diff options
Diffstat (limited to 'ethosu/vela/high_level_command_to_npu_op.py')
| -rw-r--r-- | ethosu/vela/high_level_command_to_npu_op.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/ethosu/vela/high_level_command_to_npu_op.py b/ethosu/vela/high_level_command_to_npu_op.py index 79ac392..4384f2c 100644 --- a/ethosu/vela/high_level_command_to_npu_op.py +++ b/ethosu/vela/high_level_command_to_npu_op.py @@ -143,7 +143,7 @@ def get_rounding_mode(op: Operation, fused_quantize: bool) -> NpuRoundingMode: if op.type.is_resize_op(): rounding_mode = NpuRoundingMode.NATURAL elif ( - op._original_type.npu_block_type in (NpuBlockType.ConvolutionMxN, NpuBlockType.ConvolutionDepthWise) + op.original_type.npu_block_type in (NpuBlockType.ConvolutionMxN, NpuBlockType.ConvolutionDepthWise) and op.ifm.dtype == DataType.int16 ): rounding_mode = NpuRoundingMode.NATURAL @@ -334,7 +334,7 @@ def use_zero_point_0(ps, tens: Tensor, is_ifm_tensor: bool) -> bool: return False if ps.primary_op.type == Op.AvgPool and ps.primary_op.explicit_scaling: return False - fused_quantize = any(op.type == Op.Quantize for op in ps.ops) + fused_quantize = any(op.type == Op.Quantize or op.original_type == Op.Quantize for op in ps.ops) forced_ofm_quantization = ps.primary_op.forced_output_quantization use_0 = ( ( @@ -521,7 +521,7 @@ def set_common_op_fields(npu_op: NpuBlockOperation, cmd: NpuStripe, arch: Archit if cmd.weight_tensor is not None: npu_op.weights, npu_op.biases = create_weights(cmd.weight_tensor, cmd.weight_box, cmd.scale_tensor, arch) npu_op.activation = create_npu_activation(op) - npu_op.fused_quantize = any(op.type == Op.Quantize for op in ps.ops) + npu_op.fused_quantize = any(op.type == Op.Quantize or op.original_type == Op.Quantize for op in ps.ops) npu_op.rounding_mode = get_rounding_mode(op, npu_op.fused_quantize) npu_op.block_config = NpuShape3D(height=ps.block_config[0], width=ps.block_config[1], depth=ps.block_config[3]) |