MLBEDSW-2637 Refactor util funcs out of softmax.py

There were a number of "TensorUtil" functions defined in softmax.py
These have been moved to their respective classes for Tensor and
Operator respectively.
Two of the functions were not a simple tensor/op function. These helper
functions have been moved to tensor.py for the simple fact that they
return Tensor's

Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: I17d39c4e11f0837b7867b4a54da2e4a56383e095

1 files changed, 43 insertions, 0 deletions

diff --git a/ethosu/vela/tensor.py b/ethosu/vela/tensor.py
index c2d6b6e5..98487324 100644
--- a/ethosu/vela/tensor.py
+++ b/ethosu/vela/tensor.py
@@ -21,8 +21,10 @@ import uuid
 import numpy as np
 
 from . import numeric_util
+from .data_type import DataType
 from .ethos_u55_regs.ethos_u55_regs import resampling_mode
 from .numeric_util import round_up_divide
+from .operation import Operation
 from .range_set import MemoryRangeSet
 
 
@@ -231,6 +233,38 @@ class QuantizationParameters:
         return res
 
 
+def create_const_tensor(name, shape, dtype, values, value_dtype=None, purpose=TensorPurpose.Unknown, quantization=None):
+    # Tensor
+    const_tensor = Tensor(shape, dtype, name + "_0")
+    const_tensor.purpose = purpose
+    const_tensor.quantization = quantization
+    const_tensor.values = np.array(values, dtype=value_dtype)
+    const_tensor.quant_values = np.frombuffer(const_tensor.values.tobytes(), dtype=np.uint8)
+    # Operator
+    const_op = Operation("Const", name)
+    const_op.set_output_tensor(const_tensor)
+    return const_tensor
+
+
+def create_reshape_tensor(tens, shape, ifm_reshape=True):
+    if shape == tens.shape:
+        return tens
+    # Tensors
+    name = tens.name + "_reshape"
+    reshape_ifm = tens
+    reshape_ofm = tens.clone("_reshaped")
+    reshape_ofm.set_all_shapes(shape)
+    if not ifm_reshape:
+        reshape_ifm, reshape_ofm = reshape_ofm, reshape_ifm
+    # Operator
+    reshape_op = Operation("Reshape", name)
+    reshape_op.attrs["new_shape"] = shape
+    reshape_op.add_input_tensor(reshape_ifm)
+    reshape_op.add_input_tensor(create_const_tensor(name + "_shape", [1], DataType.int32, shape))
+    reshape_op.set_output_tensor(reshape_ofm)
+    return reshape_ofm if ifm_reshape else reshape_ifm
+
+
 class Tensor:
     __slots__ = (
         "shape",
@@ -696,6 +730,15 @@ class Tensor:
         self.storage_shape = shape
         self.bandwidth_shape = shape
 
+    def get_full_shape(self):
+        d = len(self.shape)
+        if d in (1, 3):
+            return [1] * (4 - d) + self.shape
+        elif d == 2:
+            return [self.shape[0], 1, 1, self.shape[1]]
+        else:
+            return self.shape
+
     def __str__(self):
         return "<nng.Tensor '%s' shape=%s dtype=%s>" % (self.name, self.shape, self.dtype)