diff options
Diffstat (limited to 'ethosu/vela/test/test_supported_operators.py')
| -rw-r--r-- | ethosu/vela/test/test_supported_operators.py | 76 |
1 files changed, 76 insertions, 0 deletions
diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py index df310434..53c20927 100644 --- a/ethosu/vela/test/test_supported_operators.py +++ b/ethosu/vela/test/test_supported_operators.py @@ -16,9 +16,12 @@ # # Description: # Unit tests for support_operators +import numpy as np + from ethosu.vela.data_type import DataType from ethosu.vela.supported_operators import SupportedOperators from ethosu.vela.tensor import create_const_tensor +from ethosu.vela.tensor import QuantizationParameters from ethosu.vela.tensor import Tensor from ethosu.vela.test import testutil @@ -84,3 +87,76 @@ def test_strided_slice(): op = create_strided_slice() op.attrs["end_mask"] = 0 assert not support.is_operator_supported(op) + + +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) + 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]) + 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], []) + 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) + assert not support.is_operator_supported(op) + + +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) + assert not support.is_operator_supported(op) + + +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) + 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) + 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) + assert not support.is_operator_supported(op) + + +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) + 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) + assert not support.is_operator_supported(op) + + +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"}) + 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.inputs[0].quantization = QuantizationParameters() + op.inputs[0].quantization.scale_f32 = np.inf + assert not support.is_operator_supported(op) |