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-rw-r--r--ethosu/vela/test/extapi/test_extapi_encode_weights.py10
-rw-r--r--ethosu/vela/test/test_register_command_stream_util.py84
-rw-r--r--ethosu/vela/test/test_tflite_model_semantic.py22
-rw-r--r--ethosu/vela/test/test_tflite_supported_operators.py37
4 files changed, 130 insertions, 23 deletions
diff --git a/ethosu/vela/test/extapi/test_extapi_encode_weights.py b/ethosu/vela/test/extapi/test_extapi_encode_weights.py
index 6367cb30..87c504f4 100644
--- a/ethosu/vela/test/extapi/test_extapi_encode_weights.py
+++ b/ethosu/vela/test/extapi/test_extapi_encode_weights.py
@@ -24,7 +24,8 @@ from ethosu.vela.api import NpuBlockTraversal
@pytest.mark.parametrize(
- "arch", list(NpuAccelerator),
+ "arch",
+ list(NpuAccelerator),
)
@pytest.mark.parametrize("dilation_x", [1, 2])
@pytest.mark.parametrize("dilation_y", [1, 2])
@@ -32,7 +33,12 @@ from ethosu.vela.api import NpuBlockTraversal
@pytest.mark.parametrize("depth_control", [1, 2, 3])
@pytest.mark.parametrize("weights_shape_and_block_depth", [((16, 16, 16, 16), 8), ((3, 3, 25, 16), 8)])
def test_encode_weights(
- arch, weights_shape_and_block_depth, dilation_x, dilation_y, ifm_bitdepth, depth_control,
+ arch,
+ weights_shape_and_block_depth,
+ dilation_x,
+ dilation_y,
+ ifm_bitdepth,
+ depth_control,
):
"""
This unit test checks the interface of the API function but not the functionality.
diff --git a/ethosu/vela/test/test_register_command_stream_util.py b/ethosu/vela/test/test_register_command_stream_util.py
index 985523fa..86a48ff6 100644
--- a/ethosu/vela/test/test_register_command_stream_util.py
+++ b/ethosu/vela/test/test_register_command_stream_util.py
@@ -131,14 +131,34 @@ def test_calc_blockdep0():
op2 takes 1 block to complete, which results in blockdep 0
"""
op1 = NpuElementWiseOperation(NpuElementWiseOp.CLZ)
- op1.ifm = create_feature_map(NpuShape3D(height=1, width=1, depth=1), 1, 0x60, layout=NpuLayout.NHCWB16,)
- intermediate_fm = create_feature_map(NpuShape3D(height=1, width=1, depth=1), 1, 0xA0, layout=NpuLayout.NHCWB16,)
+ op1.ifm = create_feature_map(
+ NpuShape3D(height=1, width=1, depth=1),
+ 1,
+ 0x60,
+ layout=NpuLayout.NHCWB16,
+ )
+ intermediate_fm = create_feature_map(
+ NpuShape3D(height=1, width=1, depth=1),
+ 1,
+ 0xA0,
+ layout=NpuLayout.NHCWB16,
+ )
op1.ofm = intermediate_fm
op1.block_config = NpuShape3D(height=1, width=1, depth=4)
op2 = NpuElementWiseOperation(NpuElementWiseOp.SUB)
- op2.ifm = create_feature_map(NpuShape3D(height=1, width=1, depth=1), 1, 0x39AC0, layout=NpuLayout.NHCWB16,)
+ op2.ifm = create_feature_map(
+ NpuShape3D(height=1, width=1, depth=1),
+ 1,
+ 0x39AC0,
+ layout=NpuLayout.NHCWB16,
+ )
op2.ifm2 = intermediate_fm
- op2.ofm = create_feature_map(NpuShape3D(height=1, width=1, depth=1), 1, 0xE0, layout=NpuLayout.NHCWB16,)
+ op2.ofm = create_feature_map(
+ NpuShape3D(height=1, width=1, depth=1),
+ 1,
+ 0xE0,
+ layout=NpuLayout.NHCWB16,
+ )
op2.block_config = NpuShape3D(height=1, width=1, depth=4)
arch = create_default_arch(Accelerator.Ethos_U55_128)
block_dep = calc_blockdep(arch, op1, op2)
@@ -153,8 +173,18 @@ def test_calc_blockdep2():
which results in blockdep 2
"""
op1 = NpuConv2DOperation()
- op1.ifm = create_feature_map(NpuShape3D(height=4, width=48, depth=8), 1, 0x4C80, layout=NpuLayout.NHCWB16,)
- op1.ofm = create_feature_map(NpuShape3D(height=4, width=48, depth=16), 1, 0x6480, layout=NpuLayout.NHCWB16,)
