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YufengShi-duduYufengShi-dudu
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Arm backend: Add VGF unit tests to operators (Part 3) (#13154)
- Included aten.scalar_tensor to aten.zeros - Ops or test files not completed: test_scalars.py: skipped sigmoid_16bit: skipped sigmoid_32bit: skipped upsample_nearest2d: dynamic shapes tests skipped Signed-off-by: Yufeng Shi <[email protected]>
1 parent f071ea5 commit bbd23a6

27 files changed

+1183
-5
lines changed

‎backends/arm/scripts/parse_test_names.py‎

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@@ -18,6 +18,8 @@
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"bitwise_right_shift.Tensor",
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"bitwise_left_shift.Tensor",
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"native_group_norm.default",
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"silu.default",
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"sdpa.default",
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"unbind.int",
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"unflatten.int",
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"_native_batch_norm_legit_no_training.default",

‎backends/arm/test/ops/test_scalar_tensor.py‎

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@@ -11,6 +11,7 @@
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EthosU85PipelineINT,
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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float_test_data_suite = {
@@ -99,3 +100,30 @@ def test_scalar_tensor_u85_INT(test_data):
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ScalarTensor.aten_op,
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run_on_fvp=True,
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).run()
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@common.parametrize("test_data", float_test_data_suite)
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@common.SkipIfNoModelConverter
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def test_scalar_tensor_vgf_FP(test_data):
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scalar, dtype, data = test_data()
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pipeline = VgfPipeline(
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ScalarTensor(scalar, dtype),
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tuple(data),
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ScalarTensor.aten_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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@common.parametrize("test_data", int_test_data_suite)
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@common.SkipIfNoModelConverter
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def test_scalar_tensor_vgf_INT(test_data):
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scalar, dtype, data = test_data()
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pipeline = VgfPipeline(
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ScalarTensor(scalar, dtype),
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tuple(data),
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ScalarTensor.aten_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.pop_stage("check.quant_nodes")
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pipeline.run()

‎backends/arm/test/ops/test_sdpa.py‎

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@@ -8,9 +8,11 @@
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import torch
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from executorch.backends.arm.test import common
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from executorch.backends.arm.test.tester.test_pipeline import (
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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@@ -27,14 +29,14 @@ def forward(self, query, key, value):
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input_t = Tuple[torch.Tensor, torch.Tensor, torch.Tensor]
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def test_sdpa_FP():
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def test_sdpa_tosa_FP():
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test_input = tuple(torch.randn(1, 3, 197, 64) for x in range(3))
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pipeline = TosaPipelineFP[input_t](SDPA(), test_input, [], [])
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pipeline.pop_stage("check_count.exir")
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pipeline.run()
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def test_sdpa_INT():
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def test_sdpa_tosa_INT():
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test_input = tuple(torch.randn(1, 3, 197, 64) for x in range(3))
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pipeline = TosaPipelineINT[input_t](SDPA(), test_input, [], [])
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pipeline.pop_stage("check.quant_nodes")
@@ -43,3 +45,25 @@ def test_sdpa_INT():
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"run_method_and_compare_outputs"
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) # TODO: reference is not quantized
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sdpa_vgf_FP():
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test_input = tuple(torch.randn(1, 3, 197, 64) for _ in range(3))
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pipeline = VgfPipeline[input_t](
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SDPA(), test_input, [], [], tosa_version="TOSA-1.0+FP"
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sdpa_vgf_INT():
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test_input = tuple(torch.randn(1, 3, 197, 64) for _ in range(3))
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pipeline = VgfPipeline[input_t](
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SDPA(),
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test_input,
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[],
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[],
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()

‎backends/arm/test/ops/test_select.py‎

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@@ -16,6 +16,7 @@
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OpNotSupportedPipeline,
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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input_t1 = Tuple[torch.Tensor, int, int]
@@ -173,3 +174,47 @@ def test_select_int_u85_INT(test_data: Tuple):
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use_to_edge_transform_and_lower=True,
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
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def test_select_int_vgf_FP_copy(test_data: Tuple):
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pipeline = VgfPipeline[input_t1](
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SelectCopy(), test_data(), aten_op_copy, [], tosa_version="TOSA-1.0+FP"
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
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def test_select_int_vgf_FP(test_data: Tuple):
191+
pipeline = VgfPipeline[input_t1](
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SelectInt(), test_data(), aten_op_int, [], tosa_version="TOSA-1.0+FP"
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
199+
def test_select_int_vgf_INT_copy(test_data: Tuple):
200+
pipeline = VgfPipeline[input_t1](
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SelectCopy(),
202+
test_data(),
203+
aten_op_copy,
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[],
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
211+
@common.SkipIfNoModelConverter
212+
def test_select_int_vgf_INT(test_data: Tuple):
213+
pipeline = VgfPipeline[input_t1](
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SelectInt(),
215+
test_data(),
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aten_op_int,
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[],
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()

