remove all torch.ones from tests (#3494)

Summary:
Pull Request resolved: #3494

Replace all torch.ones with instances of torch.randn

Reviewed By: digantdesai

Differential Revision: D56907873

fbshipit-source-id: 809b2a42ee628b6dc50b57e22ce5b7318092f8cb

backends/xnnpack/test/ops/add.py

@@ -58,17 +58,17 @@ def _test_add(self, inputs):
         )
 
     def test_fp16_add(self):
-        inputs = (torch.ones(1).to(torch.float16), torch.ones(1).to(torch.float16))
+        inputs = (torch.randn(1).to(torch.float16), torch.randn(1).to(torch.float16))
         self._test_add(inputs)
 
     def test_fp32_add(self):
-        inputs = (torch.ones(1), torch.ones(1))
+        inputs = (torch.randn(1), torch.randn(1))
         self._test_add(inputs)
 
     def test_fp32_add_constant(self):
         inputs = (torch.randn(4, 4, 4),)
         (
-            Tester(self.AddConstant(torch.ones(4, 4, 4)), inputs)
+            Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
             .export()
             .check_count({"torch.ops.aten.add.Tensor": 4})
             .to_edge()
@@ -84,7 +84,7 @@ def test_fp32_add_constant(self):
     def test_qs8_add_constant(self):
         inputs = (torch.randn(4, 4, 4),)
         (
-            Tester(self.AddConstant(torch.ones(4, 4, 4)), inputs)
+            Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
             .quantize()
             .export()
             .check_count({"torch.ops.aten.add.Tensor": 4})
@@ -95,7 +95,7 @@ def test_qs8_add_constant(self):
             .check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
             .to_executorch()
             .serialize()
-            .run_method_compare_outputs()
+            .run_method_and_compare_outputs()
         )
 
     def test_qs8_add(self):

backends/xnnpack/test/ops/cat.py

@@ -78,8 +78,8 @@ def test_fp16_cat2(self):
         Using Clamp2 because fp16 add is done in fp32 ATM. Need to fix that first.
         """
         inputs = (
-            torch.ones(1, 2, 3).to(torch.float16),
-            torch.ones(3, 2, 3).to(torch.float16),
+            torch.randn(1, 2, 3).to(torch.float16),
+            torch.randn(3, 2, 3).to(torch.float16),
         )
         self._test_cat(self.Cat2(), inputs)
 
@@ -88,9 +88,9 @@ def test_fp16_cat3(self):
         Using Clamp2 because fp16 add is done in fp32 ATM. Need to fix that first.
         """
         inputs = (
-            torch.ones(1, 2, 3).to(torch.float16),
-            torch.ones(3, 2, 3).to(torch.float16),
-            torch.ones(2, 2, 3).to(torch.float16),
+            torch.randn(1, 2, 3).to(torch.float16),
+            torch.randn(3, 2, 3).to(torch.float16),
+            torch.randn(2, 2, 3).to(torch.float16),
         )
         self._test_cat(self.Cat3(), inputs)
 
@@ -99,44 +99,44 @@ def test_fp16_cat4(self):
         Using Clamp2 because fp16 add is done in fp32 ATM. Need to fix that first.
         """
         inputs = (
-            torch.ones(1, 2, 3).to(torch.float16),
-            torch.ones(3, 2, 3).to(torch.float16),
-            torch.ones(2, 2, 3).to(torch.float16),
-            torch.ones(5, 2, 3).to(torch.float16),
+            torch.randn(1, 2, 3).to(torch.float16),
+            torch.randn(3, 2, 3).to(torch.float16),
+            torch.randn(2, 2, 3).to(torch.float16),
+            torch.randn(5, 2, 3).to(torch.float16),
         )
         self._test_cat(self.Cat4(), inputs)
 
     def test_fp32_cat2(self):
-        inputs = (torch.ones(1, 2, 3), torch.ones(3, 2, 3))
+        inputs = (torch.randn(1, 2, 3), torch.randn(3, 2, 3))
         self._test_cat(self.Cat2(), inputs)
 
     def test_fp32_cat3(self):
-        inputs = (torch.ones(1, 2, 3), torch.ones(3, 2, 3), torch.ones(2, 2, 3))
+        inputs = (torch.randn(1, 2, 3), torch.randn(3, 2, 3), torch.randn(2, 2, 3))
         self._test_cat(self.Cat3(), inputs)
 
     def test_fp32_cat4(self):
         inputs = (
-            torch.ones(1, 2, 3),
-            torch.ones(3, 2, 3),
-            torch.ones(2, 2, 3),
-            torch.ones(5, 2, 3),
+            torch.randn(1, 2, 3),
+            torch.randn(3, 2, 3),
+            torch.randn(2, 2, 3),
+            torch.randn(5, 2, 3),
         )
         self._test_cat(self.Cat4(), inputs)
 
