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[EE/BE] T206498038 Adding the legacy flow tests to add op #6907

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[EE/BE] T206498038 Adding the legacy flow tests to add op #6907

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cd95415
[EE/BE] T206498038 Adding the legacy flow tests to add op
Nov 15, 2024
2751645
fixing typo
Nov 15, 2024
fda0b1f
fix linter
cbilgin Nov 17, 2024
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251 changes: 140 additions & 111 deletions backends/xnnpack/test/ops/add.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,17 +43,20 @@ def forward(self, x):
return out1, out2

def _test_add(self, inputs):
(
Tester(self.Add(), inputs)
.export()
.check_count({"torch.ops.aten.add.Tensor": 4})
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
for legacy in (True, False):
tester = Tester(self.Add(), inputs)
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 4})
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_fp16_add(self):
inputs = (torch.randn(1).to(torch.float16), torch.randn(1).to(torch.float16))
Expand All @@ -65,95 +68,110 @@ def test_fp32_add(self):

def test_fp32_add_constant(self):
inputs = (torch.randn(4, 4, 4),)
(
Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
.export()
.check_count({"torch.ops.aten.add.Tensor": 4})
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
for legacy in (True, False):
tester = Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 4})
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add_constant(self):
inputs = (torch.randn(4, 4, 4),)
(
Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
.quantize()
.export()
.check_count({"torch.ops.aten.add.Tensor": 4})
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
for legacy in (True, False):
tester = Tester(self.AddConstant(torch.randn(4, 4, 4)), inputs)
tester.quantize()
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 4})
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add(self):
inputs = (torch.randn(1, 1, 4, 4), torch.randn(1, 1, 4, 4))
(
Tester(self.Add(), inputs)
.quantize()
.export()
.check_count({"torch.ops.aten.add.Tensor": 4})
.check(["torch.ops.quantized_decomposed"])
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(
for legacy in (True, False):
tester = Tester(self.Add(), inputs)
tester.quantize()
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 4})
tester.check(["torch.ops.quantized_decomposed"])
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(
[
"executorch_exir_dialects_edge__ops_aten_add_Tensor",
"torch.ops.quantized_decomposed",
]
)
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add2(self):
inputs = (torch.randn(1, 1, 4, 4),)
(
Tester(self.Add2(), inputs)
.quantize()
.export()
.check_count({"torch.ops.aten.add.Tensor": 1})
.check(["torch.ops.quantized_decomposed"])
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(
for legacy in (True, False):
tester = Tester(self.Add2(), inputs)
tester.quantize()
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 1})
tester.check(["torch.ops.quantized_decomposed"])
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(
[
"executorch_exir_dialects_edge__ops_aten_add_Tensor",
"torch.ops.quantized_decomposed",
]
)
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add3(self):
inputs = (torch.randn(1, 1, 4, 4), torch.randn(1, 1, 4, 1))
(
Tester(self.Add(), inputs)
.quantize()
.export()
.check_count({"torch.ops.aten.add.Tensor": 4})
.check(["torch.ops.quantized_decomposed"])
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.check_not(
for legacy in (True, False):
tester = Tester(self.Add(), inputs)
tester.quantize()
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 4})
tester.check(["torch.ops.quantized_decomposed"])
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.check_not(
[
"executorch_exir_dialects_edge__ops_aten_add_Tensor",
"torch.ops.quantized_decomposed",
]
)
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

class AddRelu(torch.nn.Module):
def forward(self, x, y):
Expand All @@ -162,35 +180,43 @@ def forward(self, x, y):

def test_fp32_add_relu(self):
inputs = (torch.randn(1, 1, 4, 4), torch.randn(1, 1, 4, 4))
(
Tester(self.AddRelu(), inputs)
.export()
.check_count({"torch.ops.aten.add.Tensor": 1})
.check_count({"torch.ops.aten.relu.default": 1})
.to_edge_transform_and_lower()
.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
.check_not(["executorch_exir_dialects_edge__ops_aten_relu_default"])
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
for legacy in (True, False):
tester = Tester(self.AddRelu(), inputs)
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 1})
tester.check_count({"torch.ops.aten.relu.default": 1})
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_not(["executorch_exir_dialects_edge__ops_aten_add_Tensor"])
tester.check_not(["executorch_exir_dialects_edge__ops_aten_relu_default"])
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add_relu(self):
inputs = (torch.randn(1, 1, 4, 4), torch.randn(1, 1, 4, 4))
(
Tester(self.AddRelu(), inputs)
.quantize()
.export()
.check_count({"torch.ops.aten.add.Tensor": 1})
.check_count({"torch.ops.aten.relu.default": 1})
.check(["torch.ops.quantized_decomposed"])
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
for legacy in (True, False):
tester = Tester(self.AddRelu(), inputs)
tester.quantize()
tester.export()
tester.check_count({"torch.ops.aten.add.Tensor": 1})
tester.check_count({"torch.ops.aten.relu.default": 1})
tester.check(["torch.ops.quantized_decomposed"])
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count(
{"torch.ops.higher_order.executorch_call_delegate": 1}
)
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()

def test_qs8_add_relu_seq(self):
class AddReLU(torch.nn.Module):
Expand Down Expand Up @@ -220,17 +246,20 @@ def forward(self, x, z):
),
)

(
Tester(self.AddRelu(), inputs)
.quantize()
.export()
.check_count(
for legacy in (True, False):
tester = Tester(self.AddRelu(), inputs)
tester.quantize()
tester.export()
tester.check_count(
{"torch.ops.aten.add.Tensor": 1, "torch.ops.aten.relu.default": 1}
)
.check(["torch.ops.quantized_decomposed"])
.to_edge_transform_and_lower()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.serialize()
.run_method_and_compare_outputs()
)
tester.check(["torch.ops.quantized_decomposed"])
if legacy:
tester.to_edge()
tester.partition()
else:
tester.to_edge_transform_and_lower()
tester.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
tester.to_executorch()
tester.serialize()
tester.run_method_and_compare_outputs()
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