Round simple stats to avoid minute differences

- Seems like the regression tests are failing due to extremely small differences in the statistics like 1e-9 difference. Not sure what's causing this issue though. Signed-off-by: Fabrice Normandin <[email protected]>
mila-iqia · May 31, 2024 · f37b503 · f37b503
1 parent 76eb22f
commit f37b503
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Showing 5 changed files with 24 additions and 25 deletions.
diff --git a/project/conftest.py b/project/conftest.py
@@ -183,9 +183,6 @@ def accelerator(request: pytest.FixtureRequest):
     return accelerator
 
 
-_cuda_available = torch.cuda.is_available()
-
-
 @pytest.fixture(
     scope="session",
     params=None,

diff --git a/project/datamodules/datamodules_test/test_first_batch/cifar10.yaml b/project/datamodules/datamodules_test/test_first_batch/cifar10.yaml
@@ -1,20 +1,20 @@
 '0':
   device: cpu
   hash: 1082905456378942323
-  max: 2.125603675842285
-  mean: -0.007423439994454384
-  min: -1.9888888597488403
+  max: 2.1256
+  mean: -0.00742
+  min: -1.98889
   shape:
   - 128
   - 3
   - 32
   - 32
-  sum: -2919.015380859375
+  sum: -2919.01538
 '1':
   device: cpu
   hash: 3692171093056153318
   max: 9
-  mean: 4.5546875
+  mean: 4.55469
   min: 0
   shape:
   - 128

diff --git a/project/datamodules/datamodules_test/test_first_batch/fashion_mnist.yaml b/project/datamodules/datamodules_test/test_first_batch/fashion_mnist.yaml
@@ -1,9 +1,9 @@
 '0':
   device: cpu
   hash: -3706536913713083016
-  max: 2.821486711502075
-  mean: 0.47488248348236084
-  min: -0.4242129623889923
+  max: 2.82149
+  mean: 0.47488
+  min: -0.42421
   shape:
   - 128
   - 1
@@ -14,7 +14,7 @@
   device: cpu
   hash: -4023601292826392021
   max: 9
-  mean: 4.5546875
+  mean: 4.55469
   min: 0
   shape:
   - 128

diff --git a/project/datamodules/datamodules_test/test_first_batch/mnist.yaml b/project/datamodules/datamodules_test/test_first_batch/mnist.yaml
@@ -1,20 +1,20 @@
 '0':
   device: cpu
   hash: 4338584025941619046
-  max: 2.821486711502075
-  mean: 0.014241953380405903
-  min: -0.4242129623889923
+  max: 2.82149
+  mean: 0.01424
+  min: -0.42421
   shape:
   - 128
   - 1
   - 28
   - 28
-  sum: 1429.20849609375
+  sum: 1429.2085
 '1':
   device: cpu
   hash: 1596942422053415325
   max: 9
-  mean: 4.2421875
+  mean: 4.24219
   min: 0
   shape:
   - 128

diff --git a/project/utils/tensor_regression.py b/project/utils/tensor_regression.py
@@ -20,6 +20,8 @@
 
 logger = get_logger(__name__)
 
+PRECISION = 5
+
 
 @functools.singledispatch
 def to_ndarray(v: Any) -> np.ndarray | None:
@@ -360,10 +362,10 @@ def ndarray_simple_attributes(array: np.ndarray) -> dict:
     return {
         "shape": tuple(array.shape),
         "hash": _hash(array),
-        "min": array.min().item(),
-        "max": array.max().item(),
-        "sum": array.sum().item(),
-        "mean": array.mean(),
+        "min": round(array.min().item(), PRECISION),
+        "max": round(array.max().item(), PRECISION),
+        "sum": round(array.sum().item(), PRECISION),
+        "mean": round(array.mean(), PRECISION),
     }
 
 
@@ -378,10 +380,10 @@ def tensor_simple_attributes(tensor: Tensor) -> dict:
     return {
         "shape": tuple(tensor.shape) if not tensor.is_nested else get_shape_ish(tensor),
         "hash": _hash(tensor),
-        "min": tensor.min().item(),
-        "max": tensor.max().item(),
-        "sum": tensor.sum().item(),
-        "mean": tensor.float().mean().item(),
+        "min": round(tensor.min().item(), PRECISION),
+        "max": round(tensor.max().item(), PRECISION),
+        "sum": round(tensor.sum().item(), PRECISION),
+        "mean": round(tensor.float().mean().item(), PRECISION),
         "device": (
             "cpu" if tensor.device.type == "cpu" else f"{tensor.device.type}:{tensor.device.index}"
         ),