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cjolivier01 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 4ad0bba fix crash when profiler not enabled (#10306)
4ad0bba is described below
commit 4ad0bba7a0d06760ad657251193e823387019287
Author: Chris Olivier <cjolivie...@gmail.com>
AuthorDate: Fri Mar 30 17:57:39 2018 -0700
fix crash when profiler not enabled (#10306)
* fix crash when profiler not enabled
* fix
* Update graph_executor.cc
* Update graph_executor.cc
* use nosetests to try and prevent thehang
* shutdown after GPU pass
* remove temp
* remove temp
---
src/engine/threaded_engine.h | 3 ++-
src/executor/graph_executor.cc | 4 +++-
tests/python/gpu/test_operator_gpu.py | 43 ++++++++++++++++++-----------------
tests/python/gpu/test_tvm_bridge.py | 3 ++-
4 files changed, 29 insertions(+), 24 deletions(-)
diff --git a/src/engine/threaded_engine.h b/src/engine/threaded_engine.h
index d72784d..673fa3b 100644
--- a/src/engine/threaded_engine.h
+++ b/src/engine/threaded_engine.h
@@ -398,7 +398,8 @@ class ThreadedEngine : public Engine {
}
int bulk_size() const override {
- return profiler::Profiler::Get()->AggregateRunning() ? 0 :
BulkStatusStore::Get()->bulk_size;
+ const profiler::Profiler *prof = profiler::Profiler::Get();
+ return (prof && prof->AggregateRunning()) ? 0 :
BulkStatusStore::Get()->bulk_size;
}
int set_bulk_size(int bulk_size) override {
diff --git a/src/executor/graph_executor.cc b/src/executor/graph_executor.cc
index fa5931e..32772f2 100644
--- a/src/executor/graph_executor.cc
+++ b/src/executor/graph_executor.cc
@@ -1348,8 +1348,9 @@ void GraphExecutor::InitOpSegs() {
// Generate segments based on the graph structure
bool prefer_bulk_exec_inference =
dmlc::GetEnv("MXNET_EXEC_BULK_EXEC_INFERENCE", true);
// Whether to perform bulk exec for training
+ const profiler::Profiler *prof = profiler::Profiler::Get();
bool prefer_bulk_exec = dmlc::GetEnv("MXNET_EXEC_BULK_EXEC_TRAIN", 1)
- && !profiler::Profiler::Get()->AggregateEnabled();
+ && (!prof || !prof->AggregateEnabled());
bool is_training = num_forward_nodes_ != total_num_nodes;
@@ -1362,6 +1363,7 @@ void GraphExecutor::InitOpSegs() {
}
}
+
void GraphExecutor::BulkTrainingOpSegs(size_t total_num_nodes) {
// The maximum number of node in a segment executed in bulk
size_t num_nodes_threshold =
dmlc::GetEnv("MXNET_EXEC_BULK_EXEC_MAX_NODE_TRAIN", 15);
diff --git a/tests/python/gpu/test_operator_gpu.py
b/tests/python/gpu/test_operator_gpu.py
index cb422e2..1987041 100644
--- a/tests/python/gpu/test_operator_gpu.py
+++ b/tests/python/gpu/test_operator_gpu.py
@@ -904,81 +904,81 @@ def test_global_pooling():
kernel = (4,)
pad = (2,)
stride = (2,)
-
+
ctx_list = []
sym_list = []
-
+
pooling_convention = 'valid'
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=False, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=False, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=True, name='pool'))
-
+
check_consistency(sym_list, ctx_list)
-
+
def test_2d_pooling(pool_type):
data = (2, 3, 20, 20)
kernel = (4, 4)
pad = (2, 2)
stride = (2, 2)
-
+
ctx_list = []
sym_list = []
-
+
pooling_convention = 'valid'
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling_v1(kernel=kernel, pad=pad,
stride=stride, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling_v1(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.cpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=False, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=False, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pad=pad, stride=stride,
pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=True, name='pool'))
-
+
ctx_list.append({'ctx': mx.gpu(0), 'pool_data': data, 'type_dict':
{'pool_data': np.float32}})
sym_list.append(mx.sym.Pooling(kernel=kernel, pool_type=pool_type,
pooling_convention=pooling_convention,
global_pool=True, cudnn_off=True, name='pool'))
-
+
check_consistency(sym_list, ctx_list)
test_1d_pooling('max')
@@ -1784,3 +1784,4 @@ def test_kernel_error_checking():
if __name__ == '__main__':
import nose
nose.runmodule()
+
diff --git a/tests/python/gpu/test_tvm_bridge.py
b/tests/python/gpu/test_tvm_bridge.py
index 69a713d..4b1105a 100644
--- a/tests/python/gpu/test_tvm_bridge.py
+++ b/tests/python/gpu/test_tvm_bridge.py
@@ -62,4 +62,5 @@ def test_tvm_bridge():
if __name__ == "__main__":
- test_tvm_bridge()
+ import nose
+ nose.runmodule()
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