MLBEDSW-3694 Replace padding with enum
Use an Enum instead of a bytestring to specify VALID or SAME padding
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: I4e87f8c32b3bfac176d822a68de061e85a558fce
diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py
index f132eef..583821a 100644
--- a/ethosu/vela/test/test_supported_operators.py
+++ b/ethosu/vela/test/test_supported_operators.py
@@ -21,6 +21,7 @@
from ethosu.vela.data_type import DataType
from ethosu.vela.operation import ActivationFunction
from ethosu.vela.operation import Op
+from ethosu.vela.operation import Padding
from ethosu.vela.supported_operators import SupportedOperators
from ethosu.vela.tensor import create_const_tensor
from ethosu.vela.tensor import QuantizationParameters
@@ -276,7 +277,7 @@
def test_constraint_tconv_stride():
# Strides must be 2
op = testutil.create_op_with_quant_tensors(Op.Conv2DBackpropInput, [0], [1, 2, 2, 1], weights_shape=[1, 1, 1, 1])
- op.attrs = {"stride_w": 1, "stride_h": 1, "padding": b"SAME"}
+ op.attrs = {"stride_w": 1, "stride_h": 1, "padding": Padding.SAME}
ifm = Tensor([1, 1, 1, 1], DataType.uint8, "ifm")
ifm.quantization = testutil.default_quant_params()
op.add_input_tensor(ifm)
@@ -286,14 +287,14 @@
def test_constraint_tconv_same():
# Valid
op = testutil.create_op_with_quant_tensors(Op.Conv2DBackpropInput, [0], [1, 2, 2, 1], weights_shape=[1, 1, 1, 1])
- op.attrs = {"stride_w": 2, "stride_h": 2, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "padding": Padding.SAME}
ifm = Tensor([1, 1, 1, 1], DataType.uint8, "ifm")
ifm.quantization = testutil.default_quant_params()
op.add_input_tensor(ifm)
assert support.is_operator_supported(op)
# Invalid
op = testutil.create_op_with_quant_tensors(Op.Conv2DBackpropInput, [0], [1, 4, 4, 1], weights_shape=[1, 1, 1, 1])
- op.attrs = {"stride_w": 2, "stride_h": 2, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "padding": Padding.SAME}
ifm = Tensor([1, 1, 1, 1], DataType.uint8, "ifm")
ifm.quantization = testutil.default_quant_params()
op.add_input_tensor(ifm)
@@ -303,14 +304,14 @@
def test_constraint_tconv_valid():
# Valid
op = testutil.create_op_with_quant_tensors(Op.Conv2DBackpropInput, [0], [1, 4, 4, 1], weights_shape=[4, 4, 1, 1])
- op.attrs = {"stride_w": 2, "stride_h": 2, "padding": b"VALID"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "padding": Padding.VALID}
ifm = Tensor([1, 1, 1, 1], DataType.uint8, "ifm")
ifm.quantization = testutil.default_quant_params()
op.add_input_tensor(ifm)
assert support.is_operator_supported(op)
# Invalid
op = testutil.create_op_with_quant_tensors(Op.Conv2DBackpropInput, [0], [1, 4, 4, 1], weights_shape=[2, 2, 1, 1])
- op.attrs = {"stride_w": 2, "stride_h": 2, "padding": b"VALID"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "padding": Padding.VALID}
ifm = Tensor([1, 1, 1, 1], DataType.uint8, "ifm")
ifm.quantization = testutil.default_quant_params()
op.add_input_tensor(ifm)
@@ -320,7 +321,7 @@
def test_constraint_matching_in_out_types():
# Valid
op = testutil.create_op_with_quant_tensors(Op.AvgPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 2, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 2, "padding": Padding.SAME}
assert support.is_operator_supported(op)
# Invalid. datatypes for ifm and ofm must match (default uint8)
op.ifm.dtype = DataType.int8
@@ -330,7 +331,7 @@
def test_constraint_filter_type():
# Filter width/height must be integers
op = testutil.create_op_with_quant_tensors(Op.AvgPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2.5, "filter_height": "2", "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2.5, "filter_height": "2", "padding": Padding.SAME}
assert not support.is_operator_supported(op)
@@ -338,17 +339,17 @@
# Avg pool restrictions are dependent on padding:
# SAME padding restricts both W and H to max 8
op = testutil.create_op_with_quant_tensors(Op.AvgPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 20, "filter_height": 20, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 20, "filter_height": 20, "padding": Padding.SAME}
assert not support.is_operator_supported(op)
# VALID padding limits are much larger
- op.attrs["padding"] = b"VALID"
+ op.attrs["padding"] = Padding.VALID
assert support.is_operator_supported(op)
def test_constraint_filter_height_range_valid_pad():
# Avg pool restrictions are dependent on padding:
op = testutil.create_op_with_quant_tensors(Op.AvgPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 256, "padding": b"VALID"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 256, "padding": Padding.VALID}
assert support.is_operator_supported(op)
# VALID padding restricts to 256 in filter height
op.attrs["filter_height"] = 257
@@ -358,7 +359,7 @@
def test_constraint_filter_product_height_range_valid_pad():
# Avg pool restrictions are dependent on padding:
op = testutil.create_op_with_quant_tensors(Op.AvgPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 256, "filter_height": 256, "padding": b"VALID"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 256, "filter_height": 256, "padding": Padding.VALID}
assert support.is_operator_supported(op)
# VALID padding restricts filter W x H to 256x256
op.attrs["filter_width"] = 257
@@ -368,26 +369,26 @@
def test_constraint_filter_height_range():
# Max pool restrictions arent dependent on padding
op = testutil.create_op_with_quant_tensors(Op.MaxPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 256, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 2, "filter_height": 256, "padding": Padding.SAME}
assert support.is_operator_supported(op)
# Restricts to 256 in filter height
op.attrs["filter_height"] = 257
assert not support.is_operator_supported(op)
# Doesnt matter if SAME or VALID
- op.attrs["padding"] = b"VALID"
+ op.attrs["padding"] = Padding.VALID
assert not support.is_operator_supported(op)
def test_constraint_filter_product_height_range():
# Max pool restrictions arent dependent on padding
op = testutil.create_op_with_quant_tensors(Op.MaxPool, [1, 8, 8, 8], [1, 8, 8, 8])
- op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 256, "filter_height": 256, "padding": b"SAME"}
+ op.attrs = {"stride_w": 2, "stride_h": 2, "filter_width": 256, "filter_height": 256, "padding": Padding.SAME}
assert support.is_operator_supported(op)
# Restricts filter W x H to 256x256
op.attrs["filter_width"] = 257
assert not support.is_operator_supported(op)
# Doesnt matter if SAME or VALID
- op.attrs["padding"] = b"VALID"
+ op.attrs["padding"] = Padding.VALID
assert not support.is_operator_supported(op)