MLBEDSW-7881: Convert Quantize op to Avgpool op in graph optimiser
This convert is already done in the pass packing stage, but doing it
in the graph optimiser stage is better.
Change-Id: Ib9baa98d115cf88491ce39936972a93467a378ce
Signed-off-by: Johan Gunnarsson <johan.gunnarsson@arm.com>
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 @@
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 @@
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 @@
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])
diff --git a/ethosu/vela/tflite_graph_optimiser.py b/ethosu/vela/tflite_graph_optimiser.py
index ef6b90b..218f499 100644
--- a/ethosu/vela/tflite_graph_optimiser.py
+++ b/ethosu/vela/tflite_graph_optimiser.py
@@ -1685,6 +1685,21 @@
return op
+def convert_quantize(op: Operation, arch, nng) -> Operation:
+ """Convert Quantize to Avgpool. This conversion only works for int-to-int re-quantization and
+ not to/from floats. Therefor, this rewrite should only run after the supported ops check to
+ avoid rewriting ops that will run on CPU."""
+ if op.type == Op.Quantize:
+ # Create a new AvgPool op and steal its attrs, then reuse the original op with different type
+ avgpool_op = create_avgpool_nop(op.name + "_avgpool")
+ op.type = Op.AvgPool
+ op.attrs = avgpool_op.attrs.copy()
+
+ DebugDatabase.add_optimised(op, op)
+
+ return op
+
+
def fuse_activation_function_with_prev(op, arch, nng):
# if op is a no-op: attempts to move the activation function to the preceding op
if not op.attrs.get("is_nop", False) or op.activation is None:
@@ -2645,6 +2660,7 @@
fixup_bias_tensors,
fixup_asymmetric_weights,
convert_tanh_sigmoid_to_lut,
+ convert_quantize,
replace_pad_by_hw_pad,
fixup_dilation_gt2,
]