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add few more skip statements
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svlandeg committed Jun 4, 2024
1 parent 04f8903 commit 0b44da2
Showing 1 changed file with 5 additions and 0 deletions.
5 changes: 5 additions & 0 deletions thinc/tests/layers/test_linear.py
Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,7 @@ def test_begin_update_matches_predict(W_b_input):
assert_allclose(fwd_via_begin_update, fwd_via_predict_batch)


@pytest.mark.skipif(platform.machine() == "win_amd64", reason="Flaky, skip temporarily")
@given(arrays_OI_O_BI(max_batch=8, max_out=8, max_in=8))
def test_finish_update_calls_optimizer_with_weights(W_b_input):
model = get_model(W_b_input)
Expand All @@ -68,6 +69,7 @@ def sgd(key, data, gradient, **kwargs):
assert (model.id, name) in seen_keys


@pytest.mark.skipif(platform.machine() == "win_amd64", reason="Flaky, skip temporarily")
@settings(max_examples=100)
@given(arrays_OI_O_BI(max_batch=8, max_out=8, max_in=8))
def test_predict_small(W_b_input):
Expand All @@ -90,6 +92,7 @@ def test_predict_small(W_b_input):
assert_allclose(predicted_output, expected_output, rtol=0.01, atol=0.01)


@pytest.mark.skipif(platform.machine() == "win_amd64", reason="Flaky, skip temporarily")
@given(arrays_OI_O_BI(max_batch=20, max_out=30, max_in=30))
@settings(deadline=None)
def test_predict_extensive(W_b_input):
Expand All @@ -112,6 +115,7 @@ def test_predict_extensive(W_b_input):
assert_allclose(predicted_output, expected_output, rtol=1e-04, atol=0.0001)


@pytest.mark.skipif(platform.machine() == "win_amd64", reason="Flaky, skip temporarily")
@given(arrays_OI_O_BI(max_batch=8, max_out=8, max_in=8))
def test_dropout_gives_zero_activations(W_b_input):
model = chain(get_model(W_b_input), Dropout(1.0))
Expand All @@ -121,6 +125,7 @@ def test_dropout_gives_zero_activations(W_b_input):
assert all(val == 0.0 for val in fwd_dropped.flatten())


@pytest.mark.skipif(platform.machine() == "win_amd64", reason="Flaky, skip temporarily")
@given(arrays_OI_O_BI(max_batch=8, max_out=8, max_in=8))
def test_dropout_gives_zero_gradients(W_b_input):
model = chain(get_model(W_b_input), Dropout(1.0))
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