diff --git a/backends/arm/operators/op_slice.py b/backends/arm/operators/op_slice.py index aad4599a4b5..12d38060aa6 100644 --- a/backends/arm/operators/op_slice.py +++ b/backends/arm/operators/op_slice.py @@ -57,7 +57,7 @@ def define_node( validate_valid_dtype( self.target, [inputs[0], output], - [ts.DType.INT8, ts.DType.INT32, ts.DType.FP32], + [ts.DType.INT8, ts.DType.INT16, ts.DType.INT32, ts.DType.FP32], output.tosa_spec, ) diff --git a/backends/arm/test/ops/test_sigmoid.py b/backends/arm/test/ops/test_sigmoid.py index a29bbc84782..aac2ee1c9b1 100644 --- a/backends/arm/test/ops/test_sigmoid.py +++ b/backends/arm/test/ops/test_sigmoid.py @@ -8,8 +8,13 @@ from typing import Tuple +import pytest import torch -from executorch.backends.arm.test import common +from executorch.backends.arm.quantizer.arm_quantizer import ( + get_symmetric_a16w8_quantization_config, + TOSAQuantizer, +) +from executorch.backends.arm.test import common, conftest from executorch.backends.arm.test.tester.test_pipeline import ( EthosU55PipelineINT, EthosU85PipelineINT, @@ -17,6 +22,8 @@ TosaPipelineINT, VgfPipeline, ) +from executorch.backends.arm.tosa.specification import TosaSpecification +from executorch.backends.xnnpack.test.tester import Quantize aten_op = "torch.ops.aten.sigmoid.default" # Used for checking that we do not have softmax in the graph after decompose exir_op = "executorch_exir_dialects_edge__ops_aten_sigmoid_default" @@ -253,3 +260,105 @@ def test_sigmoid_vgf_INT_add_3(): tosa_version="TOSA-1.0+INT", ) pipeline.run() + + +def get_symmetric_a16w8_sigmoid_quantizer(per_channel_quantization=False): + tosa_version = conftest.get_option("tosa_version") + tosa_profiles = { + "1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"), + } + + quantizer = TOSAQuantizer(tosa_profiles[tosa_version]) + quantizer.set_global( + get_symmetric_a16w8_quantization_config(is_per_channel=per_channel_quantization) + ) + + return Quantize( + quantizer, + get_symmetric_a16w8_quantization_config( + is_per_channel=per_channel_quantization + ), + ) + + +@common.parametrize("test_data", test_data_suite) +@pytest.mark.xfail( + reason="missing int16 sigmoid ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13974" +) +def test_sigmoid_16a8w_tosa_INT(test_data: torch.Tensor): + """Test sigmoid operation with 16A8W quantization (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = TosaPipelineINT[input_t1]( + Sigmoid(), + (test_data(),), + aten_op, + exir_op=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + tosa_extensions=["int16"], + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_sigmoid_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone300 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 sigmoid operations" +) +def test_sigmoid_16a8w_u55_INT16(test_data: torch.Tensor): + """Test sigmoid operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU55PipelineINT[input_t1]( + Sigmoid(), + (test_data(),), + aten_op, + exir_op, + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_sigmoid_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone320 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 sigmoid operations" +) +def test_sigmoid_16a8w_u85_INT16(test_data: torch.Tensor): + """Test sigmoid operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU85PipelineINT[input_t1]( + Sigmoid(), + (test_data(),), + aten_op, + exir_op, + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_sigmoid_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() diff --git a/backends/arm/test/ops/test_slice.py b/backends/arm/test/ops/test_slice.py index 915aec2e522..eafeb04320e 100644 --- a/backends/arm/test/ops/test_slice.py +++ b/backends/arm/test/ops/test_slice.py @@ -7,9 +7,14 @@ from typing import Tuple +import pytest import torch +from executorch.backends.arm.quantizer.arm_quantizer import ( + get_symmetric_a16w8_quantization_config, + TOSAQuantizer, +) -from executorch.backends.arm.test import common +from executorch.backends.arm.test import common, conftest from executorch.backends.arm.test.tester.test_pipeline import ( EthosU55PipelineINT, @@ -18,6 +23,8 @@ TosaPipelineINT, VgfPipeline, ) +from executorch.backends.arm.tosa.specification import TosaSpecification +from executorch.backends.xnnpack.test.tester import Quantize aten_op = "torch.ops.aten.slice.Tensor" exir_op = "executorch_exir_dialects_edge__ops_aten_slice_copy" @@ -119,3 +126,105 @@ def test_slice_tensor_vgf_INT(test_data: torch.Tensor): tosa_version="TOSA-1.0+INT", ) pipeline.run() + + +def get_symmetric_a16w8_slice_quantizer(per_channel_quantization=False): + tosa_version = conftest.get_option("tosa_version") + tosa_profiles = { + "1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"), + } + + quantizer = TOSAQuantizer(tosa_profiles[tosa_version]) + quantizer.set_global( + get_symmetric_a16w8_quantization_config(is_per_channel=per_channel_quantization) + ) + + return