+ op1.ifm = create_feature_map(
+ NpuShape3D(height=4, width=48, depth=8),
+ 1,
+ 0x4C80,
+ layout=NpuLayout.NHCWB16,
+ )
+ op1.ofm = create_feature_map(
+ NpuShape3D(height=4, width=48, depth=16),
+ 1,
+ 0x6480,
+ layout=NpuLayout.NHCWB16,
+ )
op1.kernel = NpuKernel(1, 1)
op1.weights = [NpuAddressRange(region=1, address=0x4AE0, length=208)]
op1.biases = [NpuAddressRange(region=1, address=0x49A0, length=160)]
@@ -162,10 +192,20 @@ def test_calc_blockdep2():
op1.block_traversal = NpuBlockTraversal.PART_KERNEL_FIRST
op1.block_config = NpuShape3D(height=4, width=6, depth=16)
op2 = NpuConvDepthWiseOperation()
- op2.ifm = create_feature_map(NpuShape3D(height=3, width=48, depth=16), 1, 0, layout=NpuLayout.NHCWB16,)
+ op2.ifm = create_feature_map(
+ NpuShape3D(height=3, width=48, depth=16),
+ 1,
+ 0,
+ layout=NpuLayout.NHCWB16,
+ )
# op2 has two tiles, the lower tile is produced by op1
op2.ifm.tiles = NpuTileBox(height_0=2, height_1=2, width_0=48, addresses=[0x7680, 0, 0x6480, 0])
- op2.ofm = create_feature_map(NpuShape3D(height=1, width=24, depth=16), 1, 0x6480, layout=NpuLayout.NHCWB16,)
+ op2.ofm = create_feature_map(
+ NpuShape3D(height=1, width=24, depth=16),
+ 1,
+ 0x6480,
+ layout=NpuLayout.NHCWB16,
+ )
op2.kernel = NpuKernel(3, 3, stride_x=2, stride_y=2)
op2.weights = [NpuAddressRange(region=1, address=0x4BB0, length=208)]
op2.biases = [NpuAddressRange(region=1, address=0x4A40, length=160)]
@@ -183,8 +223,18 @@ def test_calc_blockdep3():
which results in blockdep 3
"""
op1 = NpuConv2DOperation()
- op1.ifm = create_feature_map(NpuShape3D(height=13, width=96, depth=1), 1, 0, layout=NpuLayout.NHWC,)
- op1.ofm = create_feature_map(NpuShape3D(height=6, width=48, depth=8), 1, 0x7C80, layout=NpuLayout.NHCWB16,)
+ op1.ifm = create_feature_map(
+ NpuShape3D(height=13, width=96, depth=1),
+ 1,
+ 0,
+ layout=NpuLayout.NHWC,
+ )
+ op1.ofm = create_feature_map(
+ NpuShape3D(height=6, width=48, depth=8),
+ 1,
+ 0x7C80,
+ layout=NpuLayout.NHCWB16,
+ )
op1.kernel = NpuKernel(3, 3, stride_x=2, stride_y=2)
op1.weights = [NpuAddressRange(region=1, address=0x4AE0, length=144)]
op1.biases = [NpuAddressRange(region=1, address=0x49A0, length=80)]
@@ -192,8 +242,18 @@ def test_calc_blockdep3():
op1.block_traversal = NpuBlockTraversal.PART_KERNEL_FIRST
op1.block_config = NpuShape3D(height=6, width=3, depth=8)
op2 = NpuConvDepthWiseOperation()
- op2.ifm = create_feature_map(NpuShape3D(height=5, width=48, depth=8), 1, 0x7C80, layout=NpuLayout.NHCWB16,)
- op2.ofm = create_feature_map(NpuShape3D(height=4, width=48, depth=8), 1, 0x4C80, layout=NpuLayout.NHCWB16,)
+ op2.ifm = create_feature_map(
+ NpuShape3D(height=5, width=48, depth=8),
+ 1,
+ 0x7C80,
+ layout=NpuLayout.NHCWB16,
+ )
+ op2.ofm = create_feature_map(
+ NpuShape3D(height=4, width=48, depth=8),
+ 1,
+ 0x4C80,
+ layout=NpuLayout.NHCWB16,
+ )
op2.kernel = NpuKernel(3, 3)
op2.weights = [NpuAddressRange(region=1, address=0x4BB0, length=112)]
op2.biases = [NpuAddressRange(region=1, address=0x4A40, length=80)]
diff --git a/ethosu/vela/test/test_tflite_model_semantic.py b/ethosu/vela/test/test_tflite_model_semantic.py
index 84f99160..1e5dbd4d 100644
--- a/ethosu/vela/test/test_tflite_model_semantic.py
+++ b/ethosu/vela/test/test_tflite_model_semantic.py
@@ -128,7 +128,14 @@ def test_constraint_quant_scale_inf():
def test_constraint_ofm_scale_too_small():
# Tests handling of OFM scale < 1e-38
shp = [1, 10, 20, 16]
