Add support for one dimension of size -1 in ReshapeOp
Signed-off-by: Jerry Ge <jerry.ge@arm.com>
Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: I0ef7607f4266296a1204c5cccdb5be36f345b5ba
diff --git a/verif/generator/tosa_error_if.py b/verif/generator/tosa_error_if.py
index 8c40371..a0a9203 100644
--- a/verif/generator/tosa_error_if.py
+++ b/verif/generator/tosa_error_if.py
@@ -81,6 +81,8 @@
KernelNotPowerOfTwo = "KernelNotPowerOfTwo"
FFTInputShapeMismatch = "FFTInputShapeMismatch"
FFTOutputShapeMismatch = "FFTOutputShapeMismatch"
+ ReshapeOutputSizeMultiInference = "ReshapeOutputSizeMultiInference"
+ ReshapeOutputSizeNonInteger = "ReshapeOutputSizeNonInteger"
class TosaErrorIfArgGen:
@@ -1822,13 +1824,17 @@
param_reqs = {"rank": None, "dtype": None, "shape": None}
error_result = False
error_reason = "Input tensor size does not match output tensor size"
+ op = kwargs["op"]
if check:
input_shape = kwargs["input_shape"]
output_shape = kwargs["output_shape"]
+ shape_inferencing = False
+ if -1 in output_shape and op["op"] == Op.RESHAPE:
+ shape_inferencing = True
input_size = np.prod(input_shape)
output_size = np.prod(output_shape)
- if input_size != output_size:
+ if input_size != output_size and not shape_inferencing:
error_result = True
info_dict = {
@@ -2510,6 +2516,56 @@
}
return info_dict
+ @staticmethod
+ def evReshapeOutputSizeMultiInference(check=False, **kwargs):
+ error_name = ErrorIf.ReshapeOutputSizeMultiInference
+ param_reqs = {"rank": None, "dtype": None, "shape": None}
+ error_result = False
+ error_reason = "Reshape output tensor contains more than one inferred dimension"
+
+ if check:
+ output_shape = kwargs["output_shape"]
+ inferences = 0
+ for dim in output_shape:
+ if dim == -1:
+ inferences += 1
+ if inferences > 1:
+ error_result = True
+
+ info_dict = {
+ "error_name": error_name,
+ "error_result": error_result,
+ "error_reason": error_reason,
+ "param_reqs": param_reqs,
+ }
+ return info_dict
+
+ @staticmethod
+ def evReshapeOutputSizeNonInteger(check=False, **kwargs):
+ error_name = ErrorIf.ReshapeOutputSizeNonInteger
+ param_reqs = {"rank": None, "dtype": None, "shape": None}
+ error_result = False
+ error_reason = "Reshape inferred output tensor dimension is non-integer"
+
+ if check:
+ input_shape = kwargs["input_shape"]
+ output_shape = kwargs["output_shape"]
+ input_size = np.prod(input_shape)
+ output_size = 1
+ for dim in output_shape:
+ if dim != -1:
+ output_size *= dim
+ if -1 in output_shape and input_size % output_size != 0:
+ error_result = True
+
+ info_dict = {
+ "error_name": error_name,
+ "error_result": error_result,
+ "error_reason": error_reason,
+ "param_reqs": param_reqs,
+ }
+ return info_dict
+
class TosaInvalidValidator:
@staticmethod