MLBEDSW-3070: Fix addressing of weights
Assign different equivalence ids to weights with same values but
different compression, to ensure correct addressing.
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
Change-Id: I13aabad71520e4f4a78fb2d6a81740bdd4d1256c
diff --git a/ethosu/vela/lut.py b/ethosu/vela/lut.py
index e3373ca..69aa2a0 100644
--- a/ethosu/vela/lut.py
+++ b/ethosu/vela/lut.py
@@ -16,26 +16,16 @@
# Description:
# Functionality for lookup table support.
import uuid
-from functools import lru_cache
import numpy as np
from . import numeric_util
from .high_level_command_stream import CommandType
from .tensor import create_const_tensor
+from .tensor import create_equivalence_id
from .tensor import TensorPurpose
-@lru_cache(maxsize=None)
-def create_equivalence_id(key):
- # Generates equivalence_id based on key.
- # The DMA optimization of LUT-s assumes that 2 LUT tensors are identical
- # if they have the same equivalence_id.
- # So for example all created 256-byte tanh LUT tensors should have
- # the same equivalence id.
- return uuid.uuid4()
-
-
class LUTState:
# Tracks which LUT-s are located in SHRAM.
def __init__(self):
diff --git a/ethosu/vela/tensor.py b/ethosu/vela/tensor.py
index 0f8170d..eedbada 100644
--- a/ethosu/vela/tensor.py
+++ b/ethosu/vela/tensor.py
@@ -18,6 +18,7 @@
import enum
import uuid
from collections import defaultdict
+from functools import lru_cache
import numpy as np
@@ -159,6 +160,12 @@
return new_shp
+@lru_cache(maxsize=None)
+def create_equivalence_id(key):
+ # Generates equivalence_id based on the given key.
+ return uuid.uuid4()
+
+
class QuantizationParameters:
__slots__ = "min", "max", "num_bits", "narrow_range", "scale_f32", "zero_point", "quant_min", "quant_max"
@@ -303,6 +310,7 @@
"compression_scale_for_worst_weight_stream",
"weight_compression_scales",
"weight_compression_config",
+ "value_id",
"storage_rounding_quantum",
"brick_size",
"quantization",
@@ -342,7 +350,10 @@
self.bandwidth_compression_scale = 1.0
self.compression_scale_for_worst_weight_stream = 1.0
self.weight_compression_scales = None
+ # if two tensors have the same weight_compression_config, then they have the same compressed values
self.weight_compression_config = None
+ # if two tensors have the same value_id, then they have the same values
+ self.value_id = uuid.uuid4()
self.weight_compressed_offsets = []
self.storage_rounding_quantum = (1, 1, 1, 1)
self.brick_size = (1, 1, 1, 1)
@@ -375,7 +386,6 @@
res.ops = []
res.consumer_list = []
- res.equivalence_id = self.equivalence_id
res.values = self.values
res.quant_values = self.quant_values
@@ -407,6 +417,7 @@
def copy_compressed_weight_info(self, src_tens):
# Copies compressed values + all related weight compression info from the given tensor
+ self.equivalence_id = src_tens.equivalence_id
self.compressed_values = src_tens.compressed_values
self.compressed_values_substream_offsets = src_tens.compressed_values_substream_offsets
self.storage_shape = src_tens.storage_shape
@@ -418,6 +429,7 @@
self.storage_compression_scale = src_tens.storage_compression_scale
self.block_traversal = src_tens.block_traversal
self.weight_compression_config = src_tens.weight_compression_config
+ self.value_id = src_tens.value_id
def set_format(self, fmt, arch):
self.format = fmt
diff --git a/ethosu/vela/weight_compressor.py b/ethosu/vela/weight_compressor.py
index 2374cd4..c5a3f3f 100644
--- a/ethosu/vela/weight_compressor.py
+++ b/ethosu/vela/weight_compressor.py
@@ -30,6 +30,7 @@
from .operation import NpuBlockType
from .scaling import quantise_scale
from .scaling import reduced_quantise_scale
+from .tensor import create_equivalence_id
from .tensor import TensorBlockTraversal
from .tensor import TensorFormat
from .tensor import TensorPurpose
@@ -40,7 +41,7 @@
# Contains meta info for a weight compression. If two tensors have identical weight compression config,
# then they also will have identical compressed weights.
WeightCompressionConfig = namedtuple(
- "WeightCompressionConfig", ["npu_block_type", "ofm_block_depth", "ofm_depth_step", "dilation", "equivalence_id"]
+ "WeightCompressionConfig", ["npu_block_type", "ofm_block_depth", "ofm_depth_step", "dilation", "value_id"]
)
@@ -136,7 +137,7 @@
# Note: for an ofm block only its depth is used in weight compression.
# And block depth > ofm depth gives same result as block depth == ofm depth
block_depth = min(ofm_block_depth, tens.quant_values.shape[-1])
- return WeightCompressionConfig(npu_block_type, block_depth, ofm_depth_step, dilation, tens.equivalence_id)
+ return WeightCompressionConfig(npu_block_type, block_depth, ofm_depth_step, dilation, tens.value_id)
def set_storage_shape(tens):
@@ -286,13 +287,15 @@
nng.weight_cache = CompressedWeightCache()
wcc = create_weight_compression_config(tens, npu_block_type, ofm_block_depth, ofm_depth_step, dilation)
tens.weight_compression_config = wcc
+ # Reassign equivalence id such that tensors with same weight compression get identical equivalence ids,
+ # but tensors with the same values but different compression get different equivalence ids
+ tens.equivalence_id = create_equivalence_id(wcc)
tens_cached = nng.weight_cache.get_tensor_with_same_compression(wcc)
if tens_cached is not None:
# Cache hit, copy weights from the cache
tens.copy_compressed_weight_info(tens_cached)
set_storage_shape(tens)
return
-
# No cache hit, perform the compression
assert tens.quantization is not None
assert tens.quantization.scale_f32 is not None