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[ExecuTorch] Unbreak optimized sub in the case where one input is a scalar and both are Half #5894

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[ExecuTorch] Unbreak optimized sub in the case where one input is a scalar and both are Half #5894

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2 changes: 1 addition & 1 deletion kernels/optimized/cpu/op_sub.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -134,8 +134,8 @@ Tensor& opt_sub_out(
}
});
});
return out;
}
return out;
}

auto selected_optimized_path = select_optimized_path(a, b, out);
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36 changes: 23 additions & 13 deletions kernels/test/op_sub_test.cpp
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Expand Up @@ -107,6 +107,27 @@ class OpSubOutTest : public OperatorTest {

#undef ENUMERATE_TEST_ENTRY
}

template <ScalarType DTYPE>
void test_broadcast_rank1_scalar() {
TensorFactory<DTYPE> tf;

Tensor a = tf.make({2, 1, 3}, {2, 3, 4, 5, 6, 7});
Tensor b = tf.make({1}, {2});

// Destination for the broadcasting div. Follow the broadcasting rules in
// https://fburl.com/n9wl4d0o
Tensor out = tf.zeros({2, 1, 3});

op_sub_out(a, b, 1, out);

Tensor ret = tf.make({2, 1, 3}, {0, 1, 2, 3, 4, 5});
EXPECT_TENSOR_EQ(out, ret);

op_sub_out(b, a, 1, out);
ret = tf.make({2, 1, 3}, {0, -1, -2, -3, -4, -5});
EXPECT_TENSOR_EQ(out, ret);
}
};

class OpSubScalarOutTest : public OperatorTest {
Expand Down Expand Up @@ -171,19 +192,8 @@ TEST_F(OpSubOutTest, BroadcastSupported2) {
}

TEST_F(OpSubOutTest, BroadcastScalarSupported1) {
TensorFactory<ScalarType::Float> tf;

Tensor a = tf.make({2, 1, 3}, {2, 3, 4, 5, 6, 7});
Tensor b = tf.make({1}, {2});

// Destination for the broadcasting div. Follow the broadcasting rules in
// https://fburl.com/n9wl4d0o
Tensor out = tf.zeros({2, 1, 3});

op_sub_out(a, b, 1, out);

Tensor ret = tf.make({2, 1, 3}, {0, 1, 2, 3, 4, 5});
EXPECT_TENSOR_EQ(out, ret);
test_broadcast_rank1_scalar<ScalarType::Float>();
test_broadcast_rank1_scalar<ScalarType::Half>();
}

TEST_F(OpSubOutTest, BroadcastScalarSupported2) {
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