diff options
Diffstat (limited to 'ethosu/vela/test')
-rw-r--r-- | ethosu/vela/test/test_graph_optimiser.py | 5 | ||||
-rw-r--r-- | ethosu/vela/test/test_supported_operators.py | 2 | ||||
-rw-r--r-- | ethosu/vela/test/testutil.py | 6 |
3 files changed, 5 insertions, 8 deletions
diff --git a/ethosu/vela/test/test_graph_optimiser.py b/ethosu/vela/test/test_graph_optimiser.py index 7fdc4bd8..45377417 100644 --- a/ethosu/vela/test/test_graph_optimiser.py +++ b/ethosu/vela/test/test_graph_optimiser.py @@ -21,7 +21,6 @@ import numpy as np from ethosu.vela.graph_optimiser import convert_batched_fc_shape from ethosu.vela.operation import Op from ethosu.vela.tensor import create_const_tensor -from ethosu.vela.tensor import Shape4D from ethosu.vela.tensor import Tensor from ethosu.vela.test import testutil @@ -36,8 +35,8 @@ def test_convert_batched_fc(): ifm.consumer_list.append(op) - op.ifm_shapes.append(Shape4D([4, 1, 1, 8])) - op.ofm_shapes.append(Shape4D([4, 1, 1, 8])) + op.ifm_shapes.append([4, 1, 1, 8]) + op.ofm_shapes.append([4, 1, 1, 8]) prev_op = op.clone() prev_op.ifm_shapes = op.ifm_shapes diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py index 973b820d..583821a2 100644 --- a/ethosu/vela/test/test_supported_operators.py +++ b/ethosu/vela/test/test_supported_operators.py @@ -62,7 +62,7 @@ def test_constraint_tens_input_scalar(): def test_constraint_tens_shape_size(): # Tensors cannot be > 4D - op = testutil.create_op_with_quant_tensors(Op.Relu, [1, 1, 8, 8, 8], [1, 1, 8, 8, 8], set_ifm_ofm_shapes=False) + op = testutil.create_op_with_quant_tensors(Op.Relu, [1, 1, 8, 8, 8], [1, 1, 8, 8, 8]) assert not support.is_operator_supported(op) diff --git a/ethosu/vela/test/testutil.py b/ethosu/vela/test/testutil.py index c3459501..63f841b4 100644 --- a/ethosu/vela/test/testutil.py +++ b/ethosu/vela/test/testutil.py @@ -75,7 +75,7 @@ def create_elemwise_op( def create_op_with_quant_tensors( - op_type, ifm_shape, ofm_shape, weights_shape=None, bias_shape=None, datatype=DataType.uint8, set_ifm_ofm_shapes=True + op_type, ifm_shape, ofm_shape, weights_shape=None, bias_shape=None, datatype=DataType.uint8 ): ifm = Tensor(ifm_shape, datatype, "in") ifm.quantization = default_quant_params() @@ -107,9 +107,7 @@ def create_op_with_quant_tensors( bias = create_const_tensor("bias", bias_shape, DataType.int32, np.zeros(bias_shape), np.int32, quantization=qp) op.add_input_tensor(bias) - if set_ifm_ofm_shapes: - op.set_ifm_ofm_shapes() - + op.set_ifm_ofm_shapes() return op |