Alexey-Yazev commented on code in PR #13997:
URL: https://github.com/apache/tvm/pull/13997#discussion_r1111577237
##########
src/relay/op/contrib/ethosu/pooling.cc:
##########
@@ -46,14 +46,27 @@ bool EthosuPoolingRel(const Array<Type>& types, int
num_inputs, const Attrs& att
const String operator_name = "ethosu_pooling";
- if (param->pooling_type != "AVG" && param->pooling_type != "MAX") {
+ if (param->pooling_type != "AVG" && param->pooling_type != "MAX" &&
+ param->pooling_type != "SUM") {
reporter->GetDiagCtx().EmitFatal(Diagnostic::Error(reporter->GetSpan())
<< "Invalid operator: expected " <<
operator_name
- << " type 'AVG' or 'MAX' but was " <<
param->pooling_type);
+ << " type 'AVG', 'MAX', or 'SUM' but was "
+ << param->pooling_type);
return false;
}
- CheckDataType(reporter, ifm->dtype, {DataType::UInt(8), DataType::Int(8)},
operator_name, "ifm",
+ auto max_avg_pooling_ifm_dtypes = {DataType::UInt(8), DataType::Int(8)};
+ auto sum_pooling_ifm_dtypes = {DataType::UInt(8), DataType::Int(8),
DataType::Int(16),
Review Comment:
C++ code style says:
> Favor concrete type declaration over auto as long as it is short.
How short should it be?
Is it ok to use
`std::initializer_list<DataType>`
or better
```
using DTypes = std::initializer_list<DataType>;
DTypes sum_pooling_ifm_dtypes
```
?
##########
python/tvm/relay/op/contrib/ethosu.py:
##########
@@ -1375,6 +1375,82 @@ def mean_pattern() ->
tvm.relay.dataflow_pattern.DFPattern:
return pattern
+class SumParams:
+ """
+ This class will parse a call to ethosu.sum composite function
+ and extract the parameter information.
+ """
+
+ composite_name = "ethos-u.sum"
+
+ def __init__(self, func_body: Call):
+ from tvm.relay.backend.contrib.ethosu.util import RequantArgs
+
+ requantize = func_body
+ sum_op = requantize.args[0]
+ attrs = sum_op.attrs
+ cast = sum_op.args[0]
+
+ layout = "NHWC"
+ self.ifm = TensorParams(
+ cast.args[0],
+ layout,
+ requantize.args[RequantArgs.IFM_SCALE.value],
+ requantize.args[RequantArgs.IFM_ZERO_POINT.value],
+ )
+ self.ofm = TensorParams(
+ requantize,
+ layout,
+ requantize.args[RequantArgs.OFM_SCALE.value],
+ requantize.args[RequantArgs.OFM_ZERO_POINT.value],
+ )
+
+ ifm_shape = self.ifm.shape
+ self.height = ifm_shape[0] if len(ifm_shape) in (2, 3) else
ifm_shape[1]
+ self.width = ifm_shape[1] if len(ifm_shape) in (2, 3) else ifm_shape[2]
+ self.keepdims = attrs.keepdims
+
+ self.axis = list(sorted(attrs.axis))
+ if attrs.exclude:
+ self.axis = [i for i in range(len(self.ifm.shape)) if i not in
self.axis]
+
+ def is_valid(self) -> bool:
+ """
+ Checks whether Sum has compatible attributes with HW.
+ """
+
+ ifm_shape_len = len(self.ifm.shape)
+
+ if not check_valid_dtypes([self.ifm], [np.uint8, np.int8, np.int16,
np.int32]):
+ return False
+ if not check_valid_dtypes([self.ofm], [np.int8]):
+ return False
+ if not ifm_shape_len in (3, 4):
+ return False
+ if ifm_shape_len == 3 and self.axis not in [[2]]:
+ return False
+ if ifm_shape_len == 4 and self.axis not in [[3]]:
+ return False
+
+ return True
+
+
+def sum_pattern() -> tvm.relay.dataflow_pattern.DFPattern:
Review Comment:
Yes
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