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Bump tol for autocasted fasterrcnn_resnet50_fpn #6601

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Merged
merged 2 commits into from
Sep 16, 2022
Merged

Bump tol for autocasted fasterrcnn_resnet50_fpn #6601

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bee305c
Bump tol for autocasted `fasterrcnn_resnet50_fpn`
malfet Sep 16, 2022
b19fe99
Pacify linter
malfet Sep 16, 2022
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7 changes: 4 additions & 3 deletions test/test_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -233,6 +233,8 @@ def _check_input_backprop(model, inputs):
"keypointrcnn_resnet50_fpn",
)

autocast_custom_prec = {"fasterrcnn_resnet50_fpn": 0.012} if platform.system() == "Windows" else {}

# The tests for the following quantized models are flaky possibly due to inconsistent
# rounding errors in different platforms. For this reason the input/output consistency
# tests under test_quantized_classification_model will be skipped for the following models.
Expand Down Expand Up @@ -738,7 +740,7 @@ def test_detection_model(model_fn, dev):
out = model(model_input)
assert model_input[0] is x

def check_out(out):
def check_out(out, prec=0.01):
assert len(out) == 1

def compact(tensor):
Expand Down Expand Up @@ -767,7 +769,6 @@ def compute_mean_std(tensor):
return {"mean": mean, "std": std}

output = map_nested_tensor_object(out, tensor_map_fn=compact)
prec = 0.01
try:
# We first try to assert the entire output if possible. This is not
# only the best way to assert results but also handles the cases
Expand Down Expand Up @@ -800,7 +801,7 @@ def compute_mean_std(tensor):
out = model(model_input)
# See autocast_flaky_numerics comment at top of file.
if model_name not in autocast_flaky_numerics:
full_validation &= check_out(out)
full_validation &= check_out(out, autocast_custom_prec.get(model_name, 0.01))

if not full_validation:
msg = (
Expand Down