- op = testutil.create_elemwise_op(Op.Mul, "mul", shp, shp, shp, ofm_quant=testutil.default_quant_params(),)
+ op = testutil.create_elemwise_op(
+ Op.Mul,
+ "mul",
+ shp,
+ shp,
+ shp,
+ ofm_quant=testutil.default_quant_params(),
+ )
assert semantic_checker.is_operator_semantic_valid(op)
op.ofm.quantization.scale_f32 = 1e-43
assert not semantic_checker.is_operator_semantic_valid(op)
@@ -245,7 +252,12 @@ def create_strided_slice_op(in_shape, out_shape, start_offsets, end_offsets):
def create_pad_op(
- in_shape, out_shape, padding, in_dtype=DataType.int8, out_dtype=DataType.int8, pad_dtype=DataType.int32,
+ in_shape,
+ out_shape,
+ padding,
+ in_dtype=DataType.int8,
+ out_dtype=DataType.int8,
+ pad_dtype=DataType.int32,
):
qp = testutil.default_quant_params()
in0 = Tensor(in_shape, in_dtype, "in")
@@ -259,7 +271,11 @@ def create_pad_op(
def test_constraint_pad_input_count():
# Incorrect number of input tensors (2)
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[0, 0], [1, 1], [1, 1], [0, 0]],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[[0, 0], [1, 1], [1, 1], [0, 0]],
+ )
assert semantic_checker.is_operator_semantic_valid(op)
op.add_input_tensor(op.inputs[0].clone())
assert not semantic_checker.is_operator_semantic_valid(op)
diff --git a/ethosu/vela/test/test_tflite_supported_operators.py b/ethosu/vela/test/test_tflite_supported_operators.py
index e3db7913..04d3cba1 100644
--- a/ethosu/vela/test/test_tflite_supported_operators.py
+++ b/ethosu/vela/test/test_tflite_supported_operators.py
@@ -345,7 +345,12 @@ def test_constraint_concat_pass():
def create_pad_op(
- in_shape, out_shape, padding, in_dtype=DataType.int8, out_dtype=DataType.int8, pad_dtype=DataType.int32,
+ in_shape,
+ out_shape,
+ padding,
+ in_dtype=DataType.int8,
+ out_dtype=DataType.int8,
+ pad_dtype=DataType.int32,
):
qp = testutil.default_quant_params()
in0 = Tensor(in_shape, in_dtype, "in")
@@ -359,11 +364,23 @@ def create_pad_op(
def test_constraint_padded_dimensions():
# Incorrect padding dimensions, can only pad width and height
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[1, 1], [1, 1], [1, 1], [0, 0]],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[[1, 1], [1, 1], [1, 1], [0, 0]],
+ )
assert not support.is_operator_supported(op)
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[1, 1], [1, 1], [0, 0]],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[[1, 1], [1, 1], [0, 0]],
+ )
assert support.is_operator_supported(op)
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[1, 1], [1, 1], [0, 1]],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[[1, 1], [1, 1], [0, 1]],
+ )
assert not support.is_operator_supported(op)
@@ -371,12 +388,20 @@ def test_constraint_pad_shape():
# PAD operator must be of shape (3,2) or (4,2)
op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[1, 1], [1, 1], [0, 0]])
assert support.is_operator_supported(op)
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[[0, 0], [1, 1], [1, 1], [0, 0], [0, 0]],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[[0, 0], [1, 1], [1, 1], [0, 0], [0, 0]],
+ )
assert not support.is_operator_supported(op)
def test_constraint_pad_none():
- op = create_pad_op(in_shape=[1, 1, 1, 1], out_shape=[1, 3, 3, 1], padding=[],)
+ op = create_pad_op(
+ in_shape=[1, 1, 1, 1],
+ out_shape=[1, 3, 3, 1],
+ padding=[],
+ )
assert not support.is_operator_supported(op)
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-08 04:31:31 +0000