TOSA: Support for AVGPOOL, MAXPOOL and CONV2D
Added support for
-AVGPOOL and CONV2D with TFLite correspondence
-MAXPOOL
-additional support for replacing RESCALE ops with avgpool.
No support for breaking down tensors over the
size supported by NPU.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I1d2aa50ac30a26283b3e6f1fe88cba1544b7c189
diff --git a/ethosu/vela/register_command_stream_generator.py b/ethosu/vela/register_command_stream_generator.py
index d61e571..6ee0005 100644
--- a/ethosu/vela/register_command_stream_generator.py
+++ b/ethosu/vela/register_command_stream_generator.py
@@ -71,6 +71,7 @@
from .numeric_util import quantise_float32
from .numeric_util import round_away_zero
from .numeric_util import round_up_to_int
+from .operation import ExplicitScaling
from .operation import NpuBlockType
from .range_set import MemoryAccessSet
from .register_command_stream_util import BASE_PTR_INDEX_MEM2MEM
@@ -676,11 +677,18 @@
ofm_scale_f64 = np.double(ofm_quant.scale_f32)
scale, shift = scaling.quantise_scale(ifm_scale_f64 / ofm_scale_f64)
elif pool_op.rescale is not None:
- # for ResizeBilinear operations with rescale
- rescale = pool_op.rescale
- rescale_bits = len(bin(round_up_to_int(rescale))) - 2 + 1
- scale, shift = scaling.quantise_pooling_scale(kernel.height * kernel.width, rescale_bits)
- scale = int(round_away_zero(scale * rescale))
+ if type(pool_op.rescale) == ExplicitScaling:
+ # Note: reuse of rescale for explicit scaling to not expose this in the external API
+ explicit_scaling = pool_op.rescale
+ assert explicit_scaling.per_channel is False
+ scale = explicit_scaling.multiplier[0]
+ shift = explicit_scaling.shift[0]
+ else:
+ # for ResizeBilinear operations with rescale
+ rescale = pool_op.rescale
+ rescale_bits = len(bin(round_up_to_int(rescale))) - 2 + 1
+ scale, shift = scaling.quantise_pooling_scale(kernel.height * kernel.width, rescale_bits)
+ scale = int(round_away_zero(scale * rescale))
else:
# In case avg pool fused with concat or other memory operation, rescaling might be needed.
# kernel height == kernel width == 1 is always true in this case
@@ -896,6 +904,9 @@
use_global_scale = (
npu_op.sub_op_type in (NpuPoolingOp.AVERAGE, NpuPoolingOp.REDUCE_SUM) and sum(npu_op.padding) == 0
)
+ # Note: reuse of rescale for explicit scaling to not expose this in the external API
+ if npu_op.rescale is not None and type(npu_op.rescale) == ExplicitScaling:
+ use_global_scale = not npu_op.rescale.per_channel
generate_common(emit, npu_op, NpuBlockTraversal.DEPTH_FIRST, arch, use_global_scale=use_global_scale)
# Pooling op specific
if use_global_scale: