another attempt to fix intermittent test failure

sony · Oct 21, 2024 · 8c444b9 · 8c444b9
1 parent bba3bd1
commit 8c444b9
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Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/tests/keras_tests/function_tests/test_hessian_info_calculator.py b/tests/keras_tests/function_tests/test_hessian_info_calculator.py
@@ -102,7 +102,7 @@ def get_expected_shape(t_shape, granularity, node_type, num_scores):
 
 class TestHessianInfoCalculatorBase(unittest.TestCase):
 
-    def _setup(self, layer, input_shape=(1, 8, 8, 3)):
+    def _setup(self, layer, input_shape=(1, 16, 16, 3)):
         in_model = basic_model(input_shape, layer=layer)
         keras_impl = KerasImplementation()
         _repr_dataset = functools.partial(representative_dataset,

diff --git a/tests/keras_tests/function_tests/test_hessian_service.py b/tests/keras_tests/function_tests/test_hessian_service.py
@@ -55,7 +55,7 @@ def multiple_act_nodes_model(input_shape):
 def get_representative_dataset_fn(n_iters=10):
     def f():
         for _ in range(n_iters):
-            yield [np.random.randn(2, 8, 8, 3).astype(np.float32)]
+            yield [np.random.randn(2, 16, 16, 3).astype(np.float32)]
     return f
 
 
@@ -65,7 +65,7 @@ def tearDown(self) -> None:
 
     def setUp(self):
 
-        input_shape = (8, 8, 3)
+        input_shape = (16, 16, 3)
         self.float_model = basic_model(input_shape)
         self.keras_impl = KerasImplementation()
         self.graph = prepare_graph_with_configs(self.float_model,
@@ -155,7 +155,7 @@ def test_fetch_required_zero(self):
         self.assertEqual(hessian[node.name].shape[0], 0, "Expecting an empty Hessian scores list.")
 
     def test_fetch_multiple_nodes(self):
-        input_shape = (8, 8, 3)
+        input_shape = (16, 16, 3)
         self.float_model = multiple_act_nodes_model(input_shape)
         self.keras_impl = KerasImplementation()
         self.graph = prepare_graph_with_configs(self.float_model,

diff --git a/tests/pytorch_tests/function_tests/test_hessian_info_calculator.py b/tests/pytorch_tests/function_tests/test_hessian_info_calculator.py
@@ -56,7 +56,7 @@ def __init__(self):
         self.conv2 = Conv2d(3, 3, kernel_size=3, stride=1, padding=1)
         self.bn2 = BatchNorm2d(3)
         self.relu2 = ReLU()
-        self.dense = Linear(8, 7)
+        self.dense = Linear(16, 7)
 
     def forward(self, inp):
         x = self.conv1(inp)
@@ -79,7 +79,7 @@ def __init__(self):
         self.bn2 = BatchNorm2d(3)
         self.relu2 = ReLU()
         self.hswish = Hardswish()
-        self.dense = Linear(8, 7)
+        self.dense = Linear(16, 7)
 
     def forward(self, inp):
         x = self.conv1(inp)
@@ -145,7 +145,7 @@ def __init__(self, unit_test, model, n_iters=10):
         self.n_iters = n_iters
 
     def create_inputs_shape(self):
-        return [[self.val_batch_size, 3, 8, 8]]
+        return [[self.val_batch_size, 3, 16, 16]]
 
     @staticmethod
     def generate_inputs(input_shapes):

diff --git a/tests/pytorch_tests/function_tests/test_hessian_service.py b/tests/pytorch_tests/function_tests/test_hessian_service.py
@@ -60,7 +60,7 @@ def forward(self, x):
 
 def representative_dataset():
     for _ in range(2):
-        yield [np.random.randn(2, 3, 8, 8).astype(np.float32)]
+        yield [np.random.randn(2, 3, 16, 16).astype(np.float32)]
 
 
 class BaseHessianServiceTest(BasePytorchTest):