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| author | Charles Xu <charles.xu@arm.com> | 2020-08-11 12:31:58 +0200 |
|---|---|---|
| committer | Fredrik Knutsson <fredrik.knutsson.hunnebo@gmail.com> | 2020-08-12 12:42:55 +0000 |
| commit | 89a6bbffaa85d72cd79fd73f457c01486b9258bb (patch) | |
| tree | b4e4f573462c84c90ebf32b26ae5552bc4a22f15 | |
| parent | de2a57f81197f475a9c74b65b02ac3d5c1e949bb (diff) | |
| download | ethos-u-vela-89a6bbffaa85d72cd79fd73f457c01486b9258bb.tar.gz | |
MLBEDSW-2681: Ceiling the upscale for OFM/IFM
Signed-off-by: Charles Xu <charles.xu@arm.com>
Change-Id: I566abd5a1ffc367c6b9b8f37d5a26b61d27e840b
| -rw-r--r-- | ethosu/vela/high_level_command_stream_generator.py | 7 |
1 files changed, 5 insertions, 2 deletions
diff --git a/ethosu/vela/high_level_command_stream_generator.py b/ethosu/vela/high_level_command_stream_generator.py index 2297a3bf..d34fb75b 100644 --- a/ethosu/vela/high_level_command_stream_generator.py +++ b/ethosu/vela/high_level_command_stream_generator.py @@ -23,6 +23,7 @@ from .high_level_command_stream import DMA from .high_level_command_stream import NpuStripe from .nn_graph import PassPlacement from .nn_graph import SchedulingStrategy +from .numeric_util import round_up_divide from .operation import NpuBlockType from .tensor import TensorPurpose @@ -77,8 +78,10 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id if ps.primary_op is not None: strides = ps.primary_op.attrs.get("strides", None) skirt = ps.primary_op.attrs.get("skirt", None) - if ps.primary_op.type in set(("Conv2DBackpropInputSwitchedBias", "ResizeBilinear")): + if ps.primary_op.type == "Conv2DBackpropInputSwitchedBias": upscaling = ofm_tensor.shape[-3] // ifm_tensor.shape[-3] + elif ps.primary_op.type == "ResizeBilinear": + upscaling = round_up_divide(ofm_tensor.shape[-3], ifm_tensor.shape[-3]) concat_axis = 0 concat_offset = 0 @@ -235,7 +238,7 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id ofm_box = Box(ofm_start, ofm_end) k_height = 1 - if npu_block_type == set((NpuBlockType.Pooling, NpuBlockType.ReduceSum)): + if npu_block_type in (NpuBlockType.Pooling, NpuBlockType.ReduceSum): if ps.primary_op is not None: k_height = ps.primary_op.attrs["ksize"][1] else: |