‎backends/arm/test/ops/test_sigmoid.py‎

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EthosU85PipelineINT,
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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aten_op = "torch.ops.aten.sigmoid.default" # Used for checking that we do not have softmax in the graph after decompose
@@ -154,3 +155,101 @@ def test_sigmoid_u85_INT(test_data: Tuple):
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run_on_fvp=False,
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_FP(test_data: Tuple):
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pipeline = VgfPipeline[input_t1](
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Sigmoid(),
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(test_data(),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_INT(test_data: Tuple):
176+
pipeline = VgfPipeline[input_t1](
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Sigmoid(),
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(test_data(),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_FP_add():
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pipeline = VgfPipeline[input_t1](
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AddSigmoid(),
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(test_data_suite["zeros"](),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_INT_add():
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pipeline = VgfPipeline[input_t1](
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AddSigmoid(),
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(test_data_suite["ramp"](),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_FP_add_2():
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pipeline = VgfPipeline[input_t1](
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SigmoidAdd(),
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(test_data_suite["zeros"](),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_INT_add_2():
224+
pipeline = VgfPipeline[input_t1](
225+
SigmoidAdd(),
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(test_data_suite["zeros"](),),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_FP_add_3():
236+
pipeline = VgfPipeline[input_t1](
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SigmoidAddSigmoid(),
238+
(test_data_suite["randn_neg"](), test_data_suite["randn_pos"]()),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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@common.SkipIfNoModelConverter
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def test_sigmoid_vgf_INT_add_3():
248+
pipeline = VgfPipeline[input_t1](
249+
SigmoidAddSigmoid(),
250+
(test_data_suite["randn_neg"](), test_data_suite["randn_pos"]()),
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aten_op,
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exir_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()

‎backends/arm/test/ops/test_sign.py‎

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EthosU85PipelineINT,
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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aten_op = "torch.ops.aten.sign.default"
@@ -84,3 +85,29 @@ def test_sign_u85_INT(test_data: Tuple):
8485
exir_ops=exir_op,
8586
)
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pipeline.run()
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@common.parametrize("test_data", test_data_suite)
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@common.SkipIfNoModelConverter
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def test_sign_vgf_FP(test_data: Tuple):
93+
pipeline = VgfPipeline[input_t1](
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Sign(),
95+
(test_data,),
96+
aten_op=aten_op,
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exir_op=exir_op,
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tosa_version="TOSA-1.0+FP",
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)
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pipeline.run()
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103+
@common.parametrize("test_data", test_data_suite)
104+
@common.SkipIfNoModelConverter
105+
def test_sign_vgf_INT(test_data: Tuple):
106+
pipeline = VgfPipeline[input_t1](
107+
Sign(),
108+
(test_data,),
109+
aten_op=[],
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exir_op=exir_op,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()

‎backends/arm/test/ops/test_silu.py‎

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EthosU85PipelineINT,
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TosaPipelineFP,
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TosaPipelineINT,
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VgfPipeline,
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)
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@@ -111,3 +112,49 @@ def test_silu_u85_INT_inplace(test_data: input_t):
111112
Silu(), silu_data, Silu.aten_op_INT, run_on_fvp=True
112113
)
113114
pipeline.run()
115+
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@common.parametrize("test_data", Silu.test_data)
118+
@common.SkipIfNoModelConverter
119+
def test_silu_vgf_FP(test_data: input_t):
120+
silu_data = (test_data(), False)
121+
pipeline = VgfPipeline[input_t](
122+
Silu(), silu_data, Silu.aten_op_FP, tosa_version="TOSA-1.0+FP"
123+
)
124+
pipeline.run()
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126+
127+
@common.parametrize("test_data", Silu.test_data)
128+
@common.SkipIfNoModelConverter
129+
def test_silu_vgf_FP_inplace(test_data: input_t):
130+
silu_data = (test_data(), True)
131+
pipeline = VgfPipeline[input_t](
132+
Silu(), silu_data, Silu.aten_op_inplace_FP, tosa_version="TOSA-1.0+FP"
133+
)
134+
pipeline.run()
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@common.parametrize("test_data", Silu.test_data)
138+
@common.SkipIfNoModelConverter
139+
def test_silu_vgf_INT(test_data: input_t):
140+
silu_data = (test_data(), False)
141+
pipeline = VgfPipeline[input_t](
142+
Silu(),
143+
silu_data,
144+
Silu.aten_op_INT,
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tosa_version="TOSA-1.0+INT",
146+
)
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pipeline.run()
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150+
@common.parametrize("test_data", Silu.test_data)
151+
@common.SkipIfNoModelConverter
152+
def test_silu_vgf_INT_inplace(test_data: input_t):
153+
silu_data = (test_data(), True)
154+
pipeline = VgfPipeline[input_t](
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Silu(),
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silu_data,
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Silu.aten_op_INT,
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tosa_version="TOSA-1.0+INT",
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)
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pipeline.run()

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