn.max_pool2d_alter_layout(attrs, inputs, tinfos)

@reg.register_alter_op_layout("avg_pool2d")
def alter_pooling_layout_avg_pool2d(attrs, inputs, tinfos):
with tvm.target.create(attrs.get_string("target")):
with tvm.target.create(attrs["target"]):
return topi.nn.avg_pool2d_alter_layout(attrs, inputs, tinfos)

@reg.register_alter_op_layout("global_max_pool2d")
def alter_pooling_layout_global_max_pool2d(attrs, inputs, tinfos):
with tvm.target.create(attrs.get_string("target")):
with tvm.target.create(attrs["target"]):
return topi.nn.global_max_pool2d_alter_layout(attrs, inputs, tinfos)

@reg.register_alter_op_layout("global_avg_pool2d")
def alter_pooling_layout_global_avg_pool2d(attrs, inputs, tinfos):
with tvm.target.create(attrs.get_string("target")):
with tvm.target.create(attrs["target"]):
return topi.nn.global_avg_pool2d_alter_layout(attrs, inputs, tinfos)

# max_pool2d
Expand Down
2 changes: 2 additions & 0 deletions nnvm/src/pass/subgraph/tensorrt_subgraph_property.cc
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Expand Up @@ -173,6 +173,8 @@ class TensorRTSubgraphProperty: public SubgraphProperty {
this->GetAttr<std::unordered_set<std::string>>("op_names"));
}

virtual ~TensorRTSubgraphProperty() {}

private:
nnvm::Symbol RemoveFlattenOpNodes(nnvm::Symbol sym) const {
std::stack<nnvm::Node*> node_stack;
Expand Down
6 changes: 4 additions & 2 deletions nnvm/src/top/nn/nn.cc
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Expand Up @@ -194,11 +194,12 @@ inline bool BatchNormInferShape(const nnvm::NodeAttrs& attrs,
return true;
}

inline bool BatchNormCorrectLayout(const NodeAttrs& attrs,
inline bool BatchNormCorrectLayout(const NodeAttrs& attrs_const,
std::vector<TShape>* ishapes,
std::vector<Layout> *in_layouts,
const std::vector<Layout> *last_in_layouts,
std::vector<Layout> *out_layouts) {
NodeAttrs& attrs = const_cast<NodeAttrs&>(attrs_const);
const BatchNormParam& param = nnvm::get<BatchNormParam>(attrs.parsed);
CHECK_EQ(in_layouts->size(), 5U);
CHECK_EQ(last_in_layouts->size(), 5U);
Expand Down Expand Up @@ -593,11 +594,12 @@ inline bool PadInferShape(const nnvm::NodeAttrs& attrs,
return true;
}

inline bool PadCorrectLayout(const NodeAttrs& attrs,
inline bool PadCorrectLayout(const NodeAttrs& attrs_const,
std::vector<TShape>* ishapes,
std::vector<Layout>* ilayouts,
const std::vector<Layout>* last_ilayouts,
std::vector<Layout>* olayouts) {
NodeAttrs& attrs = const_cast<NodeAttrs&>(attrs_const);
const PadParam& param = nnvm::get<PadParam>(attrs.parsed);
const auto& last_layout = last_ilayouts->at(0);
Layout layout = ilayouts->at(0);
Expand Down
56 changes: 0 additions & 56 deletions topi/python/topi/cuda/pooling.py
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Expand Up @@ -131,59 +131,3 @@ def traverse(OP):

traverse(outs[0].op)
return s


@avg_pool2d_alter_layout.register(["cuda"])
def _alter_avg_pool2d_layout(attrs, inputs, tinfo):
import nnvm.symbol as sym
copy_inputs = [s for s in inputs]
new_attrs = {k : attrs[k] for k in attrs.keys()}
# NHWC -> NCHW
if attrs["layout"] != "NHWC":
return None
new_attrs["layout"] = "NCHW"
if "target" in new_attrs:
del new_attrs["target"]
return sym.avg_pool2d(*copy_inputs, **new_attrs)


@max_pool2d_alter_layout.register(["cuda"])
def _alter_max_pool2d_layout(attrs, inputs, tinfo):
import nnvm.symbol as sym
copy_inputs = [s for s in inputs]
new_attrs = {k : attrs[k] for k in attrs.keys()}
# NHWC -> NCHW
if attrs["layout"] != "NHWC":
return None
new_attrs["layout"] = "NCHW"
if "target" in new_attrs:
del new_attrs["target"]
return sym.max_pool2d(*copy_inputs, **new_attrs)


@global_max_pool2d_alter_layout.register(["cuda"])
def _alter_global_max_pool2d_layout(attrs, inputs, tinfo):
import nnvm.symbol as sym
copy_inputs = [s for s in inputs]
new_attrs = {k : attrs[k] for k in attrs.keys()}
# NHWC -> NCHW
if attrs["layout"] != "NHWC":
return None
new_attrs["layout"] = "NCHW"
if "target" in new_attrs:
del new_attrs["target"]
return sym.global_max_pool2d(*copy_inputs, **new_attrs)


@global_avg_pool2d_alter_layout.register(["cuda"])
def _alter_global_avg_pool2d_layout(attrs, inputs, tinfo):
import nnvm.symbol as sym
copy_inputs = [s for s in inputs]
new_attrs = {k : attrs[k] for k in attrs.keys()}
# NHWC -> NCHW
if attrs["layout"] != "NHWC":
return None
new_attrs["layout"] = "NCHW"
if "target" in new_attrs:
del new_attrs["target"]
return sym.global_avg_pool2d(*copy_inputs, **new_attrs)