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remove exir.capture from quant fusion test #3106

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remove exir.capture from quant fusion test #3106

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58 changes: 34 additions & 24 deletions exir/tests/test_quant_fusion_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

import torch
from executorch import exir
from executorch.exir import CaptureConfig, EdgeCompileConfig
from executorch.exir import EdgeCompileConfig, to_edge
from executorch.exir.passes.quant_fusion_pass import QuantFusionPass
from executorch.exir.tests.common import register_additional_test_aten_ops
from torch.ao.quantization import ( # @manual
Expand All @@ -26,6 +26,7 @@
_convert_to_reference_decomposed_fx,
prepare_fx,
)
from torch.export import export
from torch.nn import functional as F

from torch.testing import FileCheck
Expand Down Expand Up @@ -56,9 +57,11 @@ def forward(self, x, y):
)
m = _convert_to_reference_decomposed_fx(m)
config = EdgeCompileConfig(_check_ir_validity=False)
m = exir.capture(m, example_inputs, CaptureConfig()).to_edge(config=config)
m = to_edge(export(m, example_inputs), compile_config=config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass(_fix_node_meta_val=True))
m = m.transform(
[QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
)
# check that we are using functional variant of q/dq/add
FileCheck().check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default"
Expand All @@ -67,12 +70,12 @@ def forward(self, x, y):
).check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default"
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)
m = m.to_executorch()
# check that we are using out variant of q/dq/add
FileCheck().check("torch.ops.quantized_decomposed.add.out").run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

def test_reshape(self) -> None:
Expand All @@ -95,9 +98,11 @@ def forward(self, x, y):
m(*example_inputs)
m = _convert_to_reference_decomposed_fx(m)
config = EdgeCompileConfig(_check_ir_validity=False)
m = exir.capture(m, example_inputs, CaptureConfig()).to_edge(config=config)
m = to_edge(export(m, example_inputs), compile_config=config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass(_fix_node_meta_val=True))
m = m.transform(
[QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
)
# check that we are using functional variant of q/dq/add/reshape
# make sure we only have two quant and one dequant since the q/dq around reshape
# should be fused
Expand All @@ -114,14 +119,14 @@ def forward(self, x, y):
1,
exactly=True,
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

m = m.to_executorch(exir.ExecutorchBackendConfig(remove_view_copy=False))
# check that we are using out variant of q/dq/add
FileCheck().check("torch.ops.quantized_decomposed.add.out").check(
"torch.ops.aten.view_copy.out"
).run(m.exported_program.graph_module.code)
).run(m.exported_program().graph_module.code)

def test_slice(self) -> None:
"""We don't proactively quantize slice today, but we'll fuse the dq-slice-q
Expand Down Expand Up @@ -150,9 +155,11 @@ def forward(self, x, y):
)
m = _convert_to_reference_decomposed_fx(m)
config = EdgeCompileConfig(_check_ir_validity=False)
m = exir.capture(m, example_inputs, CaptureConfig()).to_edge(config=config)
m = to_edge(export(m, example_inputs), compile_config=config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass(_fix_node_meta_val=True))
m = m.transform(
[QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
)
# check that we are using functional variant of q/dq/add/slice
# make sure we only have one quant and one dequant since the q/dq around slice
# should be fused
Expand All @@ -169,14 +176,14 @@ def forward(self, x, y):
).check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default"
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

m = m.to_executorch()
# check that we are using out variant of add and slice_copy
FileCheck().check("torch.ops.quantized_decomposed.add.out").check(
"torch.ops.aten.slice_copy.Tensor_out"
).run(m.dump_graph_module().code)
).run(m.exported_program().graph_module.code)

def test_cat(self) -> None:
class M(torch.nn.Module):
Expand All @@ -197,9 +204,9 @@ def forward(self, x, y):
m(*example_inputs)
m = _convert_to_reference_decomposed_fx(m)
config = EdgeCompileConfig(_check_ir_validity=False)
m = exir.capture(m, example_inputs, CaptureConfig()).to_edge(config=config)
m = to_edge(export(m, example_inputs), compile_config=config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass())
m = m.transform([QuantFusionPass()], check_ir_validity=False)
# check that we are using functional variant of q/dq/cat
FileCheck().check_count(
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default",
Expand All @@ -210,7 +217,7 @@ def forward(self, x, y):
1,
exactly=True,
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

m = m.to_executorch()
Expand All @@ -224,7 +231,7 @@ def forward(self, x, y):
).check("torch.ops.aten.cat.out").check_count(
"torch.ops.quantized_decomposed.dequantize_per_tensor.out", 1, exactly=True
).run(
m.dump_graph_module().code
m.exported_program().graph_module.code
)

def test_embedding_byte(self) -> None:
Expand Down Expand Up @@ -292,16 +299,18 @@ def forward(self, indices):
_check_ir_validity=False,
_use_edge_ops=True,
)
m = exir.capture(m, example_inputs).to_edge(config=compile_config)
m = to_edge(export(m, example_inputs), compile_config=compile_config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass(_fix_node_meta_val=True))
m = m.transform(
[QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
)
# check that we are using functional variant of q/dq/cat
FileCheck().check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_channel_default",
).check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_embedding_byte_default"
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

# TODO: enable after the out variants of quantize_per_channel is supported
Expand Down Expand Up @@ -348,17 +357,18 @@ def forward(self, indices):
_check_ir_validity=False,
_use_edge_ops=True,
)
m = exir.capture(m, example_inputs).to_edge(config=compile_config)
m = to_edge(export(m, example_inputs), compile_config=compile_config)
# QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
m = m.transform(QuantFusionPass(_fix_node_meta_val=True))
m(*example_inputs)
m = m.transform(
[QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
)
# check that we are using functional variant of q/dq/cat
FileCheck().check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_channel_default",
).check(
"executorch_exir_dialects_edge__ops_quantized_decomposed_embedding_byte_default"
).run(
m.exported_program.graph_module.code
m.exported_program().graph_module.code
)

# TODO: enable after the out variants of quantize_per_channel is supported
Expand Down