vela: Move special error cases
Due to an issue with potential cyclical imports, especially when running
individual parts of vela standalone for example with pytest, the
specialised error functions are moved out of errors.py to their
respective locations.
The use of getattr over isinstance prevents the need to import the
tensor/operator class causing the cyclical import issue.
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: If8cee4b1a2562660c6a47e1c7aeb5d7fd4dd1fca
diff --git a/ethosu/vela/tensor.py b/ethosu/vela/tensor.py
index c1443b3..69618d2 100644
--- a/ethosu/vela/tensor.py
+++ b/ethosu/vela/tensor.py
@@ -31,10 +31,11 @@
import numpy as np
-from . import errors # Import this way due to cyclic imports
from . import numeric_util
from .data_type import BaseType
from .data_type import DataType
+from .errors import UnsupportedFeatureError
+from .errors import VelaError
from .ethos_u55_regs.ethos_u55_regs import resampling_mode
from .operation import Op
from .operation import Operation
@@ -630,7 +631,7 @@
if end_coord[2] > crossing_x:
addresses[1] = self.address_for_coordinate([start_coord[0], start_coord[1], crossing_x, start_coord[3]])
- raise errors.UnsupportedFeatureError("Striping in vertical direction is not supported")
+ raise UnsupportedFeatureError("Striping in vertical direction is not supported")
if end_coord[1] > crossing_y:
addresses[2] = self.address_for_coordinate([start_coord[0], crossing_y, start_coord[2], start_coord[3]])
if end_coord[1] > crossing_y and end_coord[2] > crossing_x:
@@ -737,7 +738,7 @@
if index < len(self.weight_compressed_offsets) - 1:
# There are no half-way points in the weights
if (depth % brick_depth) != 0:
- raise errors.UnsupportedFeatureError("Offset into weights must be aligned to a brick")
+ raise UnsupportedFeatureError("Offset into weights must be aligned to a brick")
return index
@@ -851,6 +852,32 @@
__repr__ = __str__
+ def error(self, msg):
+ """
+ Raises a VelaError exception for errors encountered when parsing a Tensor
+
+ :param self: Tensor object that resulted in the error
+ :param msg: str object that contains a description of the specific error encountered
+ """
+
+ def _print_operators(ops):
+ lines = []
+ for idx, op in enumerate(ops):
+ op_type = getattr(op, "type", "Not an Operation")
+ op_id = getattr(op, "op_index", "-")
+ lines.append(f" {idx} = {op_type} ({op_id})")
+ return lines
+
+ lines = [f"Invalid {self.name} tensor. {msg}"]
+
+ lines += [" Driving operators:"]
+ lines += _print_operators(self.ops)
+
+ lines += [" Consuming operators:"]
+ lines += _print_operators(self.consumer_list)
+
+ raise VelaError("\n".join(lines))
+
def check_quantized_tens_scaling_equal(tens_a: Tensor, tens_b: Tensor) -> bool:
# checks that the scaling of two quantized tensors are equal