diff --git a/mindspore/ccsrc/kernel/gpu/nn/pooling_grad_gpu_kernel.h b/mindspore/ccsrc/kernel/gpu/nn/pooling_grad_gpu_kernel.h index 6c10635c0ce37253e136805467bfdd9dd2a81e75..b2dc7d5e67ec289f2058a7577cb06cc3f2be97e6 100644 --- a/mindspore/ccsrc/kernel/gpu/nn/pooling_grad_gpu_kernel.h +++ b/mindspore/ccsrc/kernel/gpu/nn/pooling_grad_gpu_kernel.h @@ -85,7 +85,7 @@ class PoolingGradGpuFwdKernel : public GpuKernel { padded_descriptor_, padded, &beta, padded_descriptor_, padded_dx), "cudnnPoolingBackward failed"); - CalPadGrad(padded_size_ / sizeof(T), padded_dx, n_, c_, old_height_, old_width_, old_height_ + pad_height_, + CalPadGrad(output_size_ / sizeof(T), padded_dx, n_, c_, old_height_, old_width_, old_height_ + pad_height_, old_width_ + pad_width_, pad_top_, pad_left_, dx, reinterpret_cast(stream_ptr)); } else { CHECK_CUDNN_RET_WITH_EXCEPT( diff --git a/mindspore/ccsrc/pipeline/init.cc b/mindspore/ccsrc/pipeline/init.cc index dc59d117c5f26717e81510b653f46a1562791608..c6a68369a32e00d89ea909287020f2151e24f99c 100644 --- a/mindspore/ccsrc/pipeline/init.cc +++ b/mindspore/ccsrc/pipeline/init.cc @@ -139,16 +139,10 @@ PYBIND11_MODULE(_c_expression, m) { .def("set_save_ms_model_flag", &mindspore::MsContext::set_save_ms_model_flag, "Set whether to save ms model.") .def("get_save_ms_model_path", &mindspore::MsContext::save_ms_model_path, "Get path to save ms model.") .def("set_save_ms_model_path", &mindspore::MsContext::set_save_ms_model_path, "Set path to save ms model") - .def("get_enable_gpu_summary", &mindspore::MsContext::enable_gpu_summary, "Get whether to enable gpu summary.") - .def("set_enable_gpu_summary", &mindspore::MsContext::set_enable_gpu_summary, "Set whether to enable gpu summary.") .def("get_enable_dump", &mindspore::MsContext::enable_dump, "Get whether to enable dump.") .def("set_enable_dump", &mindspore::MsContext::set_enable_dump, "Set whether to enable dump.") .def("get_save_dump_path", &mindspore::MsContext::save_dump_path, "Get path to dump.") .def("set_save_dump_path", &mindspore::MsContext::set_save_dump_path, "Set path to dump.") - .def("get_enable_dynamic_mem_pool", &mindspore::MsContext::enable_dynamic_mem_pool, - "Get whether to enable dynamic mem pool.") - .def("set_enable_dynamic_mem_pool", &mindspore::MsContext::set_enable_dynamic_mem_pool, - "Set whether to enable dynamic mem pool.") .def("set_graph_memory_max_size", &mindspore::MsContext::set_graph_memory_max_size, "set graph memory max size.") .def("set_variable_memory_max_size", &mindspore::MsContext::set_variable_memory_max_size, "set variable memory max size"); diff --git a/mindspore/context.py b/mindspore/context.py index 7db781be5a8002e61057ac2f8786ba8f92b3aa5e..bcc6ed550d7a578c3adc1082a74804e26ca634cf 100644 --- a/mindspore/context.py +++ b/mindspore/context.py @@ -265,14 +265,6 @@ class _Context: def save_ms_model_path(self, save_ms_model_path): self._context_handle.set_save_ms_model_path(save_ms_model_path) - @property - def enable_gpu_summary(self): - return self._context_handle.get_enable_gpu_summary() - - @enable_gpu_summary.setter - def enable_gpu_summary(self, enable_gpu_summary): - self._context_handle.set_enable_gpu_summary(enable_gpu_summary) - @property def enable_auto_mixed_precision(self): return self._context_handle.get_auto_mixed_precision_flag() @@ -315,14 +307,6 @@ class _Context: """Sets whether to save the network class name in the scope.""" self._thread_local_info.reserve_class_name_in_scope = reserve_class_name_in_scope - @property - def enable_dynamic_memory(self): - return self._context_handle.get_enable_dynamic_mem_pool() - - @enable_dynamic_memory.setter - def enable_dynamic_memory(self, enable_dynamic_memory): - self._context_handle.set_enable_dynamic_mem_pool(enable_dynamic_memory) - @property