update akg && set random seed for stitch case

akg

@@ -1 +1 @@
-Subproject commit f1b98639da49b0ff6a9aed61bc564f08c040fca4
+Subproject commit e869bb0010f9fc071a94f8def23655ce0acad2d2

model_zoo/official/nlp/bert/run_pretrain.py

@@ -136,7 +136,7 @@ def _set_graph_kernel_context(device_target, enable_graph_kernel, is_auto_enable
     if enable_graph_kernel == "true" or is_auto_enable_graph_kernel:
         if device_target == 'GPU':
             context.set_context(enable_graph_kernel=True,
-                                graph_kernel_flags="--enable_stitch_fusion=true --enable_parallel_fusion=true")
+                                graph_kernel_flags="--enable_stitch_fusion=false --enable_parallel_fusion=true")
         else:
             logger.warning('Graph kernel only supports GPU back-end now, run with graph kernel off.')
 

tests/st/ops/graph_kernel/test_dropoutgrad_reducesum_stitch.py

@@ -73,6 +73,7 @@ def get_dropoutgrad_reducesum_output(x, y, z, enable_stitch_fusion):
 
 
 def test_dropoutgrad_reducesum(shape, dtype):
+    np.random.seed(0)
     x = Tensor(np.random.normal(0, 1, shape).astype(dtype))
     y = Tensor(np.random.normal(0, 1, shape).astype(dtype))
     z = Tensor(np.random.normal(0, 1, shape).astype(dtype))

tests/st/ops/graph_kernel/test_layernorm_stitch.py

@@ -70,6 +70,7 @@ def get_layernorm_output(x, y, z, enable_stitch_fusion):
 
 
 def test_layernorm(shape1, shape2, dtype):
+    np.random.seed(0)
     x = Tensor(np.random.normal(0, 1, shape1).astype(dtype))
     y = Tensor(np.random.normal(0, 1, shape1).astype(dtype))
     z = Tensor(np.random.normal(0, 1, shape2).astype(dtype))

tests/st/ops/graph_kernel/test_softmax_stitch.py

@@ -77,6 +77,7 @@ def get_softmax_output(x, y, enable_stitch_fusion):
 
 
 def test_softmax(shape, dtype):
+    np.random.seed(0)
     x = Tensor(np.random.normal(0, 1, shape).astype(dtype))
     y = Tensor(np.random.normal(0, 1, shape).astype(dtype))
     expect = get_softmax_output(x, y, False)