Quantize( + quantizer, + get_symmetric_a16w8_quantization_config( + is_per_channel=per_channel_quantization + ), + ) + + +@common.parametrize("test_data", test_data_suite) +@pytest.mark.xfail( + reason="missing int16 slice ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13976" +) +def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor): + """Test slice operation with 16A8W quantization (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = TosaPipelineINT[input_t1]( + Slice(), + test_data(), + aten_op, + exir_op=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + tosa_extensions=["int16"], + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_slice_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone300 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations" +) +def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor): + """Test slice operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU55PipelineINT[input_t1]( + Slice(), + test_data(), + aten_ops=[], + exir_ops=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_slice_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone320 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations" +) +def test_slice_tensor_16a8w_u85_INT16(test_data: torch.Tensor): + """Test slice operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU85PipelineINT[input_t1]( + Slice(), + test_data(), + aten_ops=[], + exir_ops=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_slice_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() diff --git a/backends/arm/test/ops/test_tanh.py b/backends/arm/test/ops/test_tanh.py index 098d878addc..0e74618fd2f 100644 --- a/backends/arm/test/ops/test_tanh.py +++ b/backends/arm/test/ops/test_tanh.py @@ -6,9 +6,14 @@ from typing import Tuple +import pytest import torch +from executorch.backends.arm.quantizer.arm_quantizer import ( + get_symmetric_a16w8_quantization_config, + TOSAQuantizer, +) -from executorch.backends.arm.test import common +from executorch.backends.arm.test import common, conftest from executorch.backends.arm.test.tester.test_pipeline import ( EthosU55PipelineINT, EthosU85PipelineINT, @@ -16,6 +21,8 @@ TosaPipelineINT, VgfPipeline, ) +from executorch.backends.arm.tosa.specification import TosaSpecification +from executorch.backends.xnnpack.test.tester import Quantize aten_op = "torch.ops.aten.tanh.default" input_t1 = Tuple[torch.Tensor] # Input x @@ -105,3 +112,105 @@ def test_tanh_vgf_INT(test_data: Tuple): tosa_version="TOSA-1.0+INT", ) pipeline.run() + + +def get_symmetric_a16w8_tanh_quantizer(per_channel_quantization=False): + tosa_version = conftest.get_option("tosa_version") + tosa_profiles = { + "1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"), + } + + quantizer = TOSAQuantizer(tosa_profiles[tosa_version]) + quantizer.set_global( + get_symmetric_a16w8_quantization_config(is_per_channel=per_channel_quantization) + ) + + return Quantize( + quantizer, + get_symmetric_a16w8_quantization_config( + is_per_channel=per_channel_quantization + ), + ) + + +@common.parametrize("test_data", test_data_suite) +@pytest.mark.xfail( + reason="missing int16 tanh ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13975" +) +def test_tanh_16a8w_tosa_INT(test_data: torch.Tensor): + """Test tanh operation with 16A8W quantization (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = TosaPipelineINT[input_t1]( + Tanh(), + (test_data(),), + aten_op, + exir_op=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + tosa_extensions=["int16"], + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_tanh_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone300 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 tanh operations" +) +def test_tanh_16a8w_u55_INT16(test_data: torch.Tensor): + """Test tanh operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU55PipelineINT[input_t1]( + Tanh(), + (test_data(),), + aten_op, + exir_ops=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_tanh_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run() + + +@common.parametrize("test_data", test_data_suite) +@common.XfailIfNoCorstone320 +@pytest.mark.xfail( + reason="Vela compilation fails with 'Invalid arguments' for int16 tanh operations" +) +def test_tanh_16a8w_u85_INT16(test_data: torch.Tensor): + """Test tanh operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)""" + per_channel_quantization = False + + pipeline = EthosU85PipelineINT[input_t1]( + Tanh(), + (test_data(),), + aten_op, + exir_ops=[], + per_channel_quantization=per_channel_quantization, + use_to_edge_transform_and_lower=True, + run_on_fvp=True, + ) + + pipeline.change_args( + "quantize", + get_symmetric_a16w8_tanh_quantizer( + per_channel_quantization=per_channel_quantization + ), + ) + pipeline.run()