def graph_memory_max_size(self): return None @@ -485,9 +469,9 @@ def reset_auto_parallel_context(): @args_type_check(mode=int, precompile_only=bool, device_target=str, device_id=int, enable_ir_fusion=bool, save_graphs=bool, enable_task_sink=bool, save_graphs_path=str, enable_loop_sink=bool, - enable_mem_reuse=bool, save_ms_model=bool, save_ms_model_path=str, enable_gpu_summary=bool, + enable_mem_reuse=bool, save_ms_model=bool, save_ms_model_path=str, enable_auto_mixed_precision=bool, enable_dump=bool, save_dump_path=str, - enable_reduce_precision=bool, enable_dynamic_memory=bool, graph_memory_max_size=str, + enable_reduce_precision=bool, graph_memory_max_size=str, variable_memory_max_size=str) def set_context(**kwargs): """ @@ -521,7 +505,6 @@ def set_context(**kwargs): enable_mem_reuse (bool): Whether to enable memory reuse. Default: True. save_ms_model (bool): Whether to save lite model converted by graph. Default: False. save_ms_model_path (str): Path to save converted lite model. Default: "." - enable_gpu_summary (bool): Whether to enable gpu summary. Default: True. save_graphs_path (str): Path to save graphs. Default: "." enable_auto_mixed_precision (bool): Whether to enable auto mixed precision. Default: True. reserve_class_name_in_scope (bool) : Whether to save the network class name in the scope. Default: True. @@ -530,7 +513,6 @@ def set_context(**kwargs): save_dump_path (str): When the program is executed on Ascend, operators can dump data here. The root dump path is configured in /home/HwHiAiUser/ide_daemon/ide_daemon.cfg. So the real dump path is "{configured root dump path}/{`save_dump_path`}". Default: ".". - enable_dynamic_memory (bool): Whether to enable dynamic memory. Default: False. graph_memory_max_size (str): Sets graph memory max size. Default: "26GB". variable_memory_max_size (str): Sets variable memory max size. Default: "5GB". @@ -547,10 +529,8 @@ def set_context(**kwargs): >>> context.set_context(enable_mem_reuse=True) >>> context.set_context(enable_reduce_precision=True) >>> context.set_context(save_ms_model=True, save_ms_model_path=".") - >>> context.set_context(enable_gpu_summary=False) >>> context.set_context(enable_dump=True, save_dump_path=".") >>> context.set_context(reserve_class_name_in_scope=True) - >>> context.set_context(enable_dynamic_memory=True) >>> context.set_context(graph_memory_max_size="25GB") >>> context.set_context(variable_memory_max_size="6GB") >>> context.set_context(mode=context.GRAPH_MODE, diff --git a/tests/st/networks/test_gpu_resnet.py b/tests/st/networks/test_gpu_resnet.py index a045f97501343183f7b1da9247b413092c0a710a..afae359b4e566209455512329f298f0f534ff83e 100644 --- a/tests/st/networks/test_gpu_resnet.py +++ b/tests/st/networks/test_gpu_resnet.py @@ -34,6 +34,8 @@ from mindspore.nn import TrainOneStepCell, WithLossCell from mindspore.nn import Dense from mindspore import amp +context.set_context(mode=context.GRAPH_MODE, device_target="GPU") + def random_normal_init(shape, mean=0.0, stddev=0.01, seed=None): init_value = np.ones(shape).astype(np.float32) * 0.01 @@ -324,7 +326,6 @@ def resnet50(num_classes): @pytest.mark.platform_x86_gpu_training @pytest.mark.env_onecard def test_trainTensor(num_classes=10, epoch=8, batch_size=1): - context.set_context(mode=context.GRAPH_MODE, device_target="GPU") net = resnet50(num_classes) lr = 0.1 momentum = 0.9 @@ -345,8 +346,6 @@ def test_trainTensor(num_classes=10, epoch=8, batch_size=1): @pytest.mark.platform_x86_gpu_training @pytest.mark.env_onecard def test_trainTensor_amp(num_classes=10, epoch=18, batch_size=16): - context.set_context(mode=context.GRAPH_MODE, device_target="GPU", enable_mem_reuse=False, - enable_dynamic_memory=False) net = resnet50(num_classes) lr = 0.1 momentum = 0.9