     def test_qs8_cat2(self):
-        inputs = (torch.ones(1, 2, 3), torch.ones(3, 2, 3))
+        inputs = (torch.randn(1, 2, 3), torch.randn(3, 2, 3))
         self._test_cat(self.Cat2(), inputs, cat_num=2, quant=True)
 
     def test_qs8_cat3(self):
-        inputs = (torch.ones(1, 2, 3), torch.ones(3, 2, 3), torch.ones(2, 2, 3))
+        inputs = (torch.randn(1, 2, 3), torch.randn(3, 2, 3), torch.randn(2, 2, 3))
         self._test_cat(self.Cat3(), inputs, cat_num=3, quant=True)
 
     def test_qs8_cat4(self):
         inputs = (
-            torch.ones(1, 2, 3),
-            torch.ones(3, 2, 3),
-            torch.ones(2, 2, 3),
-            torch.ones(5, 2, 3),
+            torch.randn(1, 2, 3),
+            torch.randn(3, 2, 3),
+            torch.randn(2, 2, 3),
+            torch.randn(5, 2, 3),
         )
         self._test_cat(self.Cat4(), inputs, cat_num=4, quant=True)
 
@@ -145,11 +145,11 @@ def test_fp32_cat_unsupported(self):
         XNNPACK only supports concatenating up to 4 values, so it should not delegate here.
         """
         inputs = (
-            torch.ones(1, 2, 3),
-            torch.ones(3, 2, 3),
-            torch.ones(2, 2, 3),
-            torch.ones(5, 2, 3),
-            torch.ones(1, 2, 3),
+            torch.randn(1, 2, 3),
+            torch.randn(3, 2, 3),
+            torch.randn(2, 2, 3),
+            torch.randn(5, 2, 3),
+            torch.randn(1, 2, 3),
         )
         (
             Tester(self.Cat5(), inputs)
@@ -169,7 +169,7 @@ def forward(self, x, y):
             return torch.cat([x, y], -1)
 
     def test_fp32_cat_negative_dim(self):
-        inputs = (torch.ones(3, 2, 3), torch.ones(3, 2, 1))
+        inputs = (torch.randn(3, 2, 3), torch.randn(3, 2, 1))
         self._test_cat(self.CatNegativeDim(), inputs)
 
     class CatNhwc(torch.nn.Module):

backends/xnnpack/test/ops/div.py

@@ -43,15 +43,21 @@ def _test_div(self, inputs):
         )
 
     def test_fp16_div(self):
-        inputs = (torch.ones(1).to(torch.float16), torch.ones(1).to(torch.float16))
+        # Adding 4 to move distribution away from 0, 4 Std Dev should be far enough
+        inputs = (
+            (torch.randn(1) + 4).to(torch.float16),
+            (torch.randn(1) + 4).to(torch.float16),
+        )
         self._test_div(inputs)
 
     def test_fp32_div(self):
-        inputs = (torch.ones(1), torch.ones(1))
+        # Adding 4 to move distribution away from 0, 4 Std Dev should be far enough
+        inputs = (torch.randn(1) + 4, torch.randn(1) + 4)
         self._test_div(inputs)
 
     def test_fp32_div_single_input(self):
-        inputs = (torch.ones(1),)
+        # Adding 4 to move distribution away from 0, 4 Std Dev should be far enough
+        inputs = (torch.randn(1) + 4,)
         (
             Tester(self.DivSingleInput(), inputs)
             .export()

backends/xnnpack/test/ops/maxpool2d.py

@@ -111,7 +111,7 @@ def forward(self, x):
 
         # Parameter order is kernel_size, stride, padding.
         for maxpool_params in [(4,), (4, 2), (4, 2, 2)]:
-            inputs = (torch.ones(1, 2, 8, 8),)
+            inputs = (torch.randn(1, 2, 8, 8),)
             (
                 Tester(MaxPool(maxpool_params), inputs)
                 .quantize()

backends/xnnpack/test/ops/pow.py

@@ -53,7 +53,7 @@ def test_fp32_pow_unsupported(self):
         attempt to delegate other powers.
         """
 
-        inputs = (torch.ones(5),)
+        inputs = (torch.randn(5),)
         (
             Tester(self.Pow(3), inputs)
             .export()

backends/xnnpack/test/ops/sigmoid.py

@@ -36,7 +36,7 @@ def _test_sigmoid(self, inputs):
         )
 
     def test_fp16_sigmoid(self):
-        inputs = (torch.ones(4).to(torch.float16),)
+        inputs = (torch.randn(4).to(torch.float16),)
         self._test_sigmoid(inputs)
 
     def test_fp32_sigmoid(self):