diff options
Diffstat (limited to 'ethosu/vela/test/test_supported_operators.py')
| -rw-r--r-- | ethosu/vela/test/test_supported_operators.py | 28 |
1 files changed, 15 insertions, 13 deletions
diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py index 53c20927..20d448d7 100644 --- a/ethosu/vela/test/test_supported_operators.py +++ b/ethosu/vela/test/test_supported_operators.py @@ -19,6 +19,7 @@ import numpy as np from ethosu.vela.data_type import DataType +from ethosu.vela.operation import Op from ethosu.vela.supported_operators import SupportedOperators from ethosu.vela.tensor import create_const_tensor from ethosu.vela.tensor import QuantizationParameters @@ -35,7 +36,7 @@ def create_strided_slice_op(in_shape, out_shape, start_offsets, end_offsets): in3 = create_const_tensor("strides", [len(end_offsets)], DataType.uint8, len(end_offsets) * [1]) out = Tensor(out_shape, DataType.uint8, "out") attrs = {"ellipsis_mask": 0, "new_axis_mask": 0, "shrink_axis_mask": 0, "begin_mask": 0, "end_mask": 0} - return testutil.create_op("StridedSlice", [in0, in1, in2, in3], out, attrs=attrs) + return testutil.create_op(Op.StridedSlice, [in0, in1, in2, in3], out, attrs=attrs) def create_strided_slice(): @@ -93,21 +94,21 @@ def test_constraint_tens_defined_shape(): # Tensors cannot have None in them inp = Tensor([1, 8, None, 8], DataType.uint8, "in") out = Tensor([1, 8, 8, 8], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) def test_constraint_tens_shapeless(): # Shapeless input is allowed if its of a certain type: - op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8]) + op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8]) assert support.is_operator_supported(op) # Shapeless output is not allowed at all: - op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [1, 8, 8, 8], []) + op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [1, 8, 8, 8], []) assert not support.is_operator_supported(op) # Invalid shapeless input due to op type: inp = Tensor([], DataType.uint8, "in") out = Tensor([1, 8, 8, 8], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) @@ -115,7 +116,7 @@ def test_constraint_tens_shape_size(): # Tensors cannot be > 4D inp = Tensor([1, 1, 8, 8, 8], DataType.uint8, "in") out = Tensor([1, 1, 8, 8, 8], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) @@ -123,14 +124,14 @@ def test_constraint_tens_dtype(): # Tensors can only be of type uint8, int8, int16 (and int32) inp = Tensor([1, 8, 8, 8], DataType.float32, "in") out = Tensor([1, 8, 8, 8], DataType.float32, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) # For int32, only select op types are allowed: - op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8], DataType.int32) + op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8], DataType.int32) assert support.is_operator_supported(op) inp = Tensor([1, 8, 8, 8], DataType.int32, "in") out = Tensor([1, 8, 8, 8], DataType.int32, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) @@ -138,11 +139,11 @@ def test_constraint_tens_dimension(): # Tensors can only have values in the inclusive range of 1-65535 inp = Tensor([1, 8, 8, 0], DataType.uint8, "in") out = Tensor([1, 8, 8, 0], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) inp = Tensor([1, 8, 8, 65536], DataType.uint8, "in") out = Tensor([1, 8, 8, 65536], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out) + op = testutil.create_op(Op.Relu, [inp], out) assert not support.is_operator_supported(op) @@ -150,13 +151,14 @@ def test_constraint_faf(): # Fused activation functions, if set, must be a valid op type inp = Tensor([1, 8, 8, 8], DataType.uint8, "in") out = Tensor([1, 8, 8, 8], DataType.uint8, "out") - op = testutil.create_op("Relu", [inp], out, attrs={"fused_activation_function": "Conv2D"}) + op = testutil.create_op(Op.Relu, [inp], out) + op.activation = Op.Conv2D assert not support.is_operator_supported(op) def test_constraint_tens_quant_scale(): # Quantization scale cannot be infinit - op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8]) + op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8]) op.inputs[0].quantization = QuantizationParameters() op.inputs[0].quantization.scale_f32 = np.inf assert not support.is_operator_supported(op) |