Update submodule mindspore/akg

Enable Graph Kernel for W&D Host-Device Mode and ResNext50 on GPU
Enable akg-conv2d in yolov3_darknet on GPU

akg

@@ -1 +1 @@
-Subproject commit 83df651adb471ec229fc1732b894dd2142946233
+Subproject commit 32af460cac1bb7d76bc1fd41f5866107cfffe1b9

mindspore/_extends/graph_kernel/expanders/conv2d.py

@@ -100,12 +100,14 @@ class Conv2D(Expander):
         check_nd(stride, 4)
         n0, h0, w0, c0 = shape_0
         n1, h1, w1, c1 = shape_1
-        if n0 < N0_CHANNEL_ALIGN:
-            raise GKException("N({}) channel of first input should >= {}".format(n0, N0_CHANNEL_ALIGN))
+        if n0 <= N0_CHANNEL_ALIGN:
+            raise GKException("N({}) channel of first input should > {}".format(n0, N0_CHANNEL_ALIGN))
         if n1 < N1_CHANNEL_ALIGN:
             raise GKException("N({}) channel of second input should >= {}".format(n1, N1_CHANNEL_ALIGN))
         if c0 != c1 or c0 < C_CHANNEL_ALIGN:
             raise GKException("C channel of inputs({}, {}) should be same and >= {}".format(c0, c1, C_CHANNEL_ALIGN))
+        if stride != [1, 1, 2, 2]:
+            raise GKException("Stride H and W should be [2, 2] but got [{}, {}]".format(stride[2], stride[3]))
         # n0 pad
         n0 = ((n0 + N0_CHANNEL_ALIGN - 1) // N0_CHANNEL_ALIGN) * N0_CHANNEL_ALIGN
         # h0, w0 pad

model_zoo/official/cv/resnet/train.py

@@ -121,7 +121,8 @@ def apply_eval(eval_param):
 
 def set_graph_kernel_context(run_platform, net_name):
     if run_platform == "GPU" and net_name == "resnet101":
-        context.set_context(enable_graph_kernel=True, graph_kernel_flags="--enable_parallel_fusion")
+        context.set_context(enable_graph_kernel=True)
+        context.set_context(graph_kernel_flags="--enable_parallel_fusion --enable_expand_ops=Conv2D")
 
 if __name__ == '__main__':
     target = args_opt.device_target

model_zoo/official/cv/resnext50/eval.py

@@ -123,6 +123,10 @@ def get_result(model, top1_correct, top5_correct, img_tot):
     config.logger.info('after results=%s', results)
     return results
 
+def set_graph_kernel_context(device_target):
+    if device_target == "GPU":
+        context.set_context(enable_graph_kernel=True)
+
 @moxing_wrapper()
 def test(cloud_args=None):
     """test"""
@@ -131,6 +135,7 @@ def test(cloud_args=None):
                         device_target=config.device_target, save_graphs=False)
     if os.getenv('DEVICE_ID', "not_set").isdigit():
         context.set_context(device_id=int(os.getenv('DEVICE_ID')))
+    set_graph_kernel_context(config.device_target)
 
     # init distributed
     if config.run_distribute:

model_zoo/official/cv/resnext50/train.py

@@ -134,12 +134,17 @@ def set_parameters():
     config.logger = get_logger(config.outputs_dir, config.rank)
     return config
 
+def set_graph_kernel_context(device_target):
+    if device_target == "GPU":
+        context.set_context(enable_graph_kernel=True)
+
 @moxing_wrapper()
 def train():
     """training process"""
     set_parameters()
     if os.getenv('DEVICE_ID', "not_set").isdigit():
         context.set_context(device_id=int(os.getenv('DEVICE_ID')))
+    set_graph_kernel_context(config.device_target)
 
     # init distributed
     if config.run_distribute:

model_zoo/official/cv/yolov3_darknet53/train.py

@@ -64,7 +64,8 @@ def set_graph_kernel_context():
         context.set_context(enable_graph_kernel=True)
         context.set_context(graph_kernel_flags="--enable_parallel_fusion "
                                                "--disable_expand_ops=BatchNorm,BatchNormGrad "
-                                               "--disable_cluster_ops=ReduceMax,Reshape")
+                                               "--disable_cluster_ops=ReduceMax,Reshape "
+                                               "--enable_expand_ops=Conv2D")
 
 def network_init(args):
     devid = int(os.getenv('DEVICE_ID', '0'))

model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py

@@ -145,6 +145,8 @@ def train_and_eval(config):
 if __name__ == "__main__":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target=cfg.device_target)
+    if cfg.device_target == "GPU":
+        context.set_context(enable_graph_kernel=True)
     context.set_context(variable_memory_max_size="24GB")
     context.set_context(enable_sparse=True)
     init()