diff options
| -rw-r--r-- | ethosu/vela/operation.py | 5 | ||||
| -rw-r--r-- | ethosu/vela/pass_packing.py | 2 |
2 files changed, 3 insertions, 4 deletions
diff --git a/ethosu/vela/operation.py b/ethosu/vela/operation.py index a2b67dfb..710511c6 100644 --- a/ethosu/vela/operation.py +++ b/ethosu/vela/operation.py @@ -103,7 +103,7 @@ class Op(Enum): Densify = OperatorInfo() DepthToSpace = OperatorInfo() DepthwiseConv2DBias = OperatorInfo(block_type=NpuBlockType.ConvolutionDepthWise, indices=IFM_WEIGHTS_BIAS_INDICES) - Dequantize = OperatorInfo() + Dequantize = OperatorInfo(indices=IFM_INDICES) Div = OperatorInfo() Elu = OperatorInfo() EmbeddingLookup = OperatorInfo() @@ -163,7 +163,7 @@ class Op(Enum): Pow = OperatorInfo() Prelu = OperatorInfo() Prod = OperatorInfo() - Quantize = OperatorInfo() + Quantize = OperatorInfo(indices=IFM_INDICES) QuantizedAvgPool = OperatorInfo(block_type=NpuBlockType.Pooling, indices=IFM_INDICES) QuantizedConv2D = OperatorInfo(block_type=NpuBlockType.ConvolutionMxN, indices=IFM_WEIGHTS_INDICES) QuantizedMatMul = OperatorInfo(block_type=NpuBlockType.VectorProduct, indices=IFM_WEIGHTS_INDICES) @@ -207,7 +207,6 @@ class Op(Enum): SquaredDifference = OperatorInfo() Squeeze = OperatorInfo(indices=IFM_INDICES) StridedSlice = OperatorInfo(indices=IFM_INDICES) - StridedSliceOptions = OperatorInfo() Sub = OperatorInfo(block_type=NpuBlockType.ElementWise, indices=IFM_IFM2_INDICES) SubgraphInput = OperatorInfo() # Only used in CPU subgraphs Sum = OperatorInfo() diff --git a/ethosu/vela/pass_packing.py b/ethosu/vela/pass_packing.py index 35e1b143..5673c2df 100644 --- a/ethosu/vela/pass_packing.py +++ b/ethosu/vela/pass_packing.py @@ -276,7 +276,7 @@ def pack_into_passes(nng, arch, verbose_packing=False): ): assert len(curr_op.inputs) >= 1 ifm_tensor = curr_op.ifm - assert ifm_tensor is not None + assert ifm_tensor is not None, "IFM missing in {}".format(curr_op) assert ifm_tensor.purpose == TensorPurpose.FeatureMap if flags_to_set & PassFlags.Dma: |