TOSA: Added RESHAPE, SLICE and CONCAT
Added support for Data layout ops
RESHAPE, SLICE and CONCAT.
-No support for bool_t
-Support limited to Rank <= 4 and N = 1
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I487ac494b6506a2a6ba947ee758aa193194dd796
diff --git a/ethosu/vela/tosa_supported_operators.py b/ethosu/vela/tosa_supported_operators.py
index d7a1ebc..c619f2f 100644
--- a/ethosu/vela/tosa_supported_operators.py
+++ b/ethosu/vela/tosa_supported_operators.py
@@ -38,7 +38,7 @@
fc_vector_products = set((Op.FullyConnected,))
mac_main_ops = convolution_like_ops | pooling_ops | fc_vector_products
- memory_only_ops = set((Op.Reshape, Op.Transpose,))
+ memory_only_ops = set((Op.Reshape, Op.Transpose, Op.Concat, Op.SplitSliceRead,))
binary_elem_wise_add_mul_sub = set((Op.Add, Op.Mul, Op.RescaleMul, Op.Sub,))
@@ -53,7 +53,7 @@
# Supported data types
# TODO will differ compared to TensorFlow Lite, currently set to the same
- supported_op_dtypes = set((DataType.uint8, DataType.int8, DataType.int16, DataType.int32))
+ supported_op_dtypes = set((DataType.uint8, DataType.int8, DataType.int16, DataType.int32)) # TODO add bool
def __init__(self):
# Setup the generic constraints. Note: the order matters
@@ -109,7 +109,7 @@
valid = op.ifm.ops and op.ifm.ops[0].type == Op.Const
return valid, "Op has ifm with non-constant data"
- # TODO duplicates tflite_supported operators, but support for depth multiplier should be added at a later stage
+ # TODO duplicates TFLite_supported operators, but support for depth multiplier should be added at a later stage
@staticmethod
def constraint_depth_multiplier(op):
"For depth multipliers > 1, IFM channels must be 1 and OFM channels must be equal to the depth multiplier"