Reformat code to align with precommit
Signed-off-by: Per Åstrand <per.astrand@arm.com>
Change-Id: Idc6f6959bfc7eabce2f5b6e0d4935d292dcf6618
diff --git a/ethosu/vela/tosa_graph_optimiser.py b/ethosu/vela/tosa_graph_optimiser.py
index 09b2c52..26d3dca 100644
--- a/ethosu/vela/tosa_graph_optimiser.py
+++ b/ethosu/vela/tosa_graph_optimiser.py
@@ -247,7 +247,11 @@
# consumed by CPU
# Check if operator ifm/ofm are sg ifm/ofm
- ifm_is_sg_ifm = op.ifm.ops[0].type in (Op.Placeholder, Op.SubgraphInput, Op.Const)
+ ifm_is_sg_ifm = op.ifm.ops[0].type in (
+ Op.Placeholder,
+ Op.SubgraphInput,
+ Op.Const,
+ )
ifm_is_sg_ofm = any(ifm_cons is None for ifm_cons in op.ifm.consumer_list)
ofm_is_sg_ofm = any(ofm_cons is None for ofm_cons in op.ofm.consumer_list)
# Check if ifm/ofm is produced repectivly consumed by CPU
@@ -302,7 +306,13 @@
else:
name = op.name + "_add"
ofm = op.ofm
- ifm2 = create_const_tensor(name + "_zero_scalar", [1], ofm.dtype, [0], quantization=ofm.quantization)
+ ifm2 = create_const_tensor(
+ name + "_zero_scalar",
+ [1],
+ ofm.dtype,
+ [0],
+ quantization=ofm.quantization,
+ )
add_op = create_add_nop(name)
add_op.inputs = [op.ifm, ifm2]
add_op.outputs = [ofm]
@@ -330,7 +340,13 @@
write_offset = [0, 0, 0, 0]
write_offset[axis_4D] = offset
concat_end = offset + op.ifm_shapes[idx][axis_4D]
- create_add_for_concat(op, op.name + str(idx) + "_add", inp, op.ifm_shapes[idx], Shape4D.from_list(write_offset))
+ create_add_for_concat(
+ op,
+ op.name + str(idx) + "_add",
+ inp,
+ op.ifm_shapes[idx],
+ Shape4D.from_list(write_offset),
+ )
offset = concat_end
assert op.ofm_shapes[0][axis_4D] == offset
@@ -417,7 +433,10 @@
DebugDatabase.add_optimised(op, prev_op)
return op
else:
- print("Warning, unsupported fusing of TOSA Rescale previous operator is of type:", prev_op.type)
+ print(
+ "Warning, unsupported fusing of TOSA Rescale previous operator is of type:",
+ prev_op.type,
+ )
assert False
elif (
(ifm.dtype == DataType.int8 and ofm.dtype == DataType.int8)
@@ -447,7 +466,7 @@
for a in equal_attributes:
assert op.attrs[a] == rescale_1.attrs[a] == rescale_2.attrs[a], (
f"Only handling equal {a} for all operands "
- "({op.attrs[a]}, {rescale_1.attrs[a]}, {rescale_2.attrs[a]}) "
+ f"({op.attrs[a]}, {rescale_1.attrs[a]}, {rescale_2.attrs[a]}) "
"for all the rescale operations to be fused with Add!"
)
@@ -486,7 +505,10 @@
print("Warning, unsupported fusing of TOSA Rescale with Add.")
assert False
else:
- print("Warning, unsupported fusing of TOSA Rescale previous operator is of type:", prev_op.type)
+ print(
+ "Warning, unsupported fusing of TOSA Rescale previous operator is of type:",
+ prev_op.type,
+ )
assert False
return op
@@ -519,17 +541,31 @@
if left > 0:
shape = Shape4D(1, ifm_shape.height, left, ofm_shape.depth)
zero_tens = create_const_tensor(
- op.name + "_left", shape.as_list(), ofm.dtype, shape.elements() * [pad_value], quantization=quant
+ op.name + "_left",
+ shape.as_list(),
+ ofm.dtype,
+ shape.elements() * [pad_value],
+ quantization=quant,
)
zero_tens.equivalence_id = create_equivalence_id(tuple(zero_tens.values))
create_add_for_concat(op, op.name + "_left", zero_tens, shape, shp0)
if right > 0:
shape = Shape4D(1, ifm_shape.height, right, ofm_shape.depth)
zero_tens = create_const_tensor(
- op.name + "_right", shape.as_list(), ofm.dtype, shape.elements() * [pad_value], quantization=quant
+ op.name + "_right",
+ shape.as_list(),
+ ofm.dtype,
+ shape.elements() * [pad_value],
+ quantization=quant,
)
zero_tens.equivalence_id = create_equivalence_id(tuple(zero_tens.values))
- create_add_for_concat(op, op.name + "_right", zero_tens, shape, shp0.with_width(ofm_shape.width - right))
+ create_add_for_concat(
+ op,
+ op.name + "_right",
+ zero_tens,
+ shape,
+ shp0.with_width(ofm_shape.width - right),
+ )
op.type = Op.ConcatTFLite
return add_op
@@ -992,7 +1028,12 @@
)
# Rewite Operators step
- op_rewrite_list = [set_tensor_equivalence, rewrite_rescale, convert_depthwise_to_conv, convert_table_to_lut]
+ op_rewrite_list = [
+ set_tensor_equivalence,
+ rewrite_rescale,
+ convert_depthwise_to_conv,
+ convert_table_to_lut,
+ ]
for idx, sg in enumerate(nng.subgraphs):
nng.subgraphs[idx] = rewrite_graph.rewrite_graph_pre_order(
diff --git a/ethosu/vela/tosa_reader.py b/ethosu/vela/tosa_reader.py
index 5ffefad..670b264 100644
--- a/ethosu/vela/tosa_reader.py
+++ b/ethosu/vela/tosa_reader.py
@@ -247,7 +247,8 @@
if depth_multiplier > 1:
assert op.ifm.shape[-1] == 1 and op.ofm.shape[-1] == depth_multiplier, (
"For depth multipliers > 1, IFM channels must be 1 and "
- "OFM channels must be equal to the depth multiplier")
+ "OFM channels must be equal to the depth multiplier"
+ )
op.attrs["depth_multiplier"] = depth_multiplier
if op.type == Op.SplitSliceRead:
op.read_offsets[0] = Shape4D.from_list(list(op.attrs["start